May 2024 Meeting

Bill Hereth · May 9, 2024

Meetings

Date/Time: Thursday May 9th, 2024 10:00-11:30am
Location: WFRC Offices - 41 N Rio Grande St, Salt Lake City, UT 84101

Agenda

Welcome & Introductions

  • Anyone attending for the first time?
  • User Spotlights

Discussion Topics

  • Model status update
  • Git Training
    • Find a time: Schedule on Doodle
    • Location: UDOT Complex (Room TBD)
    • Summary: Greg Macfarlane (BYU professor) will provide an introduction to software version control for transportation analysts. This training is aimed at those who have heard of Git, but have never used it, or who have used it but didn’t really know what they were doing.
  • TDM Resources https://utahmug.org/resources/ (Chris)
  • Study TAZ Splits for Model Improvement (Natalia)

Presentations

  • Representing Capacity Constraints on Park and Ride Facilities
    David Ory – Vice President, WSP
    Summary: For many transit systems or services, parking capacity at park and ride facilities constraints and/or influences ridership. In this presentation, David will discuss three approaches in travel modeling to represent capacity constraints at park and ride facilities.

  • Half Time Break: UtahMUG Training Topics Ranking - Live Poll
    Bill Hereth - WFRC

  • Historic AADT and Traffic Counts on Utah’s Highways
    Nicolas Black – Traffic Data Analytics Manager, UDOT
    Summary: Agencies across the state use the AADT published by UDOT to validate their models. In this presentation, Nicolas will provide an overview of the process to create the AADT and a list of resources to obtain traffic data that could assist with modeling efforts.

Next meeting

  • Date/Time: Thursday, September 12th 10:00-11:30 am @ MAG

Suggestion Box

  • Please enter any suggestions here.

🍽 lunchiMUG



Notes

Welcome & Introductions

  • Keith Hanglin – New Member
  • Dave Ory – Visiting
  • Hayden Atchley – New Member
  • Nicholas Black – Visiting
  • Jared Lillywhite – New Member
  • Nimish Dharmadhkari – New Member

Model Status Update

  • USTM: current version is 3.0, updated a few months ago
  • Wasatch Front: current version is v901, v902 to be released next month, v910 to be released late summer
  • Cache: working on refinements, trying to integrate more count data
  • Dixie: no big updates, current version is 9.0
  • Summit Wasatch, no big updates

Representing Capacity Constraints on Park and Ride Facilities David Ory

  • Transit is often constrained by capacity of park n ride lots – the tdm must be able to understand the capacity constraints
  • Solution 1: shadow pricing in mode choice
    • Step 1: Create dummy TAZs at each of the park and ride stations
      • connect them to the roadway network; then build transit skims
    • Step 2: Modify mode choice structure to include lot options under PNR mode
      • make sure to pay attention to period and purposes
    • Step 3: Run Mode Choice Iteratively
      • calculate cumulative number of users at each lot, sum demand at each PNR lot, if over capacity it goes to the next step and if not calculate a shadow price
    • Pros: straightforward and allows changes in mode/route; credibility
    • Cons: computationally inefficient, relies on heuristics; doesn’t allow fill-up time analysis
  • Solution 2: Simulation with Re-planning
    • Step 1: For each OD pair, identify PNR stations
      • Can use dummy zones and the highways skims for closest ones
    • Step 2: Run MC using first best PNR station
    • Step 3: Estimate departure time for each PNR trip
      • For trip based, make a list of the trips and estimate departure time
    • Step 4: assign each trip to a PNR lot
      • Once lot capacity fills up, the excess people “fail”
    • Step 5: replan “failed” trips
      • Re-run MC or do something to reassign mode to “failed” trips
    • Pros: allows for MC/assign route; provides time; computationally efficient
    • Cons: lots of heuristics; tedious to implement
  • Solution 3: Network Based
    • Usually commercial software has some sort of PNR logic that can be used
    • EMME Solution:
      • Fix is done in hwy assignment
      • Create PNR node, create link to connect node to hwy network, create dummy bus line from PNR station to rail station
      • Enforces capacity because if there are no spots available, the travel time goes up, and chooses another mode
    • Pros: high-fidelity representation of lot characteristics; computationally efficient; no heuristics
    • Cons: Doesn’t answer “when lot fills up”; a bit of a hack

Historic AADT and Traffic Counts on Utah’s Highways Nicolas Black

  • Report monthly and annual data to FHWA
    • Monthly CCS data due monthly (hourly volume, speed, axle, length, and weight data)
    • AADT’s & statistics due annually (single unit & combination unit, K&D factors, SU/CU peak percentages, VMT summaries)
  • Sources of Traffic Data
    • Continuous Count Station (CCS) program – radar devices with wavetronics (volume, speed, length, & weight)
    • Short Term Count Program (STC or Portable Counts) – portable short duration counts
  • How is AADT generated each year?
    • Phase 1 – annual summarization of CCS data
    • Phase 2 – factor group evaluation and factor calculation
    • Phase 3 – short term counts
    • Phase 4 – site statistic review
      • If you see a big jump one year , thats probably not because it jumped up that year but that over the past years the data was higher and now theres enough data to prove the increase
    • Phase 5 – local statistics
    • Phase 6 – HPMS statistics
  • Question: can we have the raw AADT in order to help with TDM model calibration/validation? – Tim Baird
    • “Possibly. We can try to put it up in a queryable database for users to grab that information”
  • Question: can we have the AADT that hasn’t been annualized – to allow for seasonal counts – Chris Hall
    • “Not sure. We can have a discussion later. We want to create a dashboard with all the info.”
  • Question: The data exists then, it just isn’t easy to munge – Greg Macfarlane
    • “Correct. We hope to make it more accessible as well as try to build on it for the users”
  • New and Future Data Sets
    • Restoring Weigh in Motion program
    • ATSPM data set
    • Local Agencies