The 2030 Travel Forecast for Santa Barbara County

Transcription

1 The 2030 Travel Forecast for Santa Barbara County 180,000 Highway 101 (Caltrans Control Stations) Daily Traffic Comparison, 2000 & , , , ,000 80,000 60,000 40,000 20,000 0 SLO Co. Line 101 n/o Betteravia 101 s/o Rt n/o Los Carneros 101 n/o Las Positas 101 n/o Salinas 101 n/o Vta Co. Line Caltrans Cts 2000 Modeled Vol 2030 Modeled Vol Final Report September 16, 2004

2 PROJECT STAFF Jim Kemp Michael G. Powers William F. Yim Jim Damkowitch Brian Bresolin Executive Director Deputy Director, Planning Transportation Planner II / Author Transportation Planner II Regional Analyst Financial support for the preparation of this report was furnished by the Federal Highway Administration, Federal Transit Administration, and the State of California. 2

3 Table of Contents Page Executive Summary 7 I. Introduction 9 Background 9 II. III. Presentation of Forecast Data The 2000 Base Case and 2030 Forecast 11 Model Forecasts and Interpretation 11 The No-Project Scenario 12 Forecast Adjustments Baseline Programmed Projects, Modeling Assumptions and Methodology 13 How Person Trips and Vehicle Trips are Generated 14 4-step Modeling 15 Peak Spreading 16 Level of Service and V/C Ratios 17 IV. Modeling Standards and Requirements 18 Transportation Air Quality Conformity and Modeling Requirements 18 Model Performance standards and Validation Criteria 19 Count Data Availability and Model Output Comparison 20 V. The 2030 Demographic Growth Forecasts 22 Structure of Forecast Model Growth Forecasts 25 The 2030 Countywide and South Coast Growth Forecast 25 VI Travel Forecast 27 The 2030 Countywide and South Coast Traffic Forecast Summary 27 Traffic Growth by State Route ( ) 28 The Highway 101 Corridor Forecast 33 Comparison with Caltrans Control Station Counts 36 Highway AM & PM Peak Hour Forecasts 39 South Coast Highway BC AM Peak 39 South Coast Highway BC PM Peak 40 South Coast Highway AM and PM Peak 42 3

4 North County Highway BC 46 North County Highway Forecast 48 Traffic Growth by Sub Area 50 Carpinteria 51 Montecito and Milpas Areas 51 City of Santa Barbara 52 Goleta 53 Santa Ynez Valley 54 Lompoc and VAFB Areas 55 Orcutt 56 Santa Maria 56 Guadalupe 57 VII. Transit Ridership Forecast 59 VIII. Conclusion 61 Page IX. Attachments 62 Appendix I - Model Performance Charts Appendix II - AM Peak Hour Exhibits X. References 72 \\Grp-SBCAG\migs\TTAC\2004 Mtgs\Sept\Full Final Fcst Rpt doc 4

5 List of Tables and Exhibits Page Table III-1: Programmed Projects, Modeling Assumptions and Methodology 13 Table III-2: V/C Ratios and Travel Conditions 17 Table IV-1: Number of Network Links with Counts by 3-Time Periods, 2000BC 21 Table IV-2: Number of Network Links with Counts by Roadway Classification by CCD, 2000BC 21 Table V-1: 2030 Demographic Forecast, Santa Barbara County 25 Table V-2: 2030 Demographic Forecast, Santa Barbara County 26 Table VI-1: 2030 Countywide and South Coast Growth Forecast 27 Table VI-2: 2030 Traffic Growth at County Borders 28 Table VI-3: 2030 Traffic Growth by State Route 28 Table VI-4: Highway 101 Corridor Daily Traffic Forecast 34 Table VI-5: Highway 101 Traffic Forecast Vs. Caltrans Control Station Counts 36 Table VI-6: South Coast Highway 101, 2000 Traffic by Direction 40 Table VI-7: South Coast Highway 101, 2030 Traffic Forecast by Direction 44 Table VI-8: North County Highway 101, 2000BC Traffic by Direction 46 Table VI-9: 2030 Travel Forecast for Carpinteria Area 50 Table VI-10: 2030 Travel Forecast for Montecito and Milpas Areas 51 Table VI-11: 2030 Travel Forecast for the City of Santa Barbara 52 Table VI-12: 2030 Travel Forecast for Goleta Area 53 Table VI-13: 2030 Travel Forecast for Santa Ynez Valley 54 Table VI-14: 2030 Travel Forecast for Lompoc and VAFB areas 55 Table VI-15: 2030 Travel Forecast for Orcutt Area 56 Table VI-16: 2030 Travel Forecast for Santa Maria 57 Table VI-17: 2030 Travel Forecast for Guadalupe 57 Table VII-1: 2030 Transit Ridership Forecast 59 Exh. V-1: Element of Forecast Model 24 Exh. VI-1: 30-Year Traffic Growth by state Route 28 Exh. VI-2: Santa Barbara County Traffic Growth by State Route ( ) 30 Exh. VI-3: Santa Barbara County 2000BC Flow & V//C Ratios 31 Exh. VI-4: Santa Barbara County 2030 Traffic Forecast, Flow & V//C Ratios 32 Exh. VI-5: South Coast Highway 101, Daily Traffic Forecast ( ) 35 Exh. VI-6: North County Highway 101, Daily Traffic Forecast ( ) 35 Exh. VI-7: Highway 101 Traffic Forecast Vs. Caltrans Control Station Counts 36 Exh. VI-8: Highway 101- Milpas to Ventura Co. Line, 2000BC Flows & V/C Ratios 37 Exh. VI-9: Highway 101- Milpas to Ventura Co. Line, 2030 Traffic Forecast, Flows & V/C Ratios 37 Exh. VI-10: Highway 101- SB & Goleta Areas, 2000BC Flows and V/C Ratios 38 Exh. VI-11: Highway 101- SB & Goleta Areas, 2030 Flows and V/C Ratios, Flows & V/C Ratios 38 Exh. VI-12: South Coast Highway 101, 2000BC AM Peak Traffic by Direction 39 Exh. VI-13: South Coast Highway 101, 2000BC Traffic by Direction 41 Exh. VI-14: South Coast Highway 101, Milpas to Ventura Co. Line PM Peak Flows & V/C Ratios 42 Exh. VI-15: South Coast Highway 101, 2030 AM Peak Traffic by Direction 43 Exh. VI-16: South Coast Highway 101, 2030 PM Peak Traffic Forecast by Direction 43 Exh. VI-17: Highway 101, 2030, Milpas to Ventura Co. Line, PM Peak Flows & V/C Ratios 45 Exh. VI-18: Highway 101, 2030 SB and Goleta Areas, PM Peak Flows & V/C Ratios 45 Exh. VI-19: North County Highway 101, 2000BC PM Peak Traffic by Direction 47 Exh. VI-20: Highway 101 Santa Maria & Orcutt Areas, 2000BC Peak Flows & V/C Ratios 47 Exh. VI-21: North County Highway 101, 2030 PM Peak Traffic by Direction 48 Exh. VI-22: Highway 101 Santa Maria & Orcutt Areas, 2030 PM Peak Flows & V/C Ratios 49 Exh. VI-23: Lompoc & Vicinity, 2030 PM Peak Hour Flows &V/C Ratios 49 5

6 Appendix I: Model Performance Charts AADT Vs. Model Volume Scattergram 63 Average Trip Lengths, Caltrans Survey Vs. Model 63 Highway 101 Daily Traffic Comparisons ( ) 64 Flow Comparison by Screenline 64 Maximum Desirable Deviation in Screenline Volumes 65 Count Flow Comparisons by Link Classification 65 Model Validation Criteria 66 Count Flow Comparisons by Link Classification & RMSE 66 Comparisons of Model Capacity & Speed Relations 67 Volume Delay Curves 67 Highway BC PM Peak Hour Congestion Speeds Vs. V/C Ratios, SB Direction 68 Highway PM Peak Hour Congestion Speeds Vs. V/C Ratios, SB Direction 68 Appendix II AM Peak Hour Exhibits Highway BC, Milpas to Ventura County Line, AM Peak Flows and V/C Ratios 69 Highway BC, Santa Barbara & Goleta Areas AM Peak Flows and V/C Ratios 69 Highway , Milpas to Ventura County Line AM Peak Flows and V/C Ratios 70 Highway , Santa Barbara & Goleta Areas AM Peak Flows and V/C Ratios 70 North County Highway BC AM Peak Traffic by Direction 71 North County Highway 101, 2030 AM Peak Traffic by Direction 71 6

7 Executive Summary In response to the need to replace and update the SBCAG Travel Demand Model, the Santa Barbara County Association of Government initiated the SBCAG Model Replacement and Update project in October After two and half years of development, the SBCAG new regional travel model is now completed. Preparation of this report is the result of the completion of the SBCAG new model. The new SBCAG travel model provides significant improvements and utility over the old regional travel model and is an important transportation planning tool. This staff report documents the model development, summarizes major modeling assumptions, demographic forecasts, and presents major findings for the 2000 Base Case (2000BC) and the 2030 forecast. The travel model forecasts growth in traffic and person trips out to 2030 based on the growth assumptions in the Regional Growth Forecast Traffic forecasts are presented for all external stations, the Highway 101 Corridor, state routes and significant roadways and local streets. The model forecasts average daily traffic (ADT), AM peak hour, PM peak hour, and midday peak trips, although the latter is not documented in this report because midday peak is used less frequently than AM and PM peak hour forecasts. The 2030 forecast is developed based on the assumption that all the 2030 capital improvement projects programmed in the 2002 Transportation Improvement Plan (TIP) were to be implemented and completed. Project details were finalized based on local and the Technical Transportation Advisory Committee (TTAC) input with additional inputs from the Technical Advisory Group (TAG) members of the 101 IM project. The SBCAG model is fully calibrated in accordance with the federal and state guidelines and performance standards for model accuracy. Part of the process is to ensure the model is calibrated based on the best available data sources, i.e., the 2001 Caltrans Households Travel Survey, and other data sources such as the SBCAG 2002 Commuter Survey, 2000 Census Transportation Planning Package (CTPP) Journey-to-Work data, the 2000 Statewide Travel Model Update, and our neighboring county s model forecasts. A major step leading to the model accuracy is the model validation process. Some of the important elements include validation of roadway links by functional classification, vehicle miles traveled, and regional screenline volumes. The SBCAG model performs well and exceeds all federal and state guidelines and standards with assignment validation statistics for correlation at and "R-squared" at 0.93 (standard is 0.88). The model volumes were also compared against ground counts for each sub-area to ensure a higher level of model accuracy. Between April and August, the model has gone through a thorough review process in which the model assumptions, output, and preliminary forecasts were presented to TTAC, local jurisdictions, the 101 In Motion (101IM) Travel Forecast Subcommittee, and the South Coast Sub-Regional Planning Committee for review and comments. SBCAG staff has responded to all comments and worked with the model development consultant to further refine and update the model and subsequent forecasts. The following describes some of the highlights of the 2030 forecast findings. The most notable growth is on the principal Highway 101 corridor at both north and south county borders. By 2030, traffic on Highway 101 at the SLO County line is forecast to increase from 7

8 58,500 to 95,400 vehicle trips, a 63% increase. Traffic on 101 at the Ventura County line is forecast to increase from 60,000 to 96,800 vehicle trips, representing a 61% increase. Traffic on Route 1 at the SLO county line is forecast to increase 72% reaching 11,200 ADT. On the South Coast, Highway 101 corridor segment between Turnpike and the Ventura County line is projected to experience severe congestion on both directions during the PM peak hour. In particular, during the PM peak, traffic on Highway 101 southbound is projected to experience stop-&-go condition with significant delay. In the North County traffic on Highway 101 segments between Clark Ave and SLO County line is forecast to deteriorate from free flow to moderately congested travel conditions even with the 6-lane widening between Santa Maria Way and the county line. However, it is likely that congested conditions on Highway 101 will continue due to the congestion north of the SLO County line. Over the past several months TTAC has received reports on the development of the travel model. This last month staff presented the travel model to the full board and received comments. Recently TTAC met to consider this forecast report. TTAC unanimously approved of the model for use in air quality conformity analysis. TTAC approved of the application of the travel model for use in regional travel analysis with continued refinements and adjustments to address local concerns. Staff will send this report to our federal and state partners as documentation of the travel model that SBCAG will use for conformity assessments of our Federal Transportation Improvement Plan (FTIP) and Regional Transportation Plan (RTP) as well as future updates of our county s Clear Air Plan. Staff believes we will receive approval to use the model in our conformity analysis. The travel model will also be used by the consulting team for the Highway 101IM Study. Staff will also apply the model in the Central Ave/SR 246 corridor study. 8

9 I. Introduction The report documents the 2000 and 2030 travel forecasts for Santa Barbara County. Preparation of this report is the result of the completion of the SBCAG Travel Demand Model Replacement and Update project initiated in October The purpose of this report is: To update the previous 2020 Travel Forecast for Santa Barbara County To provide the long-term forecast and input for the ongoing 101 In Motion (101IM) project consulting team, and, To prepare travel forecast for several important documents including the Regional Transportation Plan (RTP) update, the Conformity Analysis of the Federal Transportation Improvement Program (FTIP), and other future independent travel studies such as the Route 246/Central Avenue Traffic Forecast. This report is organized into the following chapters as follows: I. Introduction II. Presentation of Forecast Data III. Base Line Programmed Projects and Modeling Assumptions IV. Model Validation Criteria and Performance V. The 2030 Demographic Growth Forecasts VI Travel Forecast VII. Transit Ridership Forecast VIII. Conclusion Background The SBCAG Travel Demand Model Replacement and Update project was initiated in October Caliper Corporation was selected as the prime model development consultant following a competitive RFP selection process. Part of the model consulting team also includes Dowling Associates, responsible for the link capacity analysis and development of the Intersection Level of Service (LOS) module, and PBConsult, responsible for the development of the Transit Mode Choice Model. The software TransCAD is the core travel demand software for the new model. TransCAD provides full travel forecasting and GIS capabilities in one single software package. It is currently the leading and state-of-the-art travel forecasting software in the U.S. with appropriately 70% of users being State Departments of Transportation (DOTs), Metropolitan Planning Organizations (MPOs), universities and academic institutions, and leading transportation planning agencies. For the last two and half years, staff, working closely with the consulting team, overcame numerous challenges during the model development process, including the development of a comprehensive model database, reconciling various data sources and deficiencies, and overcoming various technical challenges along the way. In January 2004, the preliminary 2000 base year model was completed. Results were presented to the Model Development Technical Advisory Committee (TAC). In April 2004, the 2030 Daily and a 3-time (AM, Midday, PM) Peak Hour Model were completed. Between April and August, 9

