Update on Developing Evacuation Model using Dynamic Traffic Assignment

1. Update on Developing Evacuation Model using Dynamic Traffic Assignment ChiPing Lam, Houston-Galveston Area Council Matthew Martimo, Citilabs

2. Review last Presentation • During Rita Evacuation, evacuation routes were very congested. “Crawling parking lot.” • H-GAC was asked to develop a tool for evacuation planning.

3. Challenges • Large network and demands • Long trip length and travel time • Interaction between evacuation and non-evacuation traffic • Network changes during evacuation period (eg: contraflow, HOV and toll open to public)

4. Goal of this model • Re-generate the Rita evacuations • Provide evacuation demands • Estimate traffic volumes and delays • Sensitive to various scenarios and plans • Apply to non-evacuation planning (corridor, sub-area, ITS, etc)

5. H-GAC’s Expectation • Validation • Normal Day Traffic • Rita • Year 2010 Scenario • Able to adjust evacuation trip tables for different situations • Sensitive to policy factors • Allow road changes within evacuation

6. Review – Why DTA? • Why NOT use traditional (Static) assignment? • No impact of queues • No ability to deal with upstream impacts • Links do not directly affect each other • Not conducive to time-series analysis • Why NOT use traffic micro-simulation? • Study area of interest too large and complex • Too much data and memory required • Too many uncertainties to model accurately

7. Cube Avenue Technical Facts • Unit of travel is the “packet” • Represents some number of vehicles traveling from same Origin to same Destination • Link travel time/speed is a function of • Link capacity • Queue storage capacity • Whether downstream links “block back” their queues • Link volumes are counted in the time period when a packet leaves the link

8. Progress on Last Presentation • Based on TXDOT survey, develop trip generation model • Using a simplified and relax gravity model to assign evacuation demands • Develop hourly factors for evacuation traffic and normal traffic reduction

9. Progress on Last Presentation(2) • Ramp Storage Adjusted to account for storage lane and through lane on freeway, to avoid over-estimate backup • Network simplification to save memory • Single class assignment • 72 1-hour assignment to account for network changes

10. Computer Limitations 32 bit computing (Windows XP) limits how much computer memory can be accessed by a single process to 2GB. Initially the problem size was requiring more than 2GB of memory and was failing altogether. Previous suggestion: Simplified Network to reduce memory requirement

11. Overview for this presentation • Problem Size • Greater Houston-Galveston Metropolitan Area • 72 hour simulation of evacuating vehicles • Initially strained the available computing resources • Mesoscopic modeling versus standard Macroscopic Travel Demand Modeling

12. Simplified Network Abandon Only Major arterials, highways, and freeways remained in the simplified network. In retrospect, this was a VERY bad idea… because of the nature of Mesoscopic Simulation… This will be described in a few minutes. In fact, the more detail available in the network, the better. We are now modeling with the full travel demand modeling network.

13. Multi-Class Assignment • Single class assignment remove some of the ability of the model to properly replicate flows seen on the roadways • Making calibration more difficult. • Now model multi-class assignment similar to the static model, each with their own path sets. • Drive alone free (No HOV, Toll, HOT) • Drive alone pay (No Toll) • 2 person free (No Toll, HOT) • 3+ person free (No Toll) • Share ride pay (allow everything)

14. Increase Number of Iterations Originally zero to 1 iteration (similar to AON assignment) Vehicles jam to the AON route, cause extremely long travel time and consume more computer memory Ill-conceived as with each subsequent iteration, the vehicles learn more about possible routes and their environment. With each subsequent iteration, the model is more stable, reliable, and easier to calibrate.

15. Number of Iteration vs Travel time for Single hour assignment

16. Packets Network are simulated in packets. A group of trips with same origin, destination, and start time. Treated as if a single unit Each packet can hold any number of trips. Tracking and simulating these individual packets is what consumes the memory. 2GB can simulate more than Six Million packets at anyone time.

