Transportation Network Simulation & Analysis I

WA43.1 Performance of a Stable Route Guidance Model for Real-Time Deployment

• Ta-Hui Yang; Purdue University, Sch. of Civil Eng., West Lafayette, IN 47907-1284;
• Srinivas Peeta; Purdue University, Sch. of Civil Eng., West Lafayette, IN 47907-1284; peeta@purdue.edu

Experiments are conducted to analyze the performance of a reactive dynamical system-based stable route guidance model for real-time deployment. The results are compared with those of a rolling horizon-based traffic assignment model and a deterministic DTA model. The proposed model can be implemented in sub-real time while ensuring performance comparable to the rolling horizon-based implementation.

WA43.2 A Hybrid Optimization-Mesoscopic Simulation Dynamic Traffic Assignment Model

• Michael A. Florian; INRO Solutions, 5160 Decaarie Blvd., Ste. 610, Montreal, Quebec, H3C 3J7 , Canada; mike@inro.ca
• Michael Mahut; University of Montreal, CRT, CP 6128, Station Centre-Ville, Montreal, Quebec, H3C 3J7 , Canada; michaelm@crt.umontreal.ca
• Nicolas Tremblay; INRO Consultants, Inc., 5160 Decarie Blvd., Ste. 610, Montreal, Quebec, H3X 2H9 , Canada; nicolas@inro.ca

We present a new dynamic traffic assignment model based on the mesoscopic space-time queue network loading method developed by Mahut. This hybrid optimization-simulation method was applied to a portion of the Stockholm, Sweden road network which consists of 220 zones, 2080 links and 4965 turns. The results are presented.

WA43.3 Calibration of Highway Micro-Simulation Models using ITS Data

• Kyu-Oh Kim; Texas A&M University, Texas Tramsportation Inst., College Station, TX 77843; k-kim@ttimail.tamu.edu
• L. R. Rilett; Texas A&M University, Dept. of Civil Eng., Texas Transportation Inst., College Station, TX 77843; rilett@tamu.edu

Our premise is that ITS data provides a unique opportunity for calibrating and validating traffic simulation models. We will focus on the automatic calibration of micro-simulation models. Three optimization methods, GA, SA and simplex, will be used to calibrate the micro-simulation parameters in CORSIM and TRANSIMS. The test bed will be a freeway corridor in Houston, TX...

WA43.4 GENOSIM: A Genetic Algorithm-Based Optimization Tool for Automating the Calibration of Microscropic Traffic Simulation Models

• Baher Abdulhai; University of Toronto, Dept. of Civil Eng., 35 Saint George St., #105, Toronto, Ontario, M5S 1A4 , Canada; baher@ecf.utoronto.ca
• Tao Ma; University of Toronto, Civil Eng., Intelligent Trans., Systems Ctr. & Testbed, Toronto, Ontario, M5S 1A4;

We introduce GENOSIM, a new optimization tool for automating the calibration of traffic micro-simulation models for faster, systematic and robust model building. GENOSIM is developed as an independent software employing state-of-the-art GAs for combinatorial parametric optimization and is integrated with a dynamic traffic microscopic simulation model using Paramics microsimulation suite...