10 the model results, model performance, and preliminary forecasts were presented to TTAC, California Department of Transportation (Caltrans) District 5, local jurisdictions, the 101In Motion (101IM) Travel Forecast Subcommittee, and the South Coast Sub-Regional Planning Committee for review and comment. The following summarizes the review process: Model Development TAC Meetings ( ) Four TTAC Meetings (January August 2004) Ongoing 101IM Technical Advisory Group (TAG) & Travel Forecast Subcommittee meetings since January 2004 South Coast Sub-Regional Planning Committee, July 2004 In August, staff responded to all comments. Working extensively with Caliper staff, the model was further updated and refined. Subsequent forecasts were revised. A simplified version of the calibrated model and forecasts were presented to the SBCAG Board on August 19, 2004 for review and to receive comments. This report presents a full and complete report of the SBCAG Travel Forecast resulting from the completion of the SBCAG model development. Recently TTAC met to consider this forecast report. TTAC unanimously approved of the model for use in air quality conformity analysis. TTAC approved of the application of the travel model for use in regional travel analysis with continued requirements and adjustments to address local concerns. 10

11 II. Presentation of Forecast Data The 2000 Base Case and 2030 Forecasts The traffic forecast contained in this report includes two sets of forecasts: the 2000 Base Case (2000 Base Year) and the 2030 forecast. The 2000BC model contains traffic count data for 2000 and modeled volumes for the year The 2030 forecast contains a 30-year forecast developed as part of the input to the ongoing 101IM project and to meet the planning horizon requirements of the 2004 Regional Transportation Plan (RTP) Update. The 2030 forecast represents a long-term programmed project forecast. This forecast assumes the completion and implementation of all capital improvement projects currently programmed between 2000 and Further discussion of this forecast is provided in later sections. At the request of the 101IM project team, an interim (2010) year forecast was also completed to help analyze the traffic congestion on the South Coast Highway 101 corridor. The 2010 forecast is not included in this report. However, the delivery of the model for the 101IM project team will include the 2010 interim forecast. In the subsequent supplement to this report, the 2010 forecast will be provided as well. Model Forecasts and Interpretation Model forecasts presented in this report include daily forecast under an average weekday condition. Daily volumes are expressed in terms of average daily traffic (ADT) or daily vehicle trips. The peak hour forecasts contain three one-hour peak periods during AM, Midday and PM for the 2000BC and the 2030 forecast. The 3-time peak periods presented herein are defined as follows: AM Peak Hour: Midday: PM Peak Hour: 7:00-8:00 AM 12:00 Noon - 1:00 PM, and 4:00-5:00 PM PM peak is most heavily traveled time during the day. The PM peak hour is normally used for critical peak analysis. The second most heavily traveled time is normally the AM peak when the trips to work and school begin. The noon (Midday) period, 12:00 to 1:00 PM was elected as a midday peak hour. In some localized areas in the Santa Ynez Valley and in Santa Maria, the Midday peak is nearly comparable to the AM peak. In general, the Midday forecast, is less pronounced than the AM and PM peaks. For purposes of this report and for reasons of the sheer volumes of data for reporting, only AM and PM peak hour volumes are reported. The Midday forecast will be provided on an upon request basis. Other specific hours within the average weekday including the shoulder hours of the peak as well as off-peak hours are not modeled, but are reflected as part of the 24-hour ADT forecasts. 11

12 The 2030 No Project Scenario Part of the model development process also includes a 2030 No-Project or Do-Nothing scenario. The purpose of this scenario is to examine the question: How worse could the congestion be if absolutely no projects were to be constructed after the 2000 base year? Essentially this scenario represents a hypothetical situation in which none of capital improvement projects, either programmed or planned, would be completed, i.e., a classic do-nothing scenario, applying the 2000BC network to the 2030 demographic forecast. Though this scenario is not likely, it serves as a test during the model development process for gauging the reasonableness of the 2030 (Programmed) Forecast. The output of this scenario is not part of the final report. Forecast Adjustments One of the comments received during the review process was to present the final forecast results based on an adjustment of the differences between the modeled volume and base year counts. Whereas this is a traditional and reasonable modeling procedure, staff made no such adjustments to the model output to account for the differences between modeled volumes and ground count data. The reasons for not making such adjustment are several: 1. To preserve and demonstrate the true performance of the model: Comparison between counts and modeled volumes on roadway segments (links), particularly on the 2000BC where counts are available, would genuinely demonstrate the model s accuracy. 2. To allow flexibility in adjustment: For any travel forecasting exercise, one of the objectives is to obtain the relative change or relative magnitude of the future travel conditions rather that the absolute values. Keeping the original modeled volumes would preserve these relative differences. 3. To account for uncertainty of count data: Count data could involve a number of uncertainties such as seasonality, human intervention, equipment failures, weather and roadway characteristics at the time of data collection, time spent during data collection, etc 4. To be consistent in forecast data reporting: Given that only approximately 17% of the total model links have counts, the base year adjustment approach would encounter the problem of inconsistency within the adjustment process since some links would be able to adjustment while other would not. For purposes of consistency, retaining the original modeled volumes with comparison to base counts and forecast would allow reader to visual the performance of the model. The forecast tables contain count data, whenever available, base year modeled volumes and future forecast volumes. (Also see discussion in the counts availability section) 12

13 III Baseline Programmed projects, Modeling Assumptions and Methodology As discussed earlier, the 2030 travel forecast was developed based on the assumption that all the 2030 capital improvement projects programmed in the 2002 Transportation Improvement Program (TIP), as indicated in Table III-1, were to be implemented and completed. This project list is one of the primary sources in the development of the 2030 modeling network. Project details were finalized based on local and TTAC inputs together with additional inputs from the Technical Advisory Group (TAG) members of the 101IM project. Technical modeling assumptions for adjustments of the 2030 network are also included in this table. Table III-1: Programmed projects and Modeling Assumptions FTIP Project Description Modeling Assumptions Programmed Improvements Programmed Projects Network: State Highways Rt 101 /Rt 135 Interchange Included Included Included Const new diamond I/C w/nb loop ramp. Bridge 2-ln ea dir + center LT ln. Complete 08/09 FFSpeed 30, Ln Cap 1800 Rt.101/Fairview - Add turn lanes, replace bridges Included Included Included Completed in 2000, Add LT pocket at 101 SB Ramp after bridge Rt.246 (101 to Buell Flat Rd) - Widen for LT lane. Included Included Included Increase capacity 50 vplph capacity betw 101 and Buell Flat Road.. Rt.135/UVP - Const. at-grade intersection Included Included Included Add at-grade intersection on 135. Rt.101/L. Carneros Interchange - Widen approach to SB on-ramp Included Included Included Add 50 cap. on 101SB on ramp. Rt.101/Hollister - Relocate interchange to join C. Oaks Ext'n. Included Included Relocate interchange align with Hollister. Rt.101/Donovan - Widening O/C, ramps improvements Included Included Included Add to 2010, 2020, 2030 networks, see Measure D Exhibit faxed on 3/15/04 Rt.101/Stowell - Reconst. Interchange, widening O/C Included Included Included Add to 2010, 2020, 2030 networks, see Measure D Exhibit faxed on 3/15/04 Rt.101 SM Way-SLO County line - Widen to 6-lane Included Included Included Modify as specified. Rt.154, SB to Lake Cachuma, Operat'l Improve'ts, Grp II Included Included Included Add capacity 50 vplph at spec locations, See Measure D exh. 101/Milpas Interchange reconst, const. Cacique undercrossing Included Included Included Modify as specified, add 101 undercrossing. 101 (Rt.144 to Hot Springs SB) - Add auxi. lane Included Included Included Add SB Aux. Lane, part of 101 Ops Improvements 101 (Hot Springs - Milpas NB) - Add auxi. (3rd) lane Included Included Included Add NB Aux. Lane, part of 101 Ops Improvements 101 Hot Springs/Cabrillo - Improve interchange Included Included Included See attached exhibit provided earlier, roundabout at HotSp/OC Hwy 101 (Evans - Sheffield NB) - Add auxiliary lane, const. C1 bikeway Included Included Included Added NB Aux. Lane. 101/Linden & 101/Casitas Pass - Reconst I/C + R.Real betw I'Cs and extn to Creek. Included Included Alt A1 as per previous exhibit vplph with 1 lane each dir. Via Real - Const. frontage road betw ICs (part of I/C proj) Add link betw. I/Cs, 900 vplph cap., 2-lane, See Exh Alt. A1 Via Real Ext'n across Carp. Creek (part of I/C proj) Modify as specified. Rt.101/Carrillo Blvd. - Widen NB ramp to 2-lane, Ramp metering Included Included Included Increase cap. with 50 vplph on 101 on-ramp. Rt.101/UVP - Const. full diamond interchange Included Included Included Add full diamond interchange on 101. Rt.101/Storke - Improve I/C w/ 2 LT, 1 RT & one auxiliary lane Included Included Included Modify 101SB OnRamp to 3 ln merg'g to 1. Add 50 vplph (Aux Ln already in BC Netwk) Rt.166 (SM to Guadalupe) - Widen for additional capacity (for Ag Truck passing.safety) Included Included Increase 5 mph to Free-Flow speeds Rt.166 (SM to Guadalupe) - Widen to 4 lanes Included Modify as specified (4 lanes) Rt.246 (Buellton to Lompoc) - Widen to 4 lanes Included Included Change segment from 2 to 4 lanes. 101 Bridge over SM River - Widen for additional lane Included Included Add add'l lane each direction to 3 lanes each dir. South County Hollister at Patterson Ave - Add exclusive RT on Hollister WB appr. Included Included Included Completed in 2002, add 50 vplph app. cap. Lillie/Evan Rd. Intersection - intersection improvement Included Included Included No network adjustments necessary. Calle Real (Patterson to Kellogg) - Widen to 4-lane Included Included Included Modify as specified. Evans Ave/Ortega Hill Rd - Improve intersection, widen 101 NB ramp Included Included Included No network adjustments necessary. Fowler Rd Ext. - Const. road ext & I/S at Kellogg with Pine Included Included Included Add link ( 700 cap vplph 35 mph), 2-ln at-grade Kellogg, pine. Ekwil Rd Ext. - Const. road ext & I/S at Kellogg Fairview Included Included Included Add link ( 700 cap vplph 35 mph), 2-ln at-grade Kellogg, Fairview. El Colegio (Camino Corto to UCSB Westgate - Widen to 4-lane Included Included Per County's comments, proj controversal, but potential completion by Fairview/Calle Real - Add NB LT on Fairview & EB LT on Calle Real Included Included Included Add 50 vplph on all approaches Hollister/Storke - Widen I/S w/dual LT all apps. & excl. RT & 3rd thru. Included Included Included Add 100 vplph on Hollister and Storke due to dual LTs. Hollister/L. Carneros - Add NB LT on L. Carneros, LT on WB Hollister Included Included Included Add 50 vplph on Hollister approaches North County UVP - Const E/W arterial from Hummel Dr. to Blosser Road. Included Included Included Add 800 cap vplph, 45 mph, 1-lane each dir. Hummel Drive Extension (existed in BC) Included Included Included Connect two existing unconnected segments City of Guadalupe Pioneer St extension to 11th Street in City of Guadalupe Included Included Add Pioneer St from 8th St with extension to 11 St. City of Santa Barbara Las Positas Road/Cliff Drive Intersection Improvement Included Included Included No network adjustments necessary. City of Santa Maria College Dr Ext (betw Battles and Betteravia) Included Included Included Modify as specified. UVP - Const. arterial from Rt.135 to Blosser Road Included Included Included Add 800 cap vplph 45 mph. Alignment n/o Clubhouse Dr. Blosser Rd (Cook to north city limit) - Widen to 4-lane Included Included Included U/G to Minor 800 Cap. 4-lane. Miller St. (Stowell - Cook St.) - Widen to 4-lane Included Included Included Modify as specified. Miller St. (Chapel to Alvin Ave.) - Widen to 4-lane Included Included Included Modify as specified. Betteravia / Bradley - Add Dual Left Turn Lanes Included Included Included Modify as specified or add 50 vplph approach Cap Betteravia (Rte. 101 to Blosser Rd.) Signal Interconnect Included Included Included Off-Model Emissions Analysis 1/ This table is based on the Table 7 of the 2002 FTIP network analysis, programmed projects. Shaded rows are for SBCAG info only. They denote projects that were removed from 1999 RTP 2005 Model network. File: Full Fcst Rpt/Fnl Full Rpt 2030PH SubASum Tbls New 13