17. Limit the Size of Packets • Originally, the maximum size of packet is ten vehicles or less • Large size is to reduce number of packets; to consume less memory • With software upgrade and increase iteration, now is one vehicle trip per packet • Reduce number of non-integer trips

18. Non-integer Trips • 10 million trips • Due to non-integer trips, the number of packets ends up being MUCH larger. Example: Drive Alone Free Trip Table

19. Reduce Number of Non-Integer Trips (1) • Alternative 1: traditional bucket rounding for each hourly demand • Add fraction trips across column, and assign a trip when the sum of fraction equals to or exceeds 1 • Does not reserve column (destination) total, which is bad as evacuation traffic is concentrated on a few external destinations

20. Reduce Number of Non-Integer Trips (2) • Alternative 2: Cross-time bucket rounding • Summing across time rather than column, hence preserve origin-destination total • Too little traffic on early hours because for many origin-destination, sum of early hour trips is less than 1 (no packet assigned)

21. Probabilistic Integerization (1) • For each origin-destination pair, produce probability distribution based on hourly demands • Simulate integer trip based on probability • Sum of Daily Trips for each origin-destination reserves, and early-hours are assigned with adequate traffic

22. Probabilistic Integerization(2)

23. Changes to the Software • To properly simulate network changes, such as reversible HOV facilities, contra flow lanes and etc, the following changes were made to the software: • Ability to turn facilities on and off during the simulation • Ability change the capacity of facilities during the simulation. • Ability to animate packet during the simulation

24. Changes to the Methodology Previously, break down the 72-hours evacuation into 72 single hour assignments to allow network changes Now simulate the entire 72 hours of evacuation in one long simulation, and turn on contraflow lane or reversible HOV in the middle of simulation Reduces run time from 3 days to half days

25. Cluster Speed up the simulation by distributing the work to more than one processors Now groups of computers can work on finding the best path for each packet (one major task). While others work on simulating the packets as they become available (the other major task).

26. Volume Delay Curves In macroscopic assignment, assigned volume can exceed capacity. The Volume-Delay curves were adjusted to limit the ability of the model to assign more trips than the available capacity. The speed is too high comparing to reality

27. Example: Freeway curve

28. Volume Delay Curves(2) • On contrast, DTA does not allow volume to exceed capacity. • Therefore, speed should decrease sharply when volume approaches capacity • Standard speed-capacity curve from Highway Capacity Manual replaces the volume delay curve in regional demand model

29. Mesoscopic Simulation When Compared with Macroscopic Assignment: • Vehicles take up space and progress through the network. • Capacity strictly limits the rate at which vehicles progress. • Available Storage strictly limits the number of vehicles that can occupy a link. • If vehicles cannot progress they must wait. • A full link blocks ‘back’ and will impact upstream links

30. Theorem of One Bad Link In static assignment, volume on one link may over capacity and does not impact adjoining roadways. In the mesoscopic simulation, when a link is over capacity, incoming vehicles must queue on upstream links to wait for their turn A link with extremely high v/c ratio could cause serious congestion on adjacent links

31. Impacts on Mesoscopic Assignment Example of a centroid connector between a mall (represented by a TAZ) and a frontage road … It is the only centroid connector of that TAZ. Frontage road has capacity of 1444 vph , but than 6000 trip demands during 8am… tens of thousands of trips sitting on the upstream links blocking all the roadways. Solution: adding more centroid connectors

32. Network Clean up • Incorrect Network coding may cause illogical path. Its impact could be very severe in mesoscopic assignment • Missing turn prohibition • Incorrect distance coded • Lazy coding: one coded link to substitute many links in real world

33. Impact of Incorrect Distance • The Frontage road coded as 0.2 miles instead of 1.1 miles • Freeway through traffic diverts to frontage road • Subsequent time slices showing illogical backup on other links

34. Example of Lazy codingOne link to represent all direct ramps Lazy Coding Detail Coding

35. Calibration Now in Calibration Phase of a normal day assignment Identify (and fix) problem spots in the network using two approaches: A static assignment to check for areas were Volume greatly exceeds capacity Run DTA on sub-areas for faster run time and easier problem identification, particularly network problem.

36. Conclusion - Discovery • Sufficient number of iterations is required to eliminate long travel time and nonsense backup • Clean network is necessary • High V/C ratio link in static model will cause severe congestion on adjoining links in DTA assignment • HCM curve is more suitable for DTA than volume delay curve for regional model

37. Conclusion - Progress • Develop probabilistic distribute to aggregate and to simulate fraction trips to integer trips • Replaces the “simplified” network with full network • Multi-class assignment adopted • A single 72-hours simulation substitute 72 one-hour assignment, saving run time

38. Continuing Challenges • Calibrate the normal day scenario • Mesh evacuation traffic with non- evacuation traffic, as these two types of traffic behave very different. • Code traffic signals • More network cleanup may be necessary • Trip Table adjustment?