Use of Crash Report Data for Safety Engineering in Small- and Mediumsized

Similar documents
Geospatial Big Data Analytics for Road Network Safety Management

ENHANCING ROAD SAFETY MANAGEMENT WITH GIS MAPPING AND GEOSPATIAL DATABASE

PROBLEMS AND SOLUTIONS IN LOGGING OF TRAFFIC ACCIDENTS LOCATION DATA

Local Calibration Factors for Implementing the Highway Safety Manual in Maine

NJDOT Pedestrian Safety Analysis Tool 2015 GIS T Conference

DEVELOPING DECISION SUPPORT TOOLS FOR THE IMPLEMENTATION OF BICYCLE AND PEDESTRIAN SAFETY STRATEGIES

MODELING OF 85 TH PERCENTILE SPEED FOR RURAL HIGHWAYS FOR ENHANCED TRAFFIC SAFETY ANNUAL REPORT FOR FY 2009 (ODOT SPR ITEM No.

Modeling of Accidents Using Safety Performance Functions

THE DEVELOPMENT OF ROAD ACCIDENT DATABASE MANAGEMENT SYSTEM FOR ROAD SAFETY ANALYSES AND IMPROVEMENT

Using GIS to Identify Pedestrian- Vehicle Crash Hot Spots and Unsafe Bus Stops

Texas A&M University

How GIS Can Help With Tribal Safety Planning

Abstract: Traffic accident data is an important decision-making tool for city governments responsible for

HSIP FUNDING APPLICATION

US 20 Highway Safety Study

Statistical and GIS Modeling of Crashes on Utah Highways. Eric Scott Johnson

MARITIME TRANSPORTATION RESEARCH AND EDUCATION CENTER TIER 1 UNIVERSITY TRANSPORTATION CENTER U.S. DEPARTMENT OF TRANSPORTATION

Updating the Urban Boundary and Functional Classification of New Jersey Roadways using 2010 Census data

I-95/I-85 INTERCHANGE ROADWAY SAFETY ASSESSMENT

Office of Enterprise Technology

INDOT Office of Traffic Safety

Unobserved Heterogeneity and the Statistical Analysis of Highway Accident Data. Fred Mannering University of South Florida

Using Public Information and Graphics Software in Graduate Highway Safety Research at Worcester Polytechnic Institute

Statewide State Roads Layer Michigan Geographic Framework Field Definitions

Planning Level Regression Models for Crash Prediction on Interchange and Non-Interchange Segments of Urban Freeways

Reliability and Safety Prediction for Planning

Visualization of Origin- Destination Commuter Flow Using CTPP Data and ArcGIS

Multiple Changepoint Detection on speed profile in work zones using SHRP 2 Naturalistic Driving Study Data

Transforming the Maricopa County Department of Transportation (MCDOT) GIS-based Transportation Asset Inventory System June 30, 2016

Table of Contents Introduction... 4 Study Area... 5

Safety Performance Functions for Partial Cloverleaf On-Ramp Loops for Michigan

City of Phoenix Pavement Management System. Ryan Stevens Civil Engineer III Street Transportation Department November 15, 2017

Market Street PDP. Nassau County, Florida. Transportation Impact Analysis. VHB/Vanasse Hangen Brustlin, Inc. Nassau County Growth Management

EVALUATION OF SAFETY PERFORMANCES ON FREEWAY DIVERGE AREA AND FREEWAY EXIT RAMPS. Transportation Seminar February 16 th, 2009

IDAHO TRANSPORTATION DEPARTMENT

Maricopa County Department of Transportation (MCDOT) GIS Innovations in Transportation Asset Management

NORTH HOUSTON HIGHWAY IMPROVEMENT PROJECT (NHHIP)

Appendixx C Travel Demand Model Development and Forecasting Lubbock Outer Route Study June 2014

2015 Grand Forks East Grand Forks TDM

A Study of Red Light Cameras in Kansas City, MO

GIS ANALYSIS METHODOLOGY

HSIP FUNDING APPLICATION

Snow and Ice Control POLICY NO. P-01/2015. CITY OF AIRDRIE Snow and Ice Control Policy

Xiaoguang Wang, Assistant Professor, Department of Geography, Central Michigan University Chao Liu,

FDOT Level 2 Roundabout b/c Evaluation

Accident Prediction Models for Freeways

High Friction Surface Treatment on Bridge Safety

United Kingdom (UK) Road Safety Development. Fatalities

VIRGINIA S I-77 VARIABLE SPEED LIMIT SYSTEM FOR LOW VISIBILITY CONDITIONS

DEVELOPMENT OF TRAFFIC ACCIDENT ANALYSIS SYSTEM USING GIS

DEVELOPMENT OF A VISUALIZATION SYSTEM FOR SafetyAnalyst

VDOT STARS Program Terrell Hughes, PE Conceptual Planning Manager. Richmond Regional Transportation Planning Organization November 2, 2017

