Experimental Studies for Traffic Incident Management with Pricing, Private Information, and Diverse Subject

David Brownstone, Michael McBride, Si-Yuan Kong and Amine Mahmassani

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: 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. We are 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 our existing results, we propose four new extensions to our study: the addition of more realistic driving mechanics to test driver responses to our treatments under increased cognitive load, the recruitment of subjects outside the UCI student body to confirm the validity of our 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 our experimental subject pool will strengthen the robustness and validity of our 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.

Keywords: Engineering (search for similar items in EconPapers)
Date: 2018-09-11
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