Quantifying the Effect of On-Street Parking Information on Congestion Mitigation using a Driving Simulator

Abstract

This study investigates travelers’ reactions to different types of information, in deciding their parking choice behavior and its effect on circulation time, through a driving simulator and a stated preference (SP) survey. In the simulator-based driving experiments, we develop a 3.47 mile2 network in the Chinatown area of Washington, D.C., with different scenarios of traffic, driving conditions, and information provision. The parking information is provided using a variable message sign (VMS) and mobile application. In all scenarios, participants can choose from three parking options with different prices and different walking distances to the destination (Verizon Garage, 11th St. Garage, and on-street parking). A sample of 76 participants with diverse socio-economic backgrounds who in total conducted 636 experiments is used. We applied a multinomial logistic regression model, linear regression, and t-test to analyze the collected data. We conclude that types of information and age are important determinants of drivers’ parking choice and compliance behaviors. In addition, the results show that the existence of information decreases the circulation time. In addition, the parking choice behavior revealed through the driving simulator is shown to be significantly different from that stated in the survey questionnaire.