FHWA Planning Data Resources: Census Data Planning Products (CTPP) HEPGIS Interactive Mapping Portal

Implication of GIS Technology in Accident Research in Bangladesh

NORTH HOUSTON HIGHWAY IMPROVEMENT PROJECT (NHHIP)

CITY OF NEW LONDON WINTER ROAD & SIDEWALK MAINTENANCE POLICY

Measuring and GIS Referencing of Network Level Pavement Deterioration in Post-Katrina Louisiana March 19, 2008

WEBER ROAD RESIDENTIAL DEVELOPMENT Single Family Residential Project

TRB Paper Hot Spot Identification by Modeling Single-Vehicle and Multi-Vehicle Crashes Separately

New Achievement in the Prediction of Highway Accidents

Uses of Travel Demand Models Beyond the MTP. Janie Temple Transportation Planning and Programming Division

GeoTAIS: An Application of Spatial Analysis for Traffic Safety Improvements on Provincial Highways in Saskatchewan

FHWA/IN/JTRP-2008/1. Final Report. Jon D. Fricker Maria Martchouk

2011 South Western Region Travel Time Monitoring Program Congestion Management Process. Executive Summary

DEVELOPMENT OF CRASH PREDICTION MODEL USING MULTIPLE REGRESSION ANALYSIS Harshit Gupta 1, Dr. Siddhartha Rokade 2 1

Enterprise Linear Referencing at the NYS Department of Transportation

AN ARTIFICIAL NEURAL NETWORK MODEL FOR ROAD ACCIDENT PREDICTION: A CASE STUDY OF KHULNA METROPOLITAN CITY

Advancing Transportation Performance Management and Metrics with Census Data

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8

Cipra D. Revised Submittal 1

DEVELOPMENT OF A VISUALIZATION SYSTEM FOR Safety Analyst

Spatial Variation in Local Road Pedestrian and Bicycle Crashes

TO THE REPORT: A STRATEGIC PLAN TO REDUCE VEHICLE- ANIMAL ACCIDENTS IN NORTHEAST OHIO

JCRD501: RURAL COUNTY ROADWAY SPECIFICATIONS

Comparison of spatial methods for measuring road accident hotspots : a case study of London

KEEPING DATA ACCURATE WITH THOSE WHO KNOW BEST. Adam Breznicky, GIS Analyst; TPP

EXAMINATION OF THE SAFETY IMPACTS OF VARYING FOG DENSITIES: A CASE STUDY OF I-77 IN VIRGINIA

POLICY MANUAL. Hamlets/Residential named hamlets within the County of Grande Prairie whose roads are hard surfaced.

SPEED LIMIT STUDY ELDRON BLVD NE & SE FROM AMERICANA BLVD NE TO BAYSIDE LAKES BLVD. Engineering and Traffic Investigation Conducted by:

Traffic Demand Forecast

Predicting Animal-Vehicle Collisions for Mitigation in Texas

Transport Data Analysis and Modeling Methodologies

Data Driven Approaches to Crime and Traffic Safety

Traffic accidents and the road network in SAS/GIS

Spatiotemporal Analysis of Urban Traffic Accidents: A Case Study of Tehran City, Iran

SECONDARY ROADS LEVERAGING ENTERPRISE GIS. Secondary Road Department & GIS Department Linn County, Iowa April 20, 2015

Using GIS to Determine Goodness of Fit for Functional Classification. Eric Foster NWMSU MoDOT

Using a K-Means Clustering Algorithm to Examine Patterns of Pedestrian Involved Crashes in Honolulu, Hawaii

Maryland Transit Administration (MTA) Bus Accident Mapping and Analysis Application

Extreme Weather and Climate Change Vulnerability Assessment of Central Texas Transportation Infrastructure

Understanding Land Use and Walk Behavior in Utah

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures

FALL TEXITE MEETING. ITS and Weather Events. Date. Date. Footer Text. Photo by Liam Frederick

Linear Referencing Systems (LRS) Support for Municipal Asset Management Systems

A COMPARATIVE STUDY OF THE APPLICATION OF THE STANDARD KERNEL DENSITY ESTIMATION AND NETWORK KERNEL DENSITY ESTIMATION IN CRASH HOTSPOT IDENTIFICATION

A FIELD EXPERIMENT ON THE ACCURACY OF VISUAL ASSESSMENT OF WINTER ROAD CONDITIONS

Brandywine Road Speed Study FINAL REPORT

Evaluation of fog-detection and advisory-speed system

Evaluation of NDDOT Fixed Automated Spray Technology (FAST) Systems November 24, 2009

