Ohio s Linear Based Referencing System (a.k.a. Location Based Response System LBRS), a True State and Local Government Partnership

Transcription

1 Ohio s Linear Based Referencing System (a.k.a. Location Based Response System LBRS), a True State and Local Government Partnership Ron Cramer Digital Data Technologies, Inc. Joseph Hausman The Ohio Department of Transportation

2 LBRS Concept: Create it once Use it a bunch and maintain it

3 Defining the Problem Create it once Use it a bunch And maintain it

4 Issues at the State DOT Level Every Jurisdiction in the state needs to be on the exact same Linear Referencing System (LRS) using the same Linear Referencing Method (LRM). Integrate a legacy(60+ years) GIS/LRS and create a new system that accurately(+- 1 meter) represents every Public and Private Road in Ohio. Bring mature, effective roadway information standards to this massive road network (125,000 + Centerline Miles) involving all levels of State and Local government. Match Crash data effectively to House Numbers/Addresses, Intersections etc.

5 Standardization of Common Roadway Elements ODOT Road Measurement Conventions When measuring a new road, begin at the centerline of the intersecting road and measure to the end of the new road or to the centerline of the farther intersecting Main road. Cul-de-sacs are measured to their centers unless they have islands, in High Street which case the counter-clockwise distance around the island is measured, also. Street Tie-in points are needed for all roads/streets that intersect main highways. Connector Road Measure from Centerline to Centerline New Road with Dead End Measure from Centerline to End of Road Measure Tie-in Point/Length from Nearest Intersecting Street or some other known reference point. (Record Name/number of the Intersecting Street) Main Intersecting Street New Road with Cul-de-sac Measure to Center of Cul-de-sac Topologically, loop is not completely closed Cul-de-sac with Island Measure to and Around the Island Island

6 Standardization of Ramps and Interchanges including a complete Ramp/Interchange Inventory System (5,000 ramps)

7 Defining Part of the Local Government Problem Point-based addressing ensures jurisdiction s homes, businesses, landmarks and other assets will be accurately located. Most do not have this. Geocoding, a mapping method that approximates address locations based on ranges assigned to a road segment, is unreliable for applications that require accurate locations and it wastes time that could save lives.

8 A Road with Many Names Park Road North Street US40 E. National Road W. National Road Columbia Street E. Main Street

9 To create quality data, some tried to use An orthophoto to create the centerlines Address data from the Assessor and other departments to populate the addresses It became clear that in order to obtain accurate, reliable data, ALL addresses and roads must be field-verified

10 Issues with Local Address Data Analysis of three counties data revealed over 31% of County Assessor s address information is: Incomplete Inaccurate Unreliable databases are often flawed, as well.

11 Field Verification Exposed Non-Matching Address Data Fayette County 4,236 records (37%) did not match 63 % 37% 70% 30% Clark County 30% 16,882 records (30%) did not match City of Gahanna (Franklin County) 4,715 records (31%) did not match 69% 31%

12 Orthophotos prove unreliable for roadway development 37% 25% Road seems passable in orthophoto, but field-verification reveals otherwise

13 It will be difficult to use this road segment for routing purposes 37% 25%

14 Only field-verification would reveal this road segment as impassable

15 A non-existent bridge in Champaign County, Ohio

16 A gated road, blocking travel in Jackson County, Ohio

17 Another dead end road in Champaign County, Ohio

18 An unmarked, unpaved road in Jackson County, Ohio

19 Intelligent Routing Routing Quality Road Network Good routing requirements Good road network data Good routing software Must-haves Proper road names One-way attribute Divided roads have separate lines No intersections at overpasses Speed limits Other traffic related information Nice-to-haves Bridges & culvert locations Traffic signals, stop signs, yield signs Turn arounds School zones Real-time traffic information

20 Routing Example Effect of road network attributes One way Speed Limits

21 Routing Example Effect of road closures

22 Divided Road Tiger ODOT Before LBRS LBRS

23 Standardization of Bi-Directional and Divided Highways

24 CREATE IT ONCE Create it once Use it a bunch And maintain it

25 Create It Once The Solution Location Based Response System (LBRS) State-level plan for every Ohio county Memorandums of Agreement between the Counties and the State Create spatially accurate street centerlines with field verified site-specific address locations, with emphasis on linear referencing/mileposts

26 What is LBRS, cont d. Avoids duplication of efforts Fed, state, county and local levels were creating independent datasets that met their particular needs The challenge for DDTI? Create the initial LBRS pilot project dataset that could meet the unique needs of the DOT with emphasis on linear referencing/milepost, while meeting the needs of county & local GIS, and Emergency Response

27 LBRS Data Input

28 What s so unique? The Next Generation Road Network that supports advanced applications contains these attributes

29 Centerline Address

30 Linking Legacy Data to the LBRS

31 Clark County Deliverables 1, miles of road centerlines 62,152 address locations 45,379 Single family houses 5,015 Duplexes 2,907 Manufactured homes 4,666 Apartments 90 Addressable secondary structures 165 Utility structures (cell/water towers, electric substations, etc.) 3,644 Commercial structures (churches, schools, businesses, etc.) 14 Addresses with no visible structure 272 Apartments (multiple units)

32 Clark deliverables, cont d. 53,899 Address markers 1,333 Alley intersections 525 Bad sign points 199 Jurisdictional Boundary points 2,677 Bridges and culverts 43 Chemical storage 9 Flashing signals and associated control types 30 Gates 480,987 GPS points with attached X, Y, and Z locations 3,554 Fire hydrants 3,216 Landmark points with descriptions 294 Milepost signs and their milepost value