14 How Person and Vehicle Trips Are Generated The SBCAG model follows the state-of-the-practice approach in the model development. Generation of person trips by trip purpose is primarily based on the socioeconomic factors such as households, employment, and income. Regional models such as the SBCAG Travel Model are traditional socioeconomic data-based models. These models allow users to consistently employ socioeconomic database on a region-wide basis. Such an approach is employed by most Metropolitan Planning Organizations (MPOs) and Regional Transportation Planning Agencies (RTPAs) simply because socioeconomic factors offer direct relationships with vehicular travel. The SBCAG Regional Growth Forecast (RGF) 2000 also provides a comprehensive and consistent demographic database and growth forecasts on a countywide and on each sub-region basis. The SBCAG model employs the socioeconomic data-based approach. The database consists of households, employment, household size, household income, and special generators of employment centers such as UCSB, the Vandenberg Air Force Base (VAFB), and other tourist attractions, plus other elements of the 2000 Census data. The employment database was based on the InfoUSA employment database, a nationwide employment database that tracks employer statistics such as employer addresses, employer categories and number of employees. This database is currently being used by the Census Bureau for Census 2000 activities with updates provided by MPOs across the county. During the model database development process, the employment database was further refined and redistributed by Traffic Analysis Zones (TAZ) based on local input, staff research, and field surveys to ensure accuracy for the 2000 base year. The employment database was initially updated to reflect additional employment from 1999 to 2000, and subsequently edited to ensure all major employers were included. For example, a number of major shopping centers in the InfoUSA database do not contain employment numbers and had to be researched by using building square footage ratios to estimate employment. Other discrepancies in the InfoUSA database include the underestimation of employment in the healthcare facilities and omission of greenhouses on the South Coast and were subsequently added based on information from the local jurisdictions and SBCAG staff field survey. One of the differences between the model database and the RGF database is that in the Regional Growth Forecast 2000 employment estimates are based on zip code level data from the State of California Employment Development Department showing wage and salary employment. Wage and salary employment data does not include the self-employed workers so it has a tendency to underestimate total employment. Substantial effort was therefore made to update the InfoUSA database for accuracy to the extent possible. Some travel models are land use data-based. These land use data-based models are more refined and are normally employed by local jurisdictions for sub-area analysis since land use models have finer zones and local networks which allow closer examination of traffic impacts resulting from local developments. Local models such as the Santa Maria Model and the Goleta Model are land use data-based models. 14

15 4-step Modeling The SBCAG model follows the traditional 4-step modeling practice, i.e., Trip Generation, Trip Distribution, Mode Choice, and Assignment. Trip generation predicts the number of person trips that are generated by and attracted to each zone. In trip generation, cross classification submodels are applied to predict trip productions and regression sub-models are employed for trip attractions. A balancing mechanism is applied to ensure the number of productions equals to attractions over a 24-hour period. Trip Distribution models are used to predict the spatial pattern of trips between origin and destinations. The SBCAG model employs a traditional gravity model calibrated with impedance parameters to reflect distance and travel times between zones. The trip distribution model is also calibrated based on the trip length frequency distribution from the Caltrans Travel Survey. Mode Choice models are used to analyze and predict the choices of travel mode in trip making. The goal is to predict the share or the absolute number of trips made by each mode. The SBCAG mode choice model is a multi-layer nested logit model in which modes are initially separated by motorized and non-motorized modes. The next layer further separates the motorized trips into auto, carpool, and transit. The goal is to predict the share of absolute number of person trips by mode, including auto, carpool, and transit trips before these trips are converted to vehicle trips for highway network and transit network assignments. For the first time, the SBCAG model incorporates a new transit mode choice model to handle the various transit operators in the county (SBMTD, SMAT, COLT, Clear Air Express (CAE) etc.) Transit mode choice model incorporates a number of modeling elements, including operators (modes) and their respective route systems, frequency, route stops, fares, and transit accessibility parameters, etc. The goal of the transit mode choice model is to predict the number of person trips who would like take certain transit mode. The total transit trips would then be loaded onto the transit network for transit assignment. The output of the transit mode choice model is daily ridership (boardings) and annual ridership. Prior to the assignment step, a P-A to O-D transformation procedure is required to convert production and attraction matrices to origins and destinations as well as to convert person trips into vehicle trips through the use of vehicle occupancy factors. The final step in the 4-step process is the assignment process. The SBCAG model employs the User Equilibrium (UE) assignment method, which takes into account the volume and travel time and calculates roadway segment flows. The key behavioral assumptions of UE are that every traveler has perfect information concerning the network alternatives, and travelers choose routes that minimize their travel time. UE utilizes an iterative process to achieve a convergent solution in which no traveler can improve his/her travel time by shifting route. In each iteration link flows are computed, which incorporates link capacity restraint effects and flow-dependent travel times. For example, on the critical stretch of Highway 101 between Milpas and Ventura County line, as assigned flows reach the theoretical capacity of the limited available roadway system, the model will continue to assign onto the available network. The Highway 101 segments would continue to receive flows despite higher V/C ratios. This assumes that travelers would be traveling at the expense of delay (slower speeds), particularly during the one hour peak period (4-5 PM) as defined in the SBCAG PM Peak Hour Model. 15

16 The peak hour model output provided in this report are specifically modeled for the defined AM and PM peak hours in order to investigate the magnitude or the worst case scenario. In reality, because of severe congestion, peak spreading of demand would likely occur. Peak Spreading Peak spreading is a behavioral response that occurs when the capacity of the transportation system is severely constrained in the highest demand portion of the peak period. To avoid severe congestion, travelers would tend to start either their trips earlier or later in the peak hour thereby spilling flows into neighboring hours. Thus in reality the total PM peak volume presented herein may be dampened somewhat because of the peak spreading phenomenon. The issue of peak spreading and the effect of the peak spreading would need to be addressed in more detail by the 101IM project consultant using a post-process approach. Comments from TTAC have emphasized the importance of addressing peak spreading and will be addressed by the 101 IM project. Level of Service and V/C Ratios The primary output produced by the model is traffic volumes expressed in terms of Average Daily Traffic (ADT). The ADT is modeled under an average weekday. Traffic volumes presented in the forecast sections are expressed in terms of flows. Part of the model output also provides a scaled-symbol theme that scales each side of the roadway segment (link) with the volumes (flows) in terms of bandwidth assigned to it. The model generates a color theme using flows on each roadway directional link and applies a color to each side of the link to indicate the level of congestion expressed in terms of volume-to-capacity (V/C) ratios. V/C ratios are automatically calculated by the TransCAD software as part of traffic assignment process. The varying colors from green to orange and red (different shades of gray color for black and white copies) represent the different levels of volume-to-capacity (V/C) ratios, which in turn approximates the level of traffic congestion or levels of service (LOS) during the average weekday or peak hour conditions. Green color presents V/C ratios under 0.5, which generally approximates travel conditions with free flow and unimpeded traffic conditions. Light green represents V/C ratios of 0.5 to 0.75, which approximates free-flow traffic conditions. Yellow represents V/C ratios between 0.75 and 1.0 and roughly represents traffic volumes approaching moderate to serious congested conditions with frequent delays. Red color represents V/C ratios of 1.0 or greater and represents severe congested conditions whereby stop-and-go roadway condition is frequent. The V/C ratios modeled under the peak hour conditions is a relatively reliable measure of the future performance of the roadway segments, particularly the Highway 101. Table III-2 summarizes the relative interpretations between V/C Ratios and roadway travel conditions. 16

17 Table III-2: V/C Ratios and Travel Conditions Color Scheme V/C Ratios Roadway Travel Conditions Dark Green > 0.25 Traffic unimpeded, free flow Light Green Free flow Light Yellow Moderate, some restrictions on maneuverability Dark Yellow Serious, traffic approaching capacity, slow speed, some delay Orange Severe, forced or break-down flow, frequent delay Red > 1.25 Severe, stop-n-go, significant delay File: SC Sub-Reg Cmte/VC Ratios Color Scheme

18 IV. Modeling Standards and Requirements Regional model development and performance are generally governed by a number of federal and state requirements. Two of the major requirements relate to transportation air quality conformity requirements, and meeting modeling performance standards and validation criteria. The following section describes these requirements. Transportation Air Quality Conformity and Modeling requirements Pursuant to Section (b)(1) of the transportation conformity regulation, areas designated as non-attainment or maintenance for federal air quality standards must satisfy minimum transportation modeling requirements to ensure the veracity of travel activity inputs used for air quality modeling. The network modeling assumptions of the Santa Barbara Travel Model are documented below. 1. Network Model Validation: The SBCAG Model base year is Validation of the 2000 base year was based on observed ADT and peak hour counts. Model forecast results for 2010, 2020, and 2030 are to be analyzed for reasonableness and compared to historical trends and other factors. 2. Land Use, Population, and Employment: All socio-economic assumptions of the Santa Barbara Travel Model are based on SBCAG 2002 Regional Growth Forecast. For a description of SBCAG regional growth forecasting process (see Section V). 3. Consistency of Land Development and Use with Future Transportation System Alternatives: Future scenarios of land development and use were developed from local agency general plans that in turn are consistent with the general plan circulation elements. In general, programmed and planned transportation improvements flow from these circulation elements. Assessments of the potential growth inducing impact of capacity increasing infrastructure improvements are considered during the conformity regional emissions analysis. 4. Capacity Sensitive Assignment: The SBCAG Model utilizes a form of the Bureau of Public Roads (BPR) volume delay equations to adjust travel speeds based on the level of congestion (volume-delay). To better represent the volume delay characteristics between functional class of roadways, models are recommended to use equations to reflect various roadway classifications. SBCAG model employs three BPR equations to reflect various roadway class including freeways, arterials and collectors and below. The model employs a user-equilibrium assignment algorithm. 5. Zone-to-zone Travel Impedances between Trip Distribution and Trip Assignment: To ensure consistent use of link speeds, the SBCAG Model provides the necessary congested speed feedback loops between the trip distribution and trip assignment models. 6. Model Sensitivity to Time(s), Cost(s) and Other Factors Affecting Travel Choices: The model currently employs travel impedances that represent travel time, based on speed and distance. Bus fare costs are used directly as part of the transit mode choice model. Given that no toll roads or bridges currently exist in the county, generalized costs in addition to bus fares have not been incorporated into the model at this time. 18

19 Additional conformity modeling requirements related to traffic model validation include: reasonable methods to estimate traffic speeds and delay (Section (b)(2)) and HPMS estimates of regional VMT (Section (b)(3)). For an explanation of speed and delay estimation see response to Section (b)(1) (iv) and (v) above. With respect to the use of HPMS data, SBCAG uses HPMS VMT estimates to track its VMT forecasts. Historically, HPMS based VMT adjustment factors have not been used. SBCAG will continue to evaluate the merit of HPMS based VMT adjustment factors during future updates to the Santa Barbara Travel Model. Model Performance Standards and Validation Criteria FHWA and Caltrans provide model performance guidelines and validation criteria to ensure the performance of regional models. Essentially, the two processes required in any model development process relate to model calibration and validation. Model calibration is typically conducted for each step of the 4-step modeling process. For example, large variations of screenline estimates may imply incorrect trip distributions. Trip generation rates must be adjusted to Santa Barbara County conditions to avoid incorrect estimates. Inaccurate link estimates can imply incorrect network attributes. Incorrect modechoice estimates may affect any or all of the above. As an example, calibration of the trip assignment includes identifying model specifications and adjusting the volume-delay equations to adequately represent Santa Barbara County conditions. Model volumes must be calibrated on link class basis and compared them to facility types. Adjustments to the volume delay equations or the trip assignment method can impact general over- or under estimation of link volumes. Model validation process ensures the model attains a reasonable degree of accuracy. Part of the process is based on the use of best available data sources, i.e., the 2001 Caltrans Travel Survey data, and other sources such as the 2002 Commuter Survey, 2000 CTPP JTW data, the 2000 Statewide Travel Model Update, and our neighboring county s model forecasts, etc. The following are some of the criteria employed in the model calibration and validation process: Trip Rates Development from Caltrans Survey Consistency with Average Trip Length and Time by Trip Purpose Consistency with Trip Length Frequency by Trip Purposes Peak Hour Percentages by Trip Purpose from Caltrans Survey CTPP JTW data and 2002 Commuter Survey data for commute data External Trip Data from examining various sources including The Statewide Travel Model, VCTC/SCAG model data, and historical regional traffic trends. The SBCAG model is fully validated according to the federal and state guidelines and performance standards for model accuracy. These guidelines and performance standards include: Model volumes by link classification AADT Vs. Model Volume Scattergram VMT and VHT by link classification Assignment validation statistics Maximum desirable deviation by screenline volume 19

20 Screenline validation statistics The model s performance exceeds all of the guidelines and validation criteria. As an example, in the assignment validation statistics, the standard calls for an assignment correlation of The SBCAG model assignment correlation is 0.96 with the R-Squared of Appendix I (Model Performance Charts) contains the SBCAG Model performance in comparison with the federal and state model performance standards and criteria. Count Data Availability and Model Output Comparison Comparison of model volumes against ground counts is an important part of model validation. As discussed earlier, model volumes are validated based on roadway functional class and volume. For example, higher functional class such as freeway and principal arterials, which normally carry larger travel volumes (10,000 ADT and above), are recommended to be within 5 to 10% deviation with counts and lower functional class such as collectors (with volumes of 5,000 and under) to be within 25 to 35%, depending on federal and state standards. The standards in California are stricter in that freeway and principal arterial volume deviation with counts must be under 7% and collectors under 25%. The SBCAG model performance is well within these standards. Exhibit VI-7 in Section VI (2030 Travel Forecast) presents the comparison between model volumes and Caltrans traffic counts at seven control stations along the entire Highway 101 corridor. The results are quite consistent. An extra level of scrutiny to achieve a higher level of model accuracy is the comparison of representative links with counts against modeled volumes by each sub-area. The Traffic Growth by Sub Area in Section VI provides examples of these comparisons. While this is not a model validation requirement by federal and state standards, staff employed this technique to ensure a high-quality model work product. Peak Hour Counts and Data Availability During the initial development of the peak hour models, only a total of approximately 110 peak hour counts were available for the defined 3-time periods. The limited amount of peak hour counts, particularly AM peak and Midday counts, was a major concern in the validation of the peak hour model. In view of the need to validate the peak hour volumes, staff made an extensive effort to expand the peak hour counts. These efforts include supplementing the peak hour count data from local jurisdictions, researching counts from available traffic and environmental documents, and incorporating Congestion Management Program (CMP) and HPMS counts for the defined time periods. This effort allowed staff to significantly increase the total number of links with peak hour counts from 110 to 890. Table IV-1 summarizes the total number of links available with counts under each of the 3-time periods. Currently the model contains 227 links with AM counts, 149 links with Midday peak counts and 514 links with PM peak counts. 20