Math 2331 Linear Algebra

Transcription:

Use of Crash Report Data for Safety Engineering in Small- and Mediumsized MPOs 2015 AMPO Annual Conference Sina Kahrobaei, Transportation Planner Doray Hill, Jr., Director October 21, 2015

San Angelo MPO, TX Located in Midwest Texas 116 sq. miles City of San Angelo is the major city 85% of SA MPO population reside in the City of SA Area-wise, City of SA is half of SA MPO 2

City of San Angelo, TX Pop : 93,000 Area: 58 sq. mi Pop : 97,000 Area: 26 sq. mi Pop : 112,000 Area: 18 sq. mi Pop : 105,000 Area: 8 sq. mi 3

Previous Data Analysis Received data from PD Sort/Filter o o XY Coordinates Street Narrowed top 10 Contributed factors Manually graph Geocode o Areas with high w/ concentration 4

Previous Data Analysis cont d 5

Analysis Shortfalls Inaccuracies Officer data collection method XY coordinates/address incorrect Tedious and Time consuming Location (Area) focused not detailed Frequency only, no severity Countermeasures never considered 6

Crash Data Sources for MPOs Local sources (San Angelo Police Dep.) vs. statewide sources (TxDOT CRIS database) o Crash Records Information Systems (CRIS) From PD From CRIS 7

Crash Data Analytics 1. Predictive (what could happen?) o Using Safety Performance Functions (SPF) 2. Descriptive (what has happened?) o Using historical crash data by severity and location Crashes are random events that naturally fluctuate over time at any given site: aka. Regress to Mean bias 8

Descriptive Crash Analysis Network Screening Diagnosis and Countermeasure Selection Spot-location approach Systematic approach Comprehensive approach Economic Appraisal and Priority Ranking (costbenefit) Countermeasure Evaluation (some time after implementation) 9

Crash Analysis Software Packages Predictive software packages: o TRB s CRP-CD-78 (PLANSAFE) o ASHTO s Safety Analyst ($17,000) Descriptive software packages: o Pd Programming s Crash Magic Online (estimated at $23,000 for a 5-year license for an MPO with 100,000 of population) 10

Network Screening Network elements: Road Segment Intersection (at-level) Interchange (gradeseparated) Functional classification (principal arterial, minor arterial, major collector, local) # of total lanes # of legs (3, 4, or 5) Control type (signalized or unsignalized) Division between segment and intersection accidents: 11

Crash frequency and Severity: o R = C N Where: R_ Annual Average Intersection Accident Rate C_ Accident counts in the study period (2010-2014) N_ Number of years od study (5 years) 76.8 K+A crashes +8.4 B+C crashes +1.0(O+U crashes) o SI= Total crashes Numbers of years of study Where: SI_ Crash Severity Index K_ Fatal A_ Disabling B_ Evident Injury C_ Possible Injury O_ No Injury U_ Unknown Speed (mph) Intersection functional distance (ft.) 10 120 15 120 20 150 25 190 30 240 35 290 40 355 45 415 50 490 55 565 60 650 65 735 70 840 12

Crash Frequency 13

Crash Severity 14

Pinpointing the Accident Location ST_NAME_IN..Collision has happened here AT_INTERSE..At intersection (reference point) FEETFROM..Feet from the ref. point DISTANCE_F..Direction from the ref. point 15

Diagnosis & Countermeasure Selection Bryant Blvd. @ Houston Harte Expwy. Location # More freq. found contributing factor(s) 1 Fail to yield ROW turning left 2 Fail to yield ROW turning left Fail to control speed 4 Fail to control speed Unsafe lane change 5 Fail to control speed Proposals Employ 4-phase signal operation Improve pavement markings Improve left-turn channelization Improve pavement markings Improve access management Install delineators Improve pavement markings Improve pavement markings 16

Diagnosis & Countermeasure Selection Knickerbocker Rd. @ Loop 306 Location # More freq. found contributing factor(s) 1 Fail to control speed Unsafe lane change 2 Fail to control speed Proposals Install raised median Install delineators No turn on red for Knickerbocker SBR Employ 4-phase signal operation 17

Limitations: Conclusion o Discrepancy between local and state crash data sources o Inconsistency in completing the crash report on site among the officers o Unreliability in x-y coordinates of the accident datapoints Advantages: o Cost-effectiveness for small and medium-sized MPOs 18

Sina Kahrobaei, Transportation Planner Doray Hill, Jr., Director sina@sanangelompo.org doray@sanangelomop.org www.sanangelompo.org (325) 481-2800