33 Clark deliverables, cont d. 8 CX notes to denote construction 246 MX notes to flag multiple houses sharing a driveway 113 Overpasses 96 Railroad crossings and associated control types 132 School zone points 1,901 Speed limit signs and their value 4,422 Stop signs 455 Traffic signals 173 Turnarounds 106 Underpasses 69 Yield signs

34 ROI: Improving Location Accuracy Each LBRS address point utilizes all three methods for locating an address Situs (house number) Coordinates Milepost/log points/nlfid (LRS Key) Our goal To pinpoint and route distress calls to an exact, field-verified location 100% of the time The LBRS dataset is saving lives

35 ROI: Crash Data Analysis LBRS enables more crash data to be accurately mapped because there are more identifiable locations Prioritizes critical road segment management through collection of various attributes Addresses, landmarks, local roadway network & mileposts Can introduce potential incremental roadway safety funding opportunities and help allocate dollars based on better analysis. Many state DOTs struggle to maintain accurate local roadway inventories Identification of unreported roads Updating of newly created municipal roads DOTs need to locate high hazard locations OFF the state system

36 Crash Study Case Study DOT reported 190 traffic accidents in a county along two major cooridors After comparing crash data with LBRS centerline information, the county was able to locate more than 550 crashes. LBRS road centerline data allowed crashes with incorrect street names or addresses and various other inconsistent reference points to be mapped to the correct, single point Most urban safety studies spend about $2,000 to identify and locate all traffic crashes at a given intersection Cost is associated with trying to find all the crashes based upon multiple location methods (street-intersection, address, route numbermilepost, etc.) When LBRS data is available and used to scrub crash location data, and resolve alternative location methods to a lat-long, the cost to do the same crash study is about $150 cost of intersection analysis reduced by a factor of 10! Leaves more available funds for correcting the problem Also introduces incremental roadway safety funding

37 ODOT Crash Data Analysis Study Intergraph software was used to locate crash locations using two different models Street file from a leading national map data provider Street file DDTI collected for LBRS Street and address file DDTI collected for LBRS 2006 Clark County crash data test set (817 crashes) 709 city or village crashes 108 township crashes Model Used Township City Total National Data Provider 61 of % 450 of % 501 of % LBRS Street 72 of % 675 of % 747 of % LBRS Street & Address 87 of % 687 of % 774 of % Source: Ohio Department of Transportation

38 Why are Private Roads Important?

39 Additional ROI Sales Tax Collection & disbursement of internet sales tax Streamlined Sales Tax Census LUCA Approximately $300 billion in federal grant money distributed to the state & local level Direct tie to annual population estimates Numerous state-level departments Political ROI

40 USE IT A BUNCH (a.k.a. more ROI) Create it once Use it a bunch And maintain it

41 Examples of LBRS Users

42 AccuGlobe Extensions AccuGlobe Dispatch/Mobile/Web

43 AND MAINTAIN IT Create it once Use it a bunch And maintain it

44 Example: Issues With Addressing 80%+ of data has a spatial component (address) Maintenance is the key to upholding quality and accuracy of evolving data sets PROBLEM: While parcels may be maintained by one department at the county-level, multiple addressing authorities are scattered throughout local government Data coordination/consolidation across all agencies is needed

45 Data Maintenance Solution Maintenance software local authorities can use to input new roads & addresses

46 Maintenance Data integration and dissemination COUNTY TOWNSHIP CITY/VILLAGE STATE E9-1-1 Planning Trustees E9-1-1 Engineer Health Zoning Engineer Assessor Other/Etc Other/Etc Other/Etc

47 Centralized GIS data maintenance service CLIENT DDTI

48 Centralized GIS data maintenance service Multiple users can edit the GIS data (spatial and attribute) simultaneously via the Internet Full history of edits are saved with audit trail Computed attributes generated on servers User enters only non-computable data QC checks populate the error layer within seconds after the changes are committed for quick feedback Nightly GIS data extract provides fresh data for GIS applications for other agencies

49 AccuGlobe 2007 GIS Application Provides the user interface to view and edit the GIS data Data layers can come from local sources (orthos, water ways, rail road, special layers for the Client, etc.) or remotely (via SQL Portal, etc.) A redraw of the SQL Portal layer displays the latest committed data on the Servers Edits on SQL Portal layers are sent to the SQL Portal server when the user commits them

50 SQL Portal Server Accepts connection requests, enforces account login Verifies that the user has permission to edit an object Communicates with SQL Server Can connect to different databases

51 SQL Server Stores all data Layer information, objects in GIS data layers, QCError data, permission, user administration, settings for GIS data exports

52 QC Server Performs background computations on recently changed data Detects the changes and runs a series of computations and QC checks involving multiple layers (Roads, Addresses, Address Markers, etc.) and populates the QCError layer when the data violates business rules The parity of the house number of the address is incorrect, The address has no matching road name, The house number of an address does not fit that of the neighboring addresses, The road prefix, type or suffix does not follow the abbreviation rules, etc. Errors in the QCError layer can be resolved by correcting the address or road data, or when it is not possible the user can suppress that particular error for future QC checks

53 Ohio LBRS Status

54 Digital Data Technologies, Inc. Ron Cramer Joe Hausman