21 Table IV-1: Number of Network Links with counts by 3-Time Periods, 2000 BC Number of Links with Counts, 2000BC CCD With AM Counts With Midday Counts With PM Counts Total Links w/ counts Total Network Links % Links With Counts Carpinteria CCD % Santa Barbara CCD , % Lompoc CCD % Santa Ynez CCD % Santa Maria CCD % County Unincorp. CCD , % TOTAL , % Table IV-2 presents a breakdown of the number of links with counts by higher order roadway classifications (Freeway, Other Principal Arterial, and Minor Arterial functional class). These higher order functional classes are crucial in the development of credible peak hour models. The number of links with counts for each time period and their relative percentages to total links within the higher roadway class is provided. Table IV-2: Number of Network Links with Counts by Roadway Classification by CCD, 2000BC Links with counts > or = Fwy, OPA, and MA With AM Counts with Midday With PM Total Network % Link with CCD Counts Counts Total Links Counts Carpinteria CCD % Santa Barbara CCD , % Lompoc CCD % Santa Ynez CCD % Santa Maria CCD % County Unincorp. CCD , % TOTAL , % The general validation requirements suggest an estimation of 10% links with counts. In event that this requirement is not achievable, it is recommended that as many counts for higher roadway classification such as freeways and arterials as possible be used. As indicated in Tables IV-1 and IV-2, a total of 16.7% links with counts are available in the SBCAG model, in which a total of 13.5% are links with counts for higher roadway classification (freeways, other principal arterials, or minor arterials). 21

22 V. The 2030 Demographic Growth Forecasts Santa Barbara County, Regional Growth Forecast 2000 presents a forecast of population, employment, and land use to the year 2030 for Santa Barbara County, its major economic and demographic regions, and its eight incorporated cities. Hereafter it is referred to as the Regional Growth Forecast, or the RGF Structure of Forecast Model Forecasting population, employment and land use is a complex process. To simplify this process the forecast is disaggregated into three sub models; 1) population, 2) employment, and 3) constraints. The population and employment models are linked by the constraints model. The RGF 2000 assumes that no major natural, or man made disasters, e.g., catastrophic earthquakes, will significantly disrupt the area during the forecast period. While our seismic history suggests that a significant seismic event could occur during the forecast period of 30 years, it is beyond the ability of the forecaster to foresee the magnitude and impacts of such an event. The population model provides population forecasts for Santa Barbara County, each of five subregions, and each of the eight cities within the county. Chapter II of the forecast report describes in detail the results of the population forecast. The forecast spans the period 2000 to It uses 1990 census data as a baseline, and is calibrated using 1990 to 2000 population, housing and demographic estimates from the Department of Finance and other sources such as the State Department of Health for birth and mortality rates. For each 5 year forecast period and geographic region, the model forecasts male and female population by five-year age groups (0-4, 5-9, etc.). Another variable in the population model is net migration. The model receives input in the form of migrants coming in and out of Santa Barbara County. In-migrants may arrive in search of a new job, education, or other reasons. Out-migrants leave due to lack of housing or employment. Migrants are either added or subtracted from the existing population that age over time. The population model also adds new births and subtracts out deaths to the population by applying age specific birth and mortality rates. Every 5 years the age group is advanced, or aged, so that over time someone born in 2000 will be 30 years of age in The population model also contains a separate assessment of the "fixed aged" population residing at institutions such as the University of California, Santa Barbara (UCSB). This institution generally cycles people in-and-out of school on a rotating basis so that the population does not generally age, as does the population that stays in the area for a longer period. The "group quarters" population is also forecast separately since it contains a special population, e.g., correctional facilities, dormitories, and group care homes. This group quarters population does not utilize conventional housing units. They are not considered part of the household population that requires a housing unit. The employment model forecasts the number and type of jobs for each subregion by five-year increments (2000, 2005, etc.). Chapter III of the full report describes in detail results of the employment model. The countywide employment forecast is based on an assessment of economic trends and historical employment data. The countywide forecast is then allocated to 22

23 subregions and economic sectors based on zip code level employment data. There is no employment forecast for individual cities and unincorporated areas. Commercial, retail and industrial land availability, as derived from the local community land use plans, is taken into consideration as a potential limiting factor. The forecast also estimates the potential increase in the workforce, due to more women entering the labor force etc. As stated earlier, the employment database was refined for the travel model to fill some gaps, e.g., retail shopping centers, greenhouse employment, etc. The constraints model limits the potential rate and buildout of residential development and may therefore limit new housing available for those in-migrants who arrive to take new jobs or persons who are born in the area and wish to stay. Chapter III of the full report describes in detail the results of the constraints model. The constraints model places a limit on the rate at which new housing is developed and a ceiling on the "ultimate" buildout of each jurisdiction. This ultimate buildout is based on the potential for additional housing as allowed by the community land use plans of each jurisdiction. As population (from the population model) increases (due to new births minus deaths and net migration), they are converted into households by assuming a certain number of persons per household. The constraints model limits new housing supply. For areas where the supply falls short of demand, population is allocated elsewhere to other jurisdictions within Santa Barbara County or to Ventura or San Luis Obispo County. The constraints model links the employment model to the population model by the generation of new workers who are able to fill the new jobs estimated in the employment model. New workers occur due to a variety of factors such as more women entering the labor force, new immigrants, and a natural increase of younger workers while some workers retire and leave the labor force. The constraints model balances the available housing units, with the workers (using a workers per household density), and population (using a household size density). Exhibit V-1 describes the characteristics of the population, employment, and constraints models. Each of the factors relies on a considerable amount of data and assumptions to produce a 30- year forecast. Much of the accompanying texts in the following chapters describe these assumptions as well as the forecast results. 23

24 Exhibit V-1 Elements of the Forecast Model POPULATION Component Aging Population for Cities and Unincorporated Areas. Methodology Births, Deaths, Net Migration, for each 5 year period. Group Quarters: Vandenberg AFB, UCSB Dorms, U.S. Penn. Program changes and constant proportion. CONSTRAINTS Component Provide a ceiling on total new development. Limit new residential construction for every five year forecast period. Methodology Potential increase in housing, population and employment limited by buildout of General Plans and persons/workers per household. Historical permit activity or policy based limits. EMPLOYMENT Component Number of jobs for subregions and economic sectors. Methodology Trend for countywide employment allocated to areas by type using zip code level employment data.

25 2030 Growth Forecasts Table V-1 summarizes the 2030 demographic growth forecast for Santa Barbara County. Total population is projected to increase from 399,000 in 2000 to 523,500 in 2030, representing an increase of approximately 31%. Similarly, the total number of households is projected to increase from 136,600 to 167,000, a 22% increase and employment is projected to increase from 200,300 to 278,500, a 39% increase respectively. Among the five major employment categories, the service sector, which represents the largest employment category, is expected to grow approximately 40% by 2030 whereas the industrial sector is expected to double the employment for the same period. Table V-1: 2030 Demographic Forecast, Santa Barbara County Parameter % Incr. Population 399, , % Households 136, , % Employment 200, , % Employment Office 14,222 15, % Industrial 20,377 44, % Service 86, , % Commercial 63,179 75, % Agricultural 15,711 21, % Total Employment 200, , % The 2030 Countywide and South Coast Growth Forecasts As discussed earlier, the forecast used to generate new person and vehicle trips in the travel model is based on the SBCAG Regional Growth Forecast 2000 adopted by the board in March, The forecast is based on an assessment of demographic and economic growth trends generating new jobs, households, and population whose locations are constrained by the capacity of local land use plans (in effect during 2000) to accommodate future growth. This countywide growth potential from land use plans, using the year 2000 as a baseline, is significant; 33,000 potential units countywide and 30 million square feet of potential new industrial, commercial, and retail development. Table V-2 summarizes the comparison of population, households, and employment forecasts between the County and the South Coast. As a comparison, population, households, and employment on the South Coast represent approximately 50%, 54% and 61% of the county s totals in 2000, are forecast to increase by 21%, 13% and 38% respectively. Total South Coast employment is forecast to increase 38% by the year

26 Table V-2: 2030 Demographic Forecast, Santa Barbara County Countywide South Coast South Coast as % of County Parameter % Incr % Incr Population 399, , % 201, , % 50.3% 46.5% Households 136, , % 73,700 82, % 53.9% 49.6% Employment 200, , % 121, , % 60.7% 60.4% Employment Office 14,222 15, % 10,237 10, % 72.0% 68.4% Industrial 20,377 44, % 12,808 28, % 62.9% 62.9% Service 86, , % 51,260 71, % 59.0% 58.7% Commercial 63,179 75, % 39,011 46, % 61.7% 61.2% Agricultural 15,711 21, % 8,308 11, % 52.9% 55.9% Total Employment 200, , % 121, , % 60.7% 60.4% 26

27 VI Travel Forecast The 2030 travel forecast in this section is presented in the order of countywide, the Highway 101 South Coast, the Highway 101 North County, and under each sub-area. Forecast travel volumes are presented in terms of ADT or vehicle trips under daily, AM and PM peak hour. Daily volumes are presented to the nearest 100 vehicle trips. Peak hour volumes are presented to the nearest 10 vehicle trips. The 2030 Countywide and South Coast Traffic Forecast Summary Table VI-1 summarizes the 2030 Countywide and South Coast travel forecasts. Traffic on Highway 101 at the Ventura County line is forecast to increase by 61%, from 60,000 in 2000 to 96,800 ADT in This represents approximately 1.6% growth per year. This compares with a 2.1% annual growth at the same location projected by the Ventura County Transportation Commission (VCTC) Travel Model between 1994 and At the San Luis Obispo County line, traffic is forecast at 95,400 ADT, presenting an approximate increase of 63% or 1.7% growth per year. This growth is also quite consistent with 1.6% for the 10 year growth period at this location between 1991 and Table VI-1: 2030 Countywide and South Coast Growth Forecast Countywide 2000 Base Case 2030 Prog d % Incr Base Case South Coast 2030 Prog d % Incr Veh. Trips: 101 SLO Co. line 58,500 95, % NA NA NA Veh. Trips: 101 Vta Co. line 60,000 96, % 60,000 96, % Total Person Trips 1,897,432 2,587, % 1,017,053 1,311, % Total Vehicle Trips 1,349,744 1,827, % 730, , % Total Veh. Hours Traveled 231, , % 118, , % Total Veh. Miles Traveled 9,746,101 15,468, % 5,059,718 7,370, % Trips / Household Avg. Trip Lengths (Min.) Avg. Trip Distance (Miles) By 2030, total countywide vehicle miles traveled (VMT) is forecast to increase from 9.75 million in 2000 to million in 2030, an increase of approximately 59%. Total South Coast VMT, which represents approximately 52% of the total current county s VMT is forecast to increase from 5.06 million in 2000 to 7.37 million in 2030, representing an increase of 46%. The increase of VMT is attributable to an increase in the number of average trips per household (from 9.8 to 10.9 trips), longer average trip length (from 16.8 to 20.7 minutes) and the average trip distance from 9.2 miles to 11.5 miles countywide. 1 On the South 1 According to the 2001 Caltrans Household Survey, the average weekday trip length in Santa Barbara County has increased from 13 minutes in 1991 to 16 minutes in Similarly, the average weekday trip length for home-based work (HBW) trips in Santa Barbara County has increased from 16 minutes to 20 minutes for the same ten-year period. 27

28 Coast, the average trip length is projected to increase from 7.6 miles in 2000 to 9.1 miles by Traffic Growth by State Route ( ) Tables VI-2 and VI-3 summarize the overall 30-year traffic growth for Highway 101 at the north and south county borders and for each state route in the county. In addition, traffic on Route 1 at the SLO county line is forecast to grow from 6,500 to 11,200 ADT, representing an average annual increase of 1.8%. Exhibit VI-1 summarizes the 30 year traffic growth for each state route. Table: VI-2: 2030 Traffic Growth at County Borders % An. Highway 101 Counts 2000 Modeled Vol 2030 Modeled Vol Growth Vta Co. line 60,000 60,000 96, % SLO Co. Line 60,000 58,500 95, % Rt. SLO Co. Line 4,800 6,500 11, % Table: VI-3: 2030 Traffic Growth by State Route % An. State Routes Counts 2000 Modeled Vol 2030 Modeled Vol Growth Rt 1 s/o VFBF Gate 18,000 22,700 33, % Rt. 166 e/o Cuyama 2,000 1,600 1, % Rt 246 w/o 154 8,500 14,300 23, % Rt 246 Buellton & Lompoc 9,500 11,400 31, % Rt ,000 15,600 25, % Rt. 1 w/o 101 7,200 8,300 18, % Rt ,500 18,200 19, % Rt. 192 n/o C. Pass 2,000 3,000 10, % Rt ,000 2,200 10, % Exhibit VI-1: 30-Year Traffic Growth by State Route 35, Traffic Growth for Each State Routes 30,000 25,000 20,000 15,000 10,000 5,000 - Rt 1/135 Rt. 166 e/o Cuyama Rt 246 w/o 154 Rt 246 Buellton & Lompoc Rt. 154 Rt. 1 Rt. 217 Rt. 192 Rt. 150 Counts 2000 Modeled Vol 2030 Modeled Vol 28

29 Traffic on Route 154 is forecast to reach 25,700 ADT by Traffic on Route 1 between Highway 101 and Lompoc is forecast to increase to 18,100 ADT and traffic on Route 1 at the VAFB Main Gate, is projected to increase to 33,300 ADT. In the Santa Ynez Valley, traffic on Route 246 is forecast to increase 63% taking into account the future Chumash Casino expansion and the build out of land use plans in Buellton, Solvang, and the Santa Ynez Valley. Traffic on Route 246 between Buellton and Lompoc is forecast to increase from 11,400 to 31,800 ADT reflecting the land use plans in North Lompoc (Vandenberg Village, Mesa Oaks, Mission Hills, and the Wye Area). On the South Coast, because of the future congestion on Highway 101 between Milpas and Ventura County line, traffic on Route 192 is forecast to increase from 3,000 ADT in 2000 to 11,200 ADT, despite its physical and geometric constraints (lack of shoulders, tight curves and slow speeds). Exhibit VI-2 provides an overview of the 30-year traffic growth for each state route in the county. Exhibits VI-3 and VI-4 present the travel conditions on all state routes in this county. In general, for the 2000 base year travel conditions on all state routes are primarily under free flow conditions. However, for 2030, traffic on Highway 101 south of Route 246, and segments between 154 and Orcutt area would approach capacity. Some delays and slower speed during peak periods is projected. 29

