01099308

Component

https://doi.org/10.3141/2086-09

http://scholar.google.com...lhai&publication_year=2008

Microscopic traffic simulation models offer virtual reproduction of full-scale traffic networks with individual vehicle and driver resolution. However, relevant behavioral aspects, such as route-choice behavior, are based on some theoretical assumptions. Alternatively, driving simulators allow for direct testing of real subjects. However, the virtual driving environment is typically a fairly rudimentary representation of the road network and traffic conditions, focusing on the immediate surroundings of the test vehicle. As such, both tools were integrated to create a mixed reality traffic analysis environment. The objective is to enhance the credibility of in-lab-simulated route-choice experiments under various intelligent transportation system applications. The mixed reality system allows a human subject to “drive” a vehicle in a microscopic traffic simulation model of an actual physical network. An externally controlled driving capability was integrated into the widely used Quadstone Paramics microscopic traffic simulator. The developed mixed reality platform was used at the Toronto (Canada) Intelligent Transportation System Centre to test subjects while driving in a simulated model of a main downtown Toronto corridor. Drivers were given descriptive and prescriptive traffic information while their reactions were monitored. For comparative purposes, they were also tested using a more classical map-based point-and-click route-choice procedure. Results of the analysis highlight the potential of the developed mixed reality platform to enhance the realism of in-lab-simulated route-choice experiments and hence improve the credibility of collected data. Both the virtual reproduction of the choice environment and the tangible consequences of choice decisions contribute to an enhanced experimental environment.

01120900

English

pp 72-80

2008

Transportation Research Record: Journal of the Transportation Research Board

9780309125987

Print

Figures (3) ; References (27) ; Tables (2)

Driving simulators; Intelligent transportation systems; Microsimulation; Route choice; Traffic simulation; Travel behavior

Toronto (Canada)

Highways; Operations and Traffic Management; I73: Traffic Control

TRIS, TRB, ATRI

Jan 29 2008 3:09PM

• Automatic Camera Calibration Using Pattern Detection for Vision-Based Speed Sensing
• Determinants of Route Choice and Value of Traveler Information: A Field Experiment
• Distributed Controller Design Approach to Dynamic Speed Limit Control Against Shockwaves on Freeways
• Effectiveness and Acceptance of Adaptive Intelligent Speed Adaptation Systems
• Evaluating Traveler Information Effects on Commercial and Noncommercial Users
• Evaluation of Cell Phone Traffic Data in Minnesota
• Evaluation of Route Guidance Strategies Based on Vehicle–Infrastructure Integration Under Incident Conditions
• Implementing Vehicle–Infrastructure Integration: Real-World Challenges
• Mobility and Commute Disutility Effects of 511 Deployment in Salt Lake City, Utah
• Operation Data for Evaluating Benefits and Costs of Advanced Traffic Management Components
• Real Options to Increase the Value of Intelligent Transportation Systems
• Real-Time Vehicle Classification Using Inductive Loop Signature Data
• Traffic Probe Data Processing for Full-Scale Deployment of Vehicle–Infrastructure Integration
• Vehicle Detection in Far Field of View of Video Sequences
• Wireless Infrastructure-to-Vehicle Communication Technologies to Increase Road Safety Along Motorways