Using GPS Based Origin-Destination Data to Improve Traffic Studies. Michael R. Wahlstedt, PE, PTOE OTEC October 11, 2017

Transcription

1 Using GPS Based Origin-Destination Data to Improve Traffic Studies Michael R. Wahlstedt, PE, PTOE OTEC October 11, 2017

2 Overview Benefits of using O-D data for traffic analysis, particularly for operational modeling Example applications Using O-D data in VISSIM 2

3 Benefits of O-D Data Traffic count data, particularly turn volumes provide some indications of travel patterns, but don t provide a clear picture when: There are multiple travel routes In weave areas Over longer corridors

4 Benefits of O-D Data Multiple travel routes O-D data with middle filters can identify route choice.

5 Benefits of O-D Data Weave areas O-D data will provide more realistic assignment of routing through weave areas.

6 Benefits of O-D Data Long corridors Provides more accurate trip lengths Provides weave patterns

7 Data Sources

8 O-D Data Sources Visual Observation (weave areas) License Plate Surveys Cellular Based Data (e.g. Airsage) GPS Based Data (e.g. StreetLight, INRIX)

9 O-D Data Sources Visual Observation Needs line of sight High accuracy Low cost

10 O-D Data Sources License Plate Survey Can be automated (ALPR) High accuracy High cost

11 O-D Data Sources ALPR Example: US 54/I-35/K-96 New access at I stations/48 cameras Captured 70%+ of traffic 7:15-8:15 AM 1-I35 s/o Ex50 3-I35 n/o Ex53 4-K96 n/o Ex 53 5-US54 e/o K96 10-KTA e/o 127th 11-Webb n/o US54 12-Webb s/o US US54 w/o Ex50 17-Gwich n/o US54 18-Gwich s/o US54 1-I35 s/o Ex I35 n/o Ex K96 n/o Ex US54 e/o K KTA e/o 127th Webb n/o US Webb s/o US US54 w/o Ex Gwich n/o US Gwich s/o US :15-8:15 AM 1-I35 s/o Ex50 3-I35 n/o Ex53 4-K96 n/o Ex 53 5-US54 e/o K96 10-KTA e/o 127th 11-Webb n/o US54 12-Webb s/o US US54 w/o Ex50 17-Gwich n/o US54 18-Gwich s/o US54 1-I35 s/o Ex I35 n/o Ex K96 n/o Ex US54 e/o K KTA e/o 127th Webb n/o US Webb s/o US US54 w/o Ex Gwich n/o US54 18-Gwich s/o US54

12 O-D Data Sources Cellular Based Data (e.g. AirSage) Uses triangulation of cell phone pings at towers More phones, but less spatial accuracy (need larger zones) Harder to delineate short duration trip ends More suited for zone based analysis (vs. corridor), e.g. subarea model Moderate cost

13 O-D Data Sources Randall Road Corridor Created sub-area model to generate specific routing (high effort) Sub-area model was then also used for forecasting future traffic VISSIM routing generated using sub-area model

14 O-D Data Sources GPS Based Data (e.g. StreetLight, INRIX) High-resolution tracking of vehicles (lock to roadways) Once per second sampling for certain data sets Ideal for corridor based analysis Separate commercial and personal vehicle data sets Potential for sample bias (participating truck fleets, cars with GPS tracking) Moderate cost

15 O-D Data Sources Example: Industrial Facility Change in access location to site LADOT requires specific truck routes on city streets Many possible routes from freeways to site Site Proposed Access

16 O-D Data Sources Example: Industrial Facility StreetLight Data provides both personal and commercial trip data Regional Patterns Local Patterns Redistributed trips to new site entrance Site

17 O-D Data Sources Example: Tri-State Tollway Study of 22 mile I-294 corridor VISSIM model Count data at all interchanges, but no trip length or weave data Using tflowfuzzy alone to generate matrix may result in inaccurate weaving patterns and too many short trips Regional model not satisfactory for this level of detail

18 O-D Data Sources Example: Tri-State Tollway StreetLight Data 65 Pass-Thru zones created at perimeter of study corridor Sketch network created in VISUM to generate routing (more on this later!)

19 O-D Data Sources Example: Cambridge Connector Traffic projections and VISSIM modeling New interstate connection to alleviate arterial congestion Will new connection draw sufficient traffic to reduce congested intersection and justify cost? KU Medical Center Downtown Kansas City

20 O-D Data Sources Example: Cambridge Connector Identify regional patterns More traffic from Kansas Little traffic from outside metro area A lot of traffic from due south (may not use I-35)

21 O-D Data Sources Example: Cambridge Connector Study Area O-D Data Daily Trip Destinations This analysis includes internal and external trips, including pass-thru Data set also includes peak periods KU Medical Center

22 O-D Data Sources Example: Cambridge Connector Filter zones for select link trips 7 th Street & I-35 NB off-ramp KU Medical Center

23 O-D Data Sources Example: Cambridge Connector Filter zones for select link trips SW Trafficway & I-35 NB off-ramp KU Medical Center

24 O-D Data Sources Example: Cambridge Connector Develop sketch model in VISUM Reassign trips to new route Generate O-D matrix for VISSIM

25 VISSIM Application

26 VISSIM Application Modeling process: Merge O-D data and count data in sketch VISUM model Generate matrix for use in VISSIM routing Import routing into VISSIM

27 VISSIM Application VISUM: Create stick network Generally for linear corridors only one route option between zone pairs VISSIM will assign to shortest route Don t need link and node attributes Just create permitted tsys for links and turns

28 VISSIM Application VISUM: Use Matrix Projection to adjust StreetLight O-D data to match counted volumes at externals Review matrix for illegitimate route pairs and set to 0 (can use skim matrix) StreetLight Data Matrix Counted Volumes

29 VISSIM Application VISUM: Enter counted volumes for intersections and links UDAs are useful for this Generate +/- tolerances for count data Use another UDA or AddVal fields

30 VISSIM Application VISUM: Create procedure sequence Assignment Matrix Correction - tflow Fuzzy Check/Iterate Cycle through Iterations until desirable tolerances are met Often requires some cleanup of counts and network

31 VISSIM Application VISSIM: Create network that mirrors VISUM structure (or vice versa) Pair VISSIM link numbers of external links with VISUM zone numbers For smaller networks, you can manually create routes and use volumes from balanced matrix For DTA models, stop here and pair with VISSIM matrix

32 VISSIM Application VISSIM: For large networks, create a pairing table of VISUM zones and VISSIM external links (in and out). Utilize an excel macro to generate route paths to paste into VISSIM inpx file. Just need start and end links in VISSIM route, when you run the VISSIM model, the routing will be auto generated based on the shortest route. You can then edit routes as needed.

33 VISSIM Application VISSIM: Execute model!

34 Questions? Michael R. Wahlstedt, PE, PTOE