30 Exhibit VI-2: Santa Barbara County Traffic Growth by State Route ( ) 30

31 Exhibit VI-3: Santa Barbara County 2000BC Flows & V/C Ratios 31

32 Exhibit VI-4: Santa Barbara County 2030 Traffic Forecast Flows and V.C Ratios 32

33 The Highway 101 Corridor Forecast This section describes the 30-year traffic growth along the entire Highway 101 Corridor. Forecast data are presented in terms of total volumes by roadway segments and by direction. Highway 101 is the principal N/S arterial serving both inter-county and inter-regional travel. Because it serves local, regional, and statewide needs, this roadway is subject to greater scrutiny. Table VI-4 and Exhibits VI-5 to VI-11 summarize the 2000BC and 2030 traffic forecasts on the entire corridor under the average weekday travel conditions. Traffic increase on Highway 101 can be summarized in three major freeway segments: The 26-miles stretch on the urbanized South Coast (between the Ventura County line and Winchester Canyon), The rural freeway segments between Winchester Canyon and Clark Ave in Santa Maria, and The urban freeway segments between Clark Ave and the SLO County line. In general, traffic on Highway 101 between Ventura County line and Winchester Canyon is forecast to experience significant growth. Between the Ventura County line and Milpas, the most critical corridor segment of the freeway, congestion is forecast to worsen. As indicated in Table VI-4, the entire 101 segment from Milpas to the Ventura County line is forecast to range from congested conditions to severely congested conditions by At Milpas, traffic is forecast to reach a total of 125,900 ADT. Traffic on 101 between Milpas and Fairview would experience the highest total flows, ranging from 101,900 to 147,760 ADT. These segments will also experience the smallest percentage increases but the highest vehicular travel because of the existing high travel volumes. Traffic on Highway 101 north of Las Positas would reach a total of 161,900 ADT, presenting the location with the highest traffic flow for the entire Highway 101 corridor. Traffic on Highway 101 between Winchester Canyon and Clark Ave in Santa Maria is forecast to double the existing volume, from 30,000 to approximately 60,000 ADT. Between Clark Ave in Santa Maria and the SLO County line, traffic is forecast to grow between 58-63%. Traffic on 101 north of Clark is forecast to double the existing flow. On Highway 101 north of Stowell, traffic is forecast to reach 105,900 ADT. Exhibits VI-5 and VI-6 presents the daily traffic volumes for the entire Highway 101 corridor in absolute terms. In these exhibits, the light color (yellow) bars are counts and dark color (magenta) bars are 2000 modeled volumes and the red line reflects the 2030 forecasts. 33

34 Table VI-4: Highway 101 Corridor Daily Traffic Forecast, ( ) ADT 2000 Daily 2030 ADT 2030 Daily % Incr. Highway Counts 2000 Modeled Vol NB SB 2030 Modeled Vol NB SB SLO Co. Line 60,000 58,500 29,400 29,100 95,400 48,000 47,400 63% 101 n/o Donovan 50,000 50,600 24,500 26,100 83,600 41,100 42,500 65% 101 n/o Main 53,000 57,800 29,200 28,600 99,900 49,000 50,900 73% 101 n/o Stowell 55,000 64,400 31,100 33, ,900 51,900 54,000 64% 101 n/o Betteravia 54,000 65,300 30,000 35, ,500 48,400 55,100 58% 101 n/o SM Way 36,000 42,500 19,200 23,300 79,800 38,100 41,700 88% 101 n/o Clark 33,500 33,000 16,300 16,700 60,500 30,300 30,200 83% 101 n/o Rt ,000 31,700 16,000 15,700 59,400 29,900 29,500 87% 101 n/o Rt ,500 23,000 11,600 11,400 43,400 21,900 21,500 89% 101 s/o Rt. 1 29,500 27,600 13,900 13,700 58,500 29,500 29, % Daily 2030 Daily % Incr. Highway 101 Daily Counts 2000 Modeled Vol NB SB 2030 Modeled Vol NB SB n/o Hollister I/C 36,000 35,900 18,000 17,900 68,900 34,600 34,300 92% 101 n/o G. Annie 38,000 33,300 17,200 16,100 68,100 35,000 33, % 101 n/o L. Carneros 60,000 57,000 27,400 29,600 79,100 38,600 40,500 39% 101 n/o Fairview 72,000 70,100 34,500 35,600 91,400 45,200 46,200 30% 101 n/o Patterson 81,000 82,300 40,500 41, ,900 50,400 51,500 24% 101 n/o Turnpike 119, ,900 61,600 61, ,400 71,500 71,900 17% 101 n/o , ,900 64,200 62, ,760 74,360 73,400 16% 101 n/o L. Positas 135, ,820 72,000 67, ,900 83,600 78,300 16% 101 n/o Mission 137, ,000 66,200 68, ,300 76,200 80,100 16% 101 n/o Carrillo 126, ,200 60,200 60, ,100 74,000 72,100 22% 101 n/o Castillo 106, ,600 54,600 52, ,000 69,000 66,000 27% 101 n/o Garden 94,000 98,900 49,900 49, ,400 66,100 64,300 32% 101 n/o Milpas 94, ,700 54,600 52, ,900 62,700 63,200 18% 101 n/o Salinas 95,000 93,900 47,600 46, ,800 64,800 60,000 33% 101 n/o Cabrillo/HS 95,000 91,000 44,700 46, ,000 59,000 60,000 31% 101 n/o Olive Mill 83,000 89,900 45,400 44, ,500 53,800 55,700 22% 101 n/o Sheffield 80,000 92,500 46,200 46, ,400 52,100 52,300 13% 101 n/o Padaro 77,000 90,700 45,600 45, ,500 51,300 51,200 13% 101 n/o Linden 72,000 77,500 39,800 37,700 99,700 50,500 49,200 29% 101 n/o C. pass 67,000 69,900 34,800 35,100 97,800 48,900 48,900 40% 101 n/o Bailard 70,000 70,900 35,200 35,700 95,000 47,600 47,400 34% 101 n/o ,000 61,700 30,900 30,800 94,100 46,900 47,200 53% 101 n/o Vta Co. Line 60,000 60,000 31,200 28,800 96,800 48,700 48,100 61% File: 2000 Mdl Pre/new flw tbles/101newflwdir xls 34

35 Exhibit VI-5 : South Coast Highway 101, Daily Traffic Forecast ( ) 180, , , , ,000 80,000 60,000 40,000 20,000 0 South Coast Highway 101 Daily Traffic Forecast ( ) 101 n/o Hollister I/C 101 n/o G. Annie 101 n/o L. Carneros 101 n/o Fairview 101 n/o Patterson 101 n/o Turnpike 101 n/o n/o L. Positas 101 n/o Mission 101 n/o Carrillo 101 n/o Castillo 101 n/o Garden 101 n/o Milpas 101 n/o Salinas 101 n/o Cabrillo/HS 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Padaro 101 n/o Linden 101 n/o C. pass 101 n/o Bailard 101 n/o n/o Vta Co. Line Daily Counts 2000 Modeled Vol 2030 Modeled Vol Exhibit VI-6: North County Highway 101, Daily Traffic Forecast ( ) 120,000 North County Highway 101 Daily Traffic Forecast ( ) 100,000 80,000 60,000 40,000 20,000 0 SLO Co. Line 101 n/o Donovan 101 n/o Main 101 n/o Stowell 101 n/o Betteravia 101 n/o SM Way 101 n/o Clark 101 n/o Rt n/o Rt s/o Rt Counts 2000 Modeled Vol 2030 Modeled Vol 35

36 Comparison with Caltrans Control Station Counts Part of the model performance analysis of the model output is to ensure the reasonableness of the model output. Table VI-5 and Exhibit VI-7 provide a comparison between peak hour flows for the 2000BC and 2030 forecast on Highway 101 with the seven Caltrans Control Stations. These control station counts are consistently collected quarterly by Caltrans. The counts are adjusted for seasonally adjusted and therefore are considered the most accurate representation of 2000 travel volumes on the Highway 101 corridor. These Caltrans Control Stations are: North County Station 504: SLO County line Station SM4: 101 n/o Betteravia Station 503: 101 s/o Route 1 South Coast Station 120: 101 e/o Glen Annie Station 502: 101 n/o Las Positas Station W3: 101 s/o Salinas Station 501: 101 n/o 150 (n/o Ventura County Line) As indicated, the modeled volumes for the 2000 base case are found to be reasonably consistent with the counts. Table VI-5: Highway 101 Traffic Forecasts Vs. Caltrans Control Station Counts ADT 2000 Daily 2030 ADT 2030 Daily Highway 101 Caltrans Cts 2000 Modeled Vol NB SB 2030 Modeled Vol SB SB SLO Co. Line 60,000 58,500 29,400 29,100 95,400 48,000 47, n/o Betteravia 54,000 65,300 30,000 35, ,500 48,400 55, s/o Rt. 1 29,500 27,600 13,900 13,700 58,500 29,500 29, n/o Los Carneros 60,000 57,000 27,400 29,600 79,100 38,600 40, n/o Las Positas 135, ,820 72,000 67, ,900 83,600 78, n/o Salinas 95,000 93,900 47,600 46, ,800 64,800 60, n/o Vta Co. Line 60,000 60,000 31,200 28,800 96,800 48,700 48,100 File: 2000 Mdl Pre/new flw tbles/101newflwdir xls Exhibit VI-7: 180,000 Highway 101 Traffic Forecasts Vs. Caltrans Control Station Counts Highway 101 (Caltrans Control Stations) Daily Traffic Comparison, 2000 & , , , ,000 80,000 60,000 40,000 20,000 0 SLO Co. Line 101 n/o Betteravia 101 s/o Rt n/o Los Carneros 101 n/o Las Positas 101 n/o Salinas 101 n/o Vta Co. Line Caltrans Cts 2000 Modeled Vol 2030 Modeled Vol 36

37 Exhibit VI-8: Highway 101-Milpas to Vta Co. Line, 2000BC Flows & V/C Ratios Hw y 101 n/o Rt Exhibit VI-9: Highway 101-Milpas to Vta Co. Line, 2030 Traffic Forecast, Flows & V/C Ratios 37

38 Exhibit VI-10: Highway 101-Santa Barb & Goleta Areas, 2000BC, Flows and V/C Ratios Exhibit VI-11: Highway 101-Santa Barb & Goleta Areas, 2030 Traffic Forecast, Flows & V/C Ratios 38

39 Highway AM & PM Peak Hour Forecasts South Coast Highway BC AM Peak The PM peak between 4-5 PM is typically the most heavily traveled time during the day and is normally used for critical peak analysis. The second most heavily traveled time is the AM peak between 7-8 AM, where the majority of the daily commute occurs. Exhibit VI-12 summarizes the 2000BC for South Coast Highway 101 under the AM peak hour condition. The exhibit also provides an estimated freeway capacity for each direction to compare the demand and capacity in From the modeling standpoint, the freeway capacity is estimated to be at 1,900 vehicle per lane per hour (vplph), taking into consideration the freeway capacity data from the Highway Capacity Manual (HCM) 2000, Dowlings and Caliper s recommendations, and local freeway characteristics, including geographic constraints (narrow shoulders, left hand merge, limited spacing between interchanges, etc), and traffic mixed on 101. The following are general observations: During the AM peak, the northbound traffic is predominantly commuters. Volumes are predominantly higher than the southbound flow. Traffic on 101 northbound segments between Milpas and Padaro lane exceeds the estimated capacity, reflecting current severe congestion and slow speeds during morning peak hour. Northbound traffic between Turnpike and Mission is approaching capacity. Exhibit VI-12: South. Coast Highway 101, 2000BC AM Peak Traffic by Direction 7000 South Coast Highway Base Case AM Peak Traffic by Direction Est. Freeway Capacity for Each Direction n/o Hollister I/C 101 n/o G. Annie 101 n/o L. Carneros 101 n/o Fairview 101 n/o Patterson 101 n/o Turnpike 101 n/o n/o L. Positas 101 n/o Mission 101 n/o Carrillo Northbound 101 n/o Castillo 101 n/o Garden 101 n/o Milpas 101 n/o Salinas 101 n/o Cabrillo/HS Southbound 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Padaro 101 n/o Linden 101 n/o C. pass 101 n/o Bailard 101 n/o n/o Vta Co. Line 39

40 Table VI-6 summarizes the traffic in absolute terms for South Coast Highway BC AM peak hour by direction Table VI-6 South Coast Highway 101, 2000 Traffic by Direction Daily 2000 AM 2000 PM Highway 101 Daily Counts Northbound Southbound Northbound Southbound Northbound Southbound 101 n/o Hollister I/C 36,000 18,000 17, ,490 1, n/o G. Annie 38,000 17,200 16, ,470 1, n/o L. Carneros 60,000 27,400 29, ,940 2, n/o Fairview 72,000 34,500 35, ,280 2, n/o Patterson 81,000 40,500 41, ,480 3, n/o Turnpike 119,000 61,600 61, ,120 5, n/o ,000 64,200 62, ,550 5, n/o L. Positas 135,000 72,000 67, ,290 6, n/o Mission 137,000 66,200 68, ,750 6, n/o Carrillo 126,000 60,200 60, ,300 5, n/o Castillo 106,000 54,600 52, ,790 4, n/o Garden 94,000 49,900 49, ,280 4, n/o Milpas 94,000 54,600 52, ,400 4, n/o Salinas 95,000 47,600 46, ,790 4, n/o Cabrillo/HS 95,000 44,700 46, ,580 4, n/o Olive Mill 83,000 45,400 44, ,520 4, n/o Sheffield 80,000 46,200 46, ,560 4, n/o Padaro 77,000 45,600 45, ,510 4, n/o Linden 72,000 39,800 37, ,060 3, n/o C. pass 57,000 34,800 35, ,685 3, n/o Bailard 70,000 35,200 35, ,600 3, n/o ,000 30,900 30, ,160 3, n/o Vta Co. Line 60,000 31,200 28, ,180 3,440 File: SBCAG/Full Fcst Rept/101AMPMby Dir xls DateRevised: South Coast Highway BC PM Peak Exhibits VI-13 to VI-14 presents the South Coast Highway BC under the PM Peak Hour travel condition. Because of the significant amount of data to be presented in this report, only forecast data under the most critical PM peak hour conditions are presented. The following are the observations for the PM Peak Hour conditions: In general, during the PM peak hour conditions, the entire southbound stretch of Highway 101 from Turnpike to the Ventura County line is at severe congested conditions due to the insufficient hourly capacity on the freeway. This is particularly the case for traffic on southbound direction. Demand exceeds the estimated capacity on segments between Turnpike and Mission and between Milpas and Padaro lane. Exhibits VI-13 to VI-14 present two graphical images of travel conditions by direction on the South Coast Highway 101 under the 2000BC PM peak hour. As indicated, traffic on southbound Highway 101 is under severe stop-&-go conditions (red color) with significant delays, whereas the northbound direction is under severe congested condition (dark yellow) with frequent delays. 40

