Traffic incidents and other unexpected disruptions on roadways lead to extensive delays that diminish the quality of life for those that live and/or work in major cities nationwide. The effective management of these incidents is hindered by an incomplete understanding about how drivers respond toinformation provided by network operators. We propose using economic experiments involving human subjects and a networked, realistic driving simulation to directly study driver behavior in response to information dissemination and pricing schemes designed to manage congestion in traffic networks. Specifically, our study will focus on two mechanisms of management: the use of variable message systems (VMS) and the use of roadway pricing to induce diversion to alternate routes. Our pilot study demonstrates the ability of our platform to elicit reasonable driving behavior from subjects and will guide the implementation and refinement of our ful experiment. Messaging scheme improvements for use with extant VMS infrastructure could provide a low-cost tool for general incident management, while insights into messaging/pricing synergies could provide new strategies for the management of tolled facilities.

The effective management of traffic incidents and other irregular disruptions on roadways is key to minimizing travel delay and improving the quality of life for urban residents and businesses. This project is currently using economic experiments involving human subjects and a networked, realistic driving simulation to study driver behavior in response to information displayed by variable message systems and to dynamic road pricing schemes. Based on existing results, the project will propose four new extensions to this study: the addition of more realistic driving mechanics to test driver responses to the projects treatments under increased cognitive load, the recruitment of subjects outside the University of California, Irvine (UCI) student body to confirm the validity of the results with different demographic groups, the implementation of treatments to study the impact of private information messaging systems (e.g. Waze, Google Maps, etc.), and the implementation of treatments to study a novel value-of-time based auction system for toll lane pricing and allocation. Improvements to the driving realism and the representativeness of the projects experimental subject pool will strengthen the robustness and validity of this study’s results, while the investigation of private information messaging and value-of-time auction scenarios will shed light on their potential for improving transportation management.