Using GPS Based Origin-Destination Data to Improve Traffic Studies Michael R. Wahlstedt, PE, PTOE OTEC October 11, 2017
Overview Benefits of using O-D data for traffic analysis, particularly for operational modeling Example applications Using O-D data in VISSIM 2
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
Benefits of O-D Data Multiple travel routes O-D data with middle filters can identify route choice.
Benefits of O-D Data Weave areas O-D data will provide more realistic assignment of routing through weave areas.
Benefits of O-D Data Long corridors Provides more accurate trip lengths Provides weave patterns
Data Sources
O-D Data Sources Visual Observation (weave areas) License Plate Surveys Cellular Based Data (e.g. Airsage) GPS Based Data (e.g. StreetLight, INRIX)
O-D Data Sources Visual Observation Needs line of sight High accuracy Low cost
O-D Data Sources License Plate Survey Can be automated (ALPR) High accuracy High cost
O-D Data Sources ALPR Example: US 54/I-35/K-96 New access at I-35 12 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 54 14-US54 w/o Ex50 17-Gwich n/o US54 18-Gwich s/o US54 1-I35 s/o Ex50 197 163 42 55 60 21 50 17 2 3-I35 n/o Ex53 232 59 2 37 1 10 253 4-K96 n/o Ex 53 31 41 2 163 31 4 64 9 47 5-US54 e/o K96 107 14 768 5 111 8 740 70 17 10-KTA e/o 127th 122 19 86 10 67 11-Webb n/o US54 42 5 23 185 349 42 12-Webb s/o US 54 23 16 26 11 699 284 15 2 14-US54 w/o Ex50 19 161 159 310 7 349 164 184 53 17-Gwich n/o US54 9 3 7 2 197 164 18-Gwich s/o US54 3 39 8 38 1 171 476 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 54 14-US54 w/o Ex50 17-Gwich n/o US54 18-Gwich s/o US54 1-I35 s/o Ex50 197 163 38 41 3-I35 n/o Ex53 232 1 10 253 4-K96 n/o Ex 53 31 8 5-US54 e/o K96 102 1 10-KTA e/o 127th 113 62 11-Webb n/o US54 5 12-Webb s/o US 54 16 14-US54 w/o Ex50 161 3 3 17-Gwich n/o US54 18-Gwich s/o US54
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
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
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
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
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
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
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!)
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
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)
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
O-D Data Sources Example: Cambridge Connector Filter zones for select link trips 7 th Street & I-35 NB off-ramp KU Medical Center
O-D Data Sources Example: Cambridge Connector Filter zones for select link trips SW Trafficway & I-35 NB off-ramp KU Medical Center
O-D Data Sources Example: Cambridge Connector Develop sketch model in VISUM Reassign trips to new route Generate O-D matrix for VISSIM
VISSIM Application
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
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
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
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
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
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
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.
VISSIM Application VISSIM: Execute model!
Questions? Michael R. Wahlstedt, PE, PTOE mrwahlstedt@transystems.com