41 Exhibit VI-13: South Coast Highway Traffic by Direction 7,000 South Coast Highway Base Case PM Peak Traffic by Direction 6,000 5,000 Est. Freeway Capacity for Each Direction 4,000 3,000 2,000 1, n/o Hollister I/C 101 n/o G. Annie 101 n/o L. Carneros 101 n/o Fairview 101 n/o Patterson 101 n/o Turnpike 101 n/o n/o L. Positas 101 n/o Mission 101 n/o Carrillo 101 n/o Castillo Northbound 101 n/o Garden 101 n/o Milpas 101 n/o Salinas 101 n/o Cabrillo/HS Southbound 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Padaro 101 n/o Linden 101 n/o C. pass 101 n/o Bailard 101 n/o n/o Vta Co. Line Exhibit VI-14: Highway BC, Milpas to Ventura Co. Line PM Peak Flows & V/C Ratios 41

42 South Coast Highway Forecast South Coast Highway AM and PM Peak This section discusses the travel conditions under the 2030 AM and PM peak hour travel conditions. Exhibits VI-15 and Table VI-7 summarize the major findings of the 2030 PM Peak Hour forecasts. In general, the entire stretch of Highway 101 from Milpas and Ventura County line is projected to reach severe congested conditions. At the Ventura County line, the projected PM peak hour volume would be approximately 22% above the available capacity of the freeway. As a result, serious delay would occur. However, in reality peak spreading would probably occur where a portion of the projected PM peak volume would be pushed over to the neighboring hours. As discussed earlier, the peak spreading issue will further be examined by the 101IM consulting team. The traffic volumes during PM peak are much higher than the AM peak. By 2030, similar flow characteristics are projected, and much more critical in terms of the freeway performance. Consistent with the 2030 daily forecast, AM and PM peak traffic on the South Coast are predominantly higher on Highway 101 segments between Milpas and Turnpike. The percentage of PM peak to daily volume ranges from 8 % to 10% depending on location. Segments at or near the county borders normally have higher percentages for both 2000 and In both cases, the PM peak hour percentages are about 10%. For 2030 PM peak, the increase of traffic volumes is higher on the South Coast on segments between Ventura County line and Carrillo Interchange and between Los Carneros and Hollister Interchange in Goleta. Tables VI-7 provides AM and PM peak hour traffic forecasts for the entire Highway 101 corridor for 2000 base year and 2030 forecast year. Percentages of PM peak traffic to daily volumes are also provided. However, it should be noted that the future peak hour travel volumes do not take into account the issue of peak spreading. Exhibits VI-17 and VI18 presents two charts that compare the AM and PM peak hour volumes for 2030 for the entire South Coast Highway 101 corridor. PM peak volumes are much higher at the county border segments, particularly at the Ventura County line, indicating more future inter-county commute trips between Ventura and Santa Barbara during the PM peak. 42

43 At major interchanges such as Milpas and Carrillo, increase of PM peak hour traffic is significant. Approximately 3,000 to 3,800 vehicles would be added to the 2000 peak hour flows. Exhibit VI-15: South Coast Highway 101, 2030 AM Peak Traffic by Direction South Coast Highway AM Peak Forecast by Direction Est. Freeway Capacity for Each Direction SB 3 rd Lane NB Aux Lane n/o Hollister I/C 101 n/o G. Annie 101 n/o L. Carneros 101 n/o Fairview 101 n/o Patterson 101 n/o Turnpike 101 n/o n/o L. Positas 101 n/o Mission 101 n/o Carrillo 101 n/o Castillo Northbound 101 n/o Garden 101 n/o Milpas 101 n/o Salinas 101 n/o Cabrillo/HS Southbound 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Padaro 101 n/o Linden 101 n/o C. Pass 101 n/o Bailard 101 n/o Rt n/o Vta Co. Line Exhibit VI-16: South Coast Highway 101, 2030 PM Peak Traffic by Direction 8,000 7,000 6,000 5,000 Est. Freeway Capacity for Each Direction South Coast Highway PM Peak Forecast by Direction SB 3 rd Lane NB Aux Lane 4,000 3,000 2,000 1, n/o Hollister I/C 101 n/o G. Annie 101 n/o L. Carneros 101 n/o Fairview 101 n/o Patterson 101 n/o Turnpike 101 n/o n/o L. Positas 101 n/o Mission 101 n/o Carrillo Northbound 101 n/o Castillo 101 n/o Garden 101 n/o Milpas 101 n/o Salinas 101 n/o Cabrillo/HS 101 n/o Olive Mill Southbound 101 n/o Sheffield 101 n/o Padaro 101 n/o Linden 101 n/o C. Pass 101 n/o Bailard 101 n/o Rt n/o Vta Co. Line 43

44 Table VI-7: South Coast Highway Traffic Forecast by Direction 2030 Daily 2030 AM 2030 PM Highway 101 Northbound Southbound Northbound Southbound Northbound Southbound 101 n/o Hollister I/C 34,600 34, ,430 1, n/o G. Annie 35,000 33, ,170 1, n/o L. Carneros 38,600 40, ,410 2, n/o Fairview 45,200 46, ,300 3, n/o Patterson 50,400 51, ,460 4, n/o Turnpike 71,500 71, ,120 6, n/o ,360 73, ,430 6, n/o L. Positas 83,600 78, ,280 6, n/o Mission 76,200 80, ,770 7, n/o Carrillo 74,000 72, ,550 6, n/o Castillo 69,000 66, ,010 5, n/o Garden 66,100 64, ,520 5, n/o Milpas 62,700 63, ,730 6, n/o Salinas 64,800 60, ,070 5, n/o Cabrillo/HS 59,000 60, ,690 5, n/o Olive Mill 53,800 55, ,320 5, n/o Sheffield 52,100 52, ,090 5, n/o Padaro 51,300 51, ,060 5, n/o Linden 50,500 49, ,980 4, n/o C. Pass 48,900 48, ,850 4, n/o Bailard 47,600 47, ,770 4, n/o Rt ,900 47, ,450 5, n/o Vta Co. Line 48,700 48, ,490 5,750 Source: 2000 & 2001 Caltrans Traffic Volumes on State Highways websites. 1/ Based on modeled volumes. File: SBCAG/Full Fcst Rept/101AMPMby Dir xls Exhibits VI-17 and VI-18 present the graphs of the 2030 PM peak hour graphics for the South Coast 101 and the Santa Barbara and Goleta areas. 44

45 Exhibit VI-17: Highway , Milpas to Ventral Co. Line, PM Peak Hour Flows & V/C Ratios Exhibit VI-18: Highway , Santa Barbara and Goleta Areas, PM Peak Hour Flows & V/C Ratios 45

46 North County Highway BC 2000BC Daily Forecast This section describes the 2000BC and 2030 Daily Forecasts. This will include exhibits showing absolute volumes and graphics show North County roadway travel conditions, particularly on Highway 101. Table VI-8 provides 2000BC traffic for Highway 101 segments between Highway 101 south of Route 1 to SLO County line. Similar to the South Coast analysis, the table shows ground counts, 2000BC volumes and estimated capacity are presented. The following are general observations: Under the 2000 Base year conditions, in general, traffic on Highway 101 is under free flow conditions. For Highway 101 segment between Betteravia Road and SLO County line, traffic is approaching capacity and therefore, moderate travel conditions would occur whereby some travelers would experience restrictions in maneuverability and slower speeds, as indicated in Exhibits VI-19 and VI-20. In view of the relatively free flow conditions under the AM 2000BC conditions, only 2000BC PM Peak Hour charts and exhibits are presented here. Table VI-8: North County Highway 101, 2000BC Traffic by Direction ADT 2000 Daily 2030 ADT 2030 Daily Highway Counts 2000 Modeled Vol Northbound Southbound 2030 Modeled Vol Northbound Southbound SLO Co. Line 60,000 58,500 29,400 29,100 95,400 48,000 47, n/o Donovan 50,000 50,600 24,500 26,100 83,600 41,100 42, n/o Main 53,000 57,800 29,200 28,600 99,900 49,000 50, n/o Stowell 55,000 64,400 31,100 33, ,900 51,900 54, n/o Betteravia 54,000 65,300 30,000 35, ,500 48,400 55, n/o SM Way 36,000 42,500 19,200 23,300 79,800 38,100 41, n/o Clark 33,500 33,000 16,300 16,700 60,500 30,300 30, n/o Rt ,000 31,700 16,000 15,700 59,400 29,900 29, n/o Rt ,500 23,000 11,600 11,400 43,400 21,900 21, s/o Rt. 1 29,500 27,600 13,900 13,700 58,500 29,500 29,000 Total Increase 41,650 45,440 22,120 23,320 78,990 38,810 40,180 % Increase 73.8% 75.5% 72.3% 46

47 Exhibit VI-19: North County Highway 101, 2000BC PM Peak Traffic by Direction 6,000 North County Highway Base Case PM Peak Traffic by Direction 5,000 4,000 Est. Freeway Capacity for Each Direction 3,000 2,000 1,000 0 SLO Co. Line 101 n/o Donovan 101 n/o Main 101 n/o Stowell 101 n/o Betteravia 101 n/o SM Way 101 n/o Clark 101 n/o Rt n/o Rt s/o Rt. 1 Northbound Southbound Exhibit VI-20: Highway 101 Santa Maria & Orcutt Areas, 2000BC Peak Hour Flows & V/C Ratios 47

48 North County Highway Forecast By 2030, traffic on Highway 101 between Clark Ave and the SLO County line is forecast to increase 74%. The PM peak hour traffic volume is forecast to increase approximately 72%. Since the Highway lane widening between Santa Maria Way and SLO County line is assumed to be completed, travel conditions will ease but more traffic means more travelers on Highway 101 would still experience moderate congestion. The amount of traffic increase, particularly the northbound traffic under the PM peak conditions, would begin to approach freeway capacity. Travelers would experience some constraints in maneuverability on Highway 101 during PM peak. As indicated in Exhibits VI-21 and VI-22, part of the increase of traffic on 101 would shift congestion from North County along Highway 101 to north of the SLO County line. Exhibit VI-23 shows the 2030 PM peak hour forecast for the Lompoc area. Exhibit VI-21: North County Highway 101, 2030 PM Peak Traffic Forecast by Direction 6,000 5,000 North County Highway PM Peak Traffic by Direction Freeway Widened to 3-Lane Each Direction 4,000 3,000 2,000 1,000 0 SLO Co. Line 101 n/o Donovan 101 n/o Main 101 n/o Stowell Northbound 101 n/o Betteravia 101 n/o SM Way Southbound 101 n/o Clark 101 n/o Rt n/o Rt s/o Rt. 1 48

49 Exhibit VI-22: Highway 101- Santa Maria & Orcutt Areas, 2030 PM Peak Hour Flows & V/C Ratios Exhibit VI-23: Lompoc and Vicinity, 2030 PM Peak hour Flows and V/C Ratios 49

50 Traffic Growth by Sub Area The following section presents the 2030 travel forecasts for each sub areas in Santa Barbara County. The forecast of each sub-area is summarized in a similar table format. Forecasts are presented summarizing the base year counts and daily and PM peak hour volumes. Emphasis is provided on the PM peak hour, the most critical period among the three peak periods focusing on the growth of representative links during PM peak in order to visualize the impacts. The roadway segments from each sub area were either selected because of its significance to local traffic circulation, or as a result of a programmed capital improvement to reflect its travel impacts for the year The impacts on these roadway segments are discussed. The percentage change between the 2000 and 2030 during PM peak is also provided. Carpinteria Table VI-9 summarizes the 2030 travel forecast for Carpinteria area. The following highlights some of the forecast findings: Table VI-9: 2030 Travel Forecast for Carpinteria Area /01 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPHd PMPH n/o ,000 2,626 4,297 61,600 3,240 5,610 94,100 4,990 8, % SR192 C. Pass & Linden 2, , , % Casitas Pass s/o , ,152 7, , , % Casitas Pass n/o 101 5, , % Linden s/o , , , , % Linden n/o , , ,100 1,200 1, % Carpinteria, Linden & C. Pass 17, ,100 1,100 1,220 14,800 1,130 1, % Via Real s/o Bailard 8, , , % Via Real n/o Bailard 2, , ,290 NA Via Real e/o Linden NA Via Real, Linden & C. Pass , ,110 NA 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls By 2030, traffic on 101 north of Rt. 150 is forecast to increase from 61,600 ADT in 2000 to approximately 94,100 ADT by 2030, representing an increase of approximately 52%. PM peak traffic would reach 8,500 ADT. At this level, the travel condition would be at severe congestion with stop-&-go conditions. Because of the congestion on Highway 101, PM peak traffic on SR192 is forecast to increase over 100% from current level reaching 940 ADT. As a result of the new Casitas Pass/Linden Interchanges, more traffic is projected to use Linden Ave. This is particularly the case on the north side of Highway 101 since the new interchange would provide an easier access on and off the freeway. Traffic on Casitas Pass on the south side of the freeway is projected to increase approximately 78% during PM peak reflecting more use of the new interchange during the PM peak. 50

