01154517

Component

https://doi.org/10.3141/2161-03

http://scholar.google.com...sson&publication_year=2010

Incident response and mitigation are among the main tasks of operators at traffic control centers. Simulation models have a good chance of reproducing and predicting the effects of incident response by explicitly modeling driver response to the incident and information provided. In the PREDIKT project sponsored by the Swedish National Road Administration, the state-of-the-art mesoscopic simulation model MEZZO was extended to provide decision support for incident management. Numerous essential modeling components are described and tested, including modeling the incident response logic, a mixed-logit model, and a method for generating alternatives for drivers switching routes. In addition, the results of a fast calibration method based on simultaneous perturbation statistic approximation are presented. The model components are tested in a small case study that investigates the effect of delay in providing information to drivers after incidents. A linearization of speed–density functions also is shown to improve computational performance by 30% and increase calibration speed and stability while preserving simulation accuracy.

01173561

10-1989

English

pp 20-28

2010

Transportation Research Record: Journal of the Transportation Research Board

9780309142892

Print

Figures (9) ; References (21) ; Tables (2)

Calibration; Case studies; Decision support systems; Incident management; Route choice; Traffic incidents; Traffic simulation

MEZZO (Computer model)

Driver reaction; Mixed logit models; Speed-density relationships; Traffic information

Sweden

Highways; Operations and Traffic Management; Planning and Forecasting; I71: Traffic Theory; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 25 2010 10:55AM

• Data Archives of Intelligent Transportation Systems Used to Support Traffic Simulation
• Ex Post Evaluation of Calibrated Simulation Models of Significantly Different Future Systems
• Investigating the Shape of the Macroscopic Fundamental Diagram Using Simulation Data
• Modeling the Lane-Changing Execution of Multiclass Vehicles Under Heavy Traffic Conditions
• Research and Implementation of Lane-Changing Model Based on Driver Behavior