51 With Via Real fully extended to connect both Linden and Casitas Pass, daily traffic on this new roadway segment is forecast to increase from 2,600 in 2000 to 12,200 by PM peak traffic is forecast to reach 1,290 ADT. This roadway would undoubtedly become an important roadway for local access and circulation linking up the industrial park on the north side of the freeway and the nearby residential neighborhoods. As part of the interchange improvement, Ogan Street is planned to connect Linden Ave and the freeway via the Via Real Extension. Daily traffic on this roadway is expected to be significant, reaching 10,800, with PM peak hour traffic reaching 1,100 vehicle trips. With the connection to Bailard Interchange, Via Real would play a key role for local circulation. This increase in traffic also reflects the significant use of the Via Real Extension feeding local traffic to and from the industrial parks on both side of the freeway. Carpinteria Ave would remain as a major local E-W arterial serving the entire Carpinteria area. Montecito And Milpas Areas Table VI-10 summarizes the 2030 travel forecast for the Montecito and Milpas areas. The following highlights some of the forecast findings: Table VI-10: 2030 Travel Forecast for Montecito and Milpas Areas 1/ /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH Montecito 101 n/o Olive Mill 83,000 89,800 5,610 7, ,500 6,600 9, % 192 n/o Sycamore Cyn 5,200 4, , , % Ortega Hill Rd 4,700 2/ 4, , , % N Jameson Lane 4,300 2/ 1, , , % Sheffield 3,400 2/ 3, % Olive Mill Rd 6,400 2/ 4, , % Hot Springs Rd 11,800 2/ 13,800 1,040 1,130 14,000 1,080 1, % Coast Village Rd 12,700 2/ 8, , , % Old Coast Hwy 7, , , , % Cabrillo Blvd s/o , ,280 16, ,580 17,500 1,010 1, % Milpas Area 101 n/o Milpas I/C 94, ,700 7,090 9, ,900 9,230 11, % 101 s/o Milpas I/C 95,000 6,240 5,650 93,800 6,280 8, ,000 8,100 11, % Milpas n/o ,000 30,700 2,200 2,620 33,900 2,530 3, % Milpas n/o 101SB OnRamp 15,300 3/ 14, ,310 18, , % Cacique Undercrossing , NA Salinas n/o 101 7, , , , % Cabrillo e/o State St 21,600 2/ 1,052 15, ,550 20,330 1,080 2, % 1:/ AM, Midday and PM Peak hours refer 7-8 AM, 12-1 PM, and 4-5 PM during an average weekday. 2/ 1996 Values from SBCAG 2020 Travel Forecast, September / 1999 values from Milpas/Cabrillo HS project, Feb File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls By 2030, daily traffic on Highway 101 north of the Milpas Interchange is forecast to increase 28%, reaching 125,900 ADT. PM peak traffic is projected to reach 11,830 ADT. Traffic at this level is projected to exceed the estimated freeway capacity 51

52 even with the completion of the auxiliary lane in the northbound and the 3 rd lane southbound on the freeway. Severe congestion is expected. In Montecito, because of significant congestion on Highway 101, traffic on the local parallel roadways such as Ortega Hill Road, North Jameson Lane, and Coast Village Road is forecast to increase substantially. During PM peak, traffic on Ortega Hill Road is forecast to increase from 540 to 1,100 ADT. Traffic on N. Jameson Lane is forecast to increase from 500 to 1,170 ADT. Traffic on Coast Village Road is forecast to increase 66% reaching 1,480 vehicle trips. Because of the significant congestion on Highway 101, traffic on SR192 north of Sycamore Canyon would increase substantially despite its physical and geometric constraints. PM peak traffic in 2030 is forecast to reach approximately 1,000 ADT, a significant increase over existing volume. Since one of the Cabrillo/Hot Springs Operational Improvements is the closing of the Cabrillo/101 southbound on ramp, traffic on Cabrillo Blvd is expected to remain more or less the same as existing volume. The model appears to validate the desire effect of diverting traffic away from using Cabrillo Blvd. City of Santa Barbara Table VI-11 summarizes the 2030 travel forecast for the City of Santa Barbara. The following highlights some of the findings: Table VI-11: 2030 Travel Forecast for the City of Santa Barbara 1/ /2001 Counts 2000 Modeled Vol 2030 Modeled Vol %Chg PMPH Daily Cts AMPHd PMPH Daily AMPHd PMPH Daily AMPH d PMPH Garden 101 Underpass 14, ,182 16,700 1,170 1, % Anacapa s/o Carrillo ,600 1,000 1,040 12,500 1,010 1, % State St. s/o Carrillo , , % Chapala s/o Carrillo , ,610 22,000 1,230 2, % Castillo/101 Underpass ,700 1,750 2,010 28,800 2,140 2, % Mission e/o Castillo ,100 2,300 2,640 31,800 2,480 2, % Anapamu e/o Garden 8, , % Carrillo 101 Underpass ,700 2,930 3,330 44,100 3,390 3, % Haley e/o Chapala , , % Montecito w/o Castillo ,300 2,460 2,740 39,700 3,080 3, % 101 n/o Las Positas 135, ,900 10,200 12, ,900 11,950 14, % 101 n/o Mission 137, ,000 9,780 11, ,300 11,480 13, % 101 n/o Carrillo 126, ,650 8,390 10, ,000 10,320 12, % State n/o Las Positas 30, ,200 2,670 3,160 42,700 3,030 3, % Modoc s/o La Palmas 8,148 6, , , % C. Real n/o Las Positas , ,070 14,960 1,000 1, % 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls By 2030, both AM and PM peak traffic on Highway 101 at major downtown interchanges would experience severe congestion during PM Peak. Traffic increase during PM peak ranges between 23 to 33%. Daily traffic on Highway 101 north of Las Positas is forecast to reach 161,900 ADT, the highest volume for the entire 101 corridor with PM peak reaching 14, 200 vehicle trips. 52

53 Traffic on major N/S arterials within the City is projected to increase between 20 to 30%. Similar traffic increases are projected at major interchanges, such as Garden and Castillo. However, Mission and Carrillo underpasses would experience lesser traffic increases due to their current heavy volumes. Traffic on North State Street would experience significant delays during PM peak. For local arterials such as Modoc south of La Palmas, the increase in evening peak traffic is forecast to increase by approximately 600 trips. Traffic on Calle Real north of Las Positas would experience significant congestion with traffic reaching capacity during evening peak. Goleta Table VI-12 summarizes the 2030 travel forecast for City of Goleta and the nearby unincorporated areas. The following are some of the forecast findings: Table VI-12: 2030 Travel Forecast for Goleta Area /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH Hollister n/o Turnpike 17,274 16,800 1,210 1,570 23,400 1,570 2, % Hollister n/o Patterson 17,978 1,345 1,750 22,200 1,700 2,040 30,900 2,260 2, % Hollister n/o Fairview 20,600 1,254 1,912 20,300 1,382 2,040 26,400 1,850 2, % Hollister s/o Los Carneros 16,800 1,448 22,800 1,510 2,150 31,400 2,130 2, % Hollister s/o Storke 754 1,663 14, ,470 25,100 1,690 2, % Hollister s/o 101 IC 641 1,150 15,400 1,060 1,440 21,300 1,610 1, % C. Oaks s/o ,973 1,148 1,175 9, , , % C. Oaks s/o Fairview 9, , , , % C. Oaks s/o Los Carneros 7, , , % C. Oaks n/o Glen Annie , , , % C. Oaks n/o 101 IC 8, , % Calle Real n/o Patterson , ,030 14, , % Calle Real s/o Los Carneros 7, , , % Calle Real n/o Glen Annie 12,600 1,010 1,010 13,500 1,080 1, % El Colegio s/o Los Carneros 31,200 2,500 2,710 33,500 2,700 2, % Turnpike n/o , ,800 1,220 1,560 21,800 1,580 2, % Turnpike s/o ,072 1,165 1,577 25,300 1,820 2,190 30,230 2,150 2, % Patterson n/o 101 2,368 29,200 2,080 2,510 34,300 2,550 3, % Patterson s/o ,345 1,244 1,086 21,430 1,600 1,810 27,200 2,050 2, % Fairview n/o ,700 2,354 26,800 1,870 2,330 30,700 2,170 2, % Fairview s/o ,171 2,041 26,400 1,890 2,430 33,900 2,490 3, % Los Carneros n/o 101 1,074 1,287 10, , , % Los Carneros s/o ,606 1,503 1,848 30,300 2,360 2,710 39,200 2,768 3, % Storke n/o 101 9,082 27,600 2,000 2,660 35,400 2,200 3, % Storke s/o ,082 1,843 2,576 40,700 3,330 3,510 49,900 3,830 4, % 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls By 2030, traffic on Highway 101 and on most of the arterials would experience significant traffic increases. This appears to be in agreement with the County land use plan for the Goleta area which these assumptions are based on. (The City of Goleta is currently preparing its new General Plan). The Goleta area has 53

54 approximately 80% of the commercial and residential buildout potential on the South Coast. Traffic on Highway 101 at major interchanges would experience severe congestion during the PM peak. These include Turnpike, Patterson, Fairview, and Storke interchanges. Almost without exception, major east/west arterials such as Hollister, Cathedral Oaks, and Calle Real are forecast to increase 30 to 70% from current levels during the PM peak. The entire stretch of Hollister would experience significant congestion during the evening peak. Consistent with the findings on prior 2030 daily forecast report, the PM peak traffic volumes on all N/S arterials would experience similar congestion levels as Hollister Avenue. Average traffic increase at PM peak is between 300 and 600 vehicle trips (or 20 to 40%) over current levels. By 2030, PM Peak traffic on Turnpike is forecast to increase approximately 30% reaching approximately 2,010 trips. Santa Yney Valley Table VI-13 summarizes the 2030 travel forecast for the Santa Ynez Valley. The following highlights some of the forecast findings: Table VI-13: 2030 Travel Forecast for Santa Ynez Valley /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH w/o ,200 1,067 14,300 1,020 1,280 23,300 1,680 2, % 246 e/o Alamo Pintado 17,500 17,510 1,570 24,300 1,810 2, % 246 e/o ,300 2,099 21,000 1,350 1,840 33,900 2,220 2, % 246 e/o Ave of Flags 16,949 2,050 15,100 1,120 1,340 30,300 2,210 2, % 246 w/o Ave of Flags 16,600 15,800 1,160 1,410 31,880 2,320 2, % Refugio n/o SR % Alamo Pintado 549 2, , % Alisal n/o SR , , % 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls Consistent with the 2030 ADT forecast, future PM peak forecasts in the Santa Ynez Valley focuses on Route 246. Most of the traffic increases on this roadway are primarily external and/or inter-city related, with the exception of the traffic generated from the Chumash Casino. Future 2030 traffic is forecast to approach capacity with slow speeds during PM peak. The two areas with the most noticeable traffic increase are the segments west of Route 154 (near the Chumash Casino) and the segments within the City of Buellton. PM peak traffic on 246 west of Route 154 is forecast to reach 2,050 trips. 54

55 Traffic within City of Buellton boundary and areas around Highway 101 interchange are forecast to increase substantially. PM peak traffic on Route 246 within the City Buellton is forecast to double the current volumes. Lompoc and VAFB Areas Table VI-14 summarizes the 2030 travel forecast for the Lompoc and VAFB areas. The following highlights some of the findings: Table VI-14: 2030 Travel Forecast for Lompoc and VAFB Areas /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH SR246 e/o Purisima 11, , % SR246 e/o Rt 1 8,900 10, ,400 1,210 1, % Rt 1 s/o 246 8,700 11, ,110 21,100 1,580 1, % Rt 1 s/o VAFB Main Gate 17,800 1,099 1,383 22,800 1,490 2,040 37,760 2,480 3, % Rt 1 n/o Harris Grade Rd 24,100 1,567 1,742 28,400 2,000 2,540 45,800 3,150 3, % Harris Grade n/o Rt. 1 6,800 6, , , % Rucker Rd n/o Purisima 4, , , % Constellation 8, , , % S. Lucia Cyn n/o Prison 1,600 1, , % Central e/o H St 16,240 1,391 14,400 1,030 1,300 19,400 1,400 1, % Central e/o O St 855 1,145 11, ,010 17,000 1,160 1, % Ocean e/o 7 St 15, ,190 21,100 1,560 1,940 36,300 2,710 3, % Ocean e/o H St 16,000 1,204 14, ,240 23,100 1,630 2, % College w/o H St , , , % H St n/o Ocean 13,000 1,130 12, ,210 22,100 1,450 2, % H St n/o Central 31,000 2,117 33,000 2,310 2,950 51,400 3,550 4, % A St n/o College 1,498 2,272 4, , % V St n/o College 6, , % 7th St s/o North. 4, , % 1:/ AM, Midday and PM Peak hours refer 7-8 AM, 12-1 PM, and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls Date Prepared: PM peak traffic on Route 246 between Buellton and Lompoc is forecast to double the current volume, reaching over 2,220 vehicle trips. Traffic growth on Route 1 between Lompoc and VAFB Main Gate is significant. During the evening peak, an increase of 67% is projected. Traffic on local arterials such as Harris Grades Road and Rucker Road serving the Vandenberg Village, Mission Hills, and the Wye area is forecast to experience significant growth. Within the City of Lompoc, traffic growth on Central Ave is significant. PM peak traffic would reach 1,710 vehicle trips. Traffic on H Street and Ocean Ave would experience 70 to 75% increase during the PM peak. 55

56 Orcutt Table VI-15 summarizes the 2030 travel forecast for the Orcutt area. The following highlights some of the findings: Table VI15: 2030 Travel Forecast for Orcutt Area /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH UVP w/o Bradley 5, ,400 1,320 1, % UVP e/o 135 1,100 2, , % Clark w/o , ,200 1,150 1,450 22,400 1,520 2, % Clark e/o Bradley 17,300 21,800 1,540 1,840 27,700 1,950 2, % Clark e/o ,900 1,482 13,450 1,100 1,220 20,600 1,520 1, % Clark w/o Blosser 5, , % Santa Maria Way 16,800 19,800 1,610 1,710 21,600 1,670 1, % Lakeview e/o 135 9,300 5, , % Foster e/o 135 7,400 6, , % Blosser n/o Clark 1,000 4, , % California n/o Clark 2,500 1, , % Bradley n/o Clark 10,452 1,069 21,300 1,730 1,850 30,200 2,310 2, % Bradley s/o Clark 8, , , % Rice Ranch Rd 2,900 5, , % 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls The completion of UVP will have an impact on local circulation. The peak hour models indicate that UVP would provide an alternate access from Highway 101 to Orcutt and Route 135/Broadway. Some traffic would use UVP to gain access to south Orcutt area. Because of its convenience, the PM peak traffic on UVP is forecast to grow significantly. PM peak traffic would reach approximately 1,290 vehicle trips. Traffic on Clark would continue to increase. PM peak volume is projected to increase between 28 to 38% from the current volumes. Traffic on Bradley would experience congestion during the PM peak. At the segment north of Clark Ave, PM peak traffic is forecast to reach 2,400 vehicle trips. Rich Ranch Road would become an important local arterial providing for access to south Orcutt and the nearby new developments in Orcutt. PM peak traffic is forecast to increase from 480 vehicle trips to 990 trips. Santa Maria Table VI-16 summarizes the 2030 travel forecast for the Santa Maria area. The following highlights some of the findings: With the 6-lane widening on Highway 101, the PM peak traffic is forecast to increase from current 6,000 trips to 9,000 trips. On segments between Betteravia and Donovan, traffic is forecast to be moderately congested. Much of the traffic appears to be inter-county travel mixed with local circulation. 56

57 The substantial traffic increase on Highway 101 during PM peak will likely shift the congestion to north of the Santa Maria Bridge and the SLO County side. PM peak traffic on 135/Broadway is forecast to increase 13 to 25%. The traffic increase on College, Miller, Blosser, and Skyway Drive is also substantial. Table VI-16: Travel Forecast for Santa Maria /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH SLO Co. Line 60,000 58,400 3,170 5,520 95,700 5,200 8, % 101 n/o Main 53,000 57,800 3,350 5, ,300 5,940 8, % 101 n/o Betteravia 54,000 3,126 4,989 65,000 3,950 5, ,000 6,370 8, % 101 n/o Clark 37,200 2,016 2,838 33,000 2,130 3,110 60,400 3,880 5, % 135 n/o Donovan 25,000 1,814 20,700 1,320 1,770 25,600 1,770 2, % 135 s/o Main 26,400 30,400 2,330 2,560 34,000 2,630 2, % 135 s/o Betteravia 34,500 2,559 33,400 1,860 3,050 39,800 2,500 3, % 135 s/o SM Way 34,500 34,500 2,100 3,200 41,900 2,720 3, % Main w/o ,600 13,800 1,010 1,190 17,200 1,260 1, % Main e/o ,700 1,752 19,300 1,350 1,690 29,900 2,020 2, % Main e/o Blosser 17,800 1,179 11, ,000 21,200 1,460 1, % Stowell e/o ,100 1,841 15,000 1,110 1,240 18,200 1,320 1, % Betteravia w/o ,200 31,900 1,940 2,940 37,700 2,410 3, % Betteravia e/o ,800 1,631 24,500 1,440 2,240 27,300 1,660 2, % Betteravia e/o Blosser 14,300 1,341 13, ,200 24,400 1,670 2, % College n/o Main 6, , , , % College n/o Stowell 14, ,600 1,020 1,030 15,800 1,270 1, % Miller s/o Main NA 1,754 10, ,900 1,030 1, % Miller n/o Betteravia 14, ,346 20,500 1,580 1,820 22,900 1,770 2, % Blosser n/o Betteravia 17,100 1,103 1,433 16,300 1,150 1,440 21,800 1,530 1, % SM Way 16,800 19,800 1,610 1,710 21,700 1,690 1, % Bradley n/o Betteravia 11,400 10, ,040 13,400 1,100 1, % Skyway Dr w/o ,700 17,200 1,170 1,430 19,200 1,430 1, % 1:/ AM and PM Peak hours refer 7-8 AM and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl New.xls Date Revised: Guadalupe Table VI-17 summarizes the 2030 travel forecast for the Guadalupe area. The following highlights some of the forecast findings: Table VI-17: 2030 Travel Forecast for Guadalupe /2001 Counts 2000 Modeled Vol 2030 Modeled Vol % PM Chge Daily Cts AMPH d PMPH Daily AMPH d PMPH Daily AMPH d PMPH Rt 166 e/o Simas St 7, , , , % Rt 1 s/o SLO Co. line 4,800 6, , , % Rt 1 s/o 166 1,900 2, , , % Rt.1 n/o 166 (Main St) 6, , , , % Rt 1 s/o 11st St. 4,800 3, , , % 11St. e/o Rt 1 3, , % 1:/ AM and PM Peak hours refer 7-8 AM, 12-1 PM, and 4-5 PM during an average weekday. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls In Guadalupe, the most significant impact in the PM peak is on Route 1 at SLO County line. PM traffic is forecast to 570 to 1,730 vehicle trips. This level of traffic increase could be the result of some traffic diversion from Highway 101 due to the congestion on the SLO County side. However, it is likely that the congestion at the County line could just be during PM peak hour. 57

58 PM peak traffic on Route 166 between Santa Maria and Guadalupe is forecast to increase 59%. Traffic within the City of Guadalupe is expected to experience some levels of congestion due to the substantial increase of traffic on Route 166 from Santa Maria and from Route 1. Heavy PM traffic is also projected on 11th Street and Route 1, the main arterial through the City. 58

59 VII. Transit Ridership Forecast The Transit Mode Choice Model was re-examined in order to develop more reasonable annual ridership forecast by each transit operator. Based on new information, some future route systems and frequency adjustments were made, including the planned SBMTD Santa Ynez Valley Express and Coastal Express expansions to better reflect the ongoing and future transit system expansion within the county. Table VIII-1 summarizes the transit ridership forecast under the daily and annual conditions: Table VII-1: 2030 Transit Ridership Forecast An. Ridership Daily Annual Transit Operator 2000 Cts Total Chge % Chge CAE 125, , , , , % Coastal Express 6, ,023 18, , , % COLT 122, , , , , % Guadalupe Flyer NA 679 1, , , , % SBMTD 7,179,400 23,773 25,388 7,131,900 7,616, , % SMAT 582,300 1,954 4, ,200 1,319, , % SYVT 26, ,200 51,000 25, % InterCommunity Transit NA , ,500 CCAT (SM-SLO) NA 92 27,600 27,600 Total 29,404 37,768 8,221,200 10,721,400 2,500, % NA: Not modeled or not applicable. File:\SBCAG\Fnl Report\Fnl Full Rpt 2030PH SUbArSumTbl xls Clean Air Express (CAE) and Coastal Express ridership are separated out to account for two distinct transit service areas. By 2030, annual CAE ridership is forecast to increase from 129,600 to 369,000. The new Inter-Community Transit between Lompoc, VAFB and Santa Maria is planned in the near future with a 3-year pilot program being considered for completion by 2006/2007. This service is incorporated in the future year model. A total annual ridership of 163,500 is projected. Most recently, SBMTD plans to introduce a new Valley Express service between Santa Ynez Valley and the South Coast. This service will include four morning one-way trips from Santa Ynez to the South Coast and four return trips in the afternoon. This new service is now incorporated as part of the 2030 SBMTD route system. The revised ridership forecast indicates that approximately 7% increase of ridership is projected by 2030 for the entire SBMTD system. The expanding Coastal Express appears to take away some of the SBMTD riders from Carpinteria, Santa Barbara, and Goleta because of more direct and more comfortable service between Carpinteria, Santa Barbara, and Goleta route segments. In general, SBMTD annual ridership is forecast to increase from 7.1 million to 7.6 million, a nominal increase of approximately 7%. Annual ridership for City of Lompoc Transit (COLT) is projected to increase from 125,700 to 372,300 and Santa Maria Area Transit is forecast to increase from 586,000 to approximately 1.3 million by

60 Cuyama Transit is not modeled due to the inter-zonal nature of the route system and negligible ridership. 60

61 VIII. Conclusion This report provides a complete SBCAG travel forecast for Santa Barbara County as a result of the SBCAG Model Replacement and Update effort. The new model predicts quite accurately the existing 2000 base year travel conditions on Santa Barbara County roadways, particularly traffic on the Highway 101 corridor. For example, the severe congestion modeled during existing 2000 PM peak between Turnpike to Padaro Lane reflects this current travel conditions. By 2030, traffic on Highway 101 is forecast to grow approximately 61% at the Ventura County Line. Traffic on the South Coast Highway 101 Corridor is forecast to experience severe congestion between Turnpike and Ventura Co. Line during both AM and PM peak hours in both directions. Significant delay during the PM peak is projected. Similarly, traffic on Highway 101 is forecast to grow 63% at the SLO County Line. Traffic on North County Highway 101 between Clark Ave and SLO County line is forecast to experience moderate travel conditions. During the PM peak hour, congested conditions are forecasted to worsen due to the congestion on Highway 101 projected north of the county line. 61

62 IX. Attachments Appendix I: Model Performance Charts Appendix II: AM Peak Hour Exhibits 62

63 Appendix I: Model Performance Charts AADT Vs. Model Volume Scattergram Volume Volum e AADT 60 Average Trip Lengths Caltrans Survey Vs. Model 50 Trip Length (Minutes) Survey Model 10 0 Home-Based Work Home-Based Shopping Home-Based School Home-Based Other Non Home- Based Work Non Home- Based Other IX-XI Trip Purpose 63

64 Highway 101 Daily Traffic Comparison ( ) 180,000 Highway 101 (Caltrans Control Stations) Daily Traffic Comparison, 2000 & , , , ,000 80,000 60,000 40,000 20,000 0 SLO Co. Line 101 n/o Betteravia 101 s/o Rt n/o Los Carneros 101 n/o Las Positas 101 n/o Salinas 101 n/o Vta Co. Line 2000 Counts 2000 Modeled Vol 2030 Modeled Vol JDr/Win/101NewFlw Dir Flow Comparisons by Screenline Count Vs. Flow Comparison by Screenline WESTMONT WEST 101 VANDENBERG SOUTH GOLETA Screenline SB DOW NTOW N SB AIRPORT SANTA MARIA ORCUTT NORTH GOLETA N SANTA MARIA LOMPOC ARROYO BURRO 0 20,000 40,000 60,000 80, , , , , , ,000 Volume TotalCount TotalFlow 64

65 Maximum Desirable Deviation in Screenline Volumes Deviation in Screenline Volumes Deviation (Percent) ,000 40,000 60,000 80, , , , , , ,000 Screenline Count Volume Deviation Flow Comparisons by Link Classification Volume Flows vs. Count by Functional Class 4,000,000 3,500,000 3,000,000 Volume Flow 2,500,000 2,000,000 1,500,000 1,000, ,000 0 Freew ays Expressw ay s Major Arterials Minor Arterials TotalCount 3,404, ,500 1,454,534 1,610, ,891 64,980 53,832 TotalFlow 3,509, ,770 1,418,817 1,555, ,013 59,233 37,237 Functional Class Urban Collectors Rural Collectors Local Roads TotalCount TotalFlow 65

66 M odel Validation Criteria Assignment Validation Statistics Correlation: R-Squared: 0.93, Standard: 0.88 Flow Comparisons by Link Classification Link Type Segment s Total Count Total Flow % Diff. Standard % RMSE RMSE Standard Freeways 103 3,404,450 3,509, % 6.0% 10.3% 25.0% Expressways , , % 6.0% 14.7% 25.0% Major Arterials 77 1,454,534 1,418, % 10.0% 25.7% 40.0% Minor Arterials 179 1,610,034 1,555, % 10.0% (15% CA) 45.0% 50.0% Urban Collectors , , % 20.0% (25% CA) 46.7% 60.0% Rural Collectors 24 64,980 59, % 20.0% (25% CA) 87.1% 60.0% Local Roads 7 53,832 37, % 65.5% All Roads 440 7,002,221 6,998, % 24.2% 30.0% 66

67 Comparsons of Model Capacity/Speed Relations Speed (mph) Model BPR Capacity Volume (Model Capacity = 1900: LOS E) Delay Time (Minutes Volume-Delay Curves V/C Ratio 0.9 BPR Equation Exponential 67

68 60 Highway BC, PM Peak Hour PM Congested Speeds Vs. V/C Ratios, SB Direction 1.6 Congested Speeds V/C Ratios n/o Las Positas 101 n/o Carrillo 101 n/o Milpas 101 n/o Salinas 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Casitas Pass 2000 Cong. Speeds 2000 V/C Ratio 101 n/o Ventura Co. Line 70 Highway PM Peak Hour PM Congested Speeds Vs. V/C Ratios, SB Direction n/o Las Positas 101 n/o Carrillo 101 n/o Milpas 101 n/o Salinas 101 n/o Olive Mill 101 n/o Sheffield 101 n/o Casitas Pass 101 n/o Ventura Co. Line Congested Speeds V/C Ratios Cong. Speeds 2000 V/C Ratio 68

69 Appendix II AM Peak Hour Exhibits Highway BC, Milpas to Ventura Co. Line AM Peak, Flows & V/C Ratios Highway BC, Santa Barb & Goleta Areas AM Peak, Flows & V/C Ratios 69

70 Highway , Milpas to Ventura Co. Line AM Peak, Flows & V/C Ratios Highway , Santa Barb & Goleta Areas AM Peak, Flows & V/C Ratios 70

71 North County Highway 101, 2000BC AM Peak Traffic by Direction North County Highway 101, 2030 AM Peak Traffic by Direction North County Highway Base Case AM Peak Traffic by Direction Freeway Widened to 3-Lane Each Direction SLO Co. Line 101 n/o Donovan 101 n/o Main 101 n/o Stowell 101 n/o Betteravia 101 n/o SM Way 101 n/o Clark 101 n/o Rt n/o Rt s/o Rt. 1 Northbound Southbound 71