Contrarians do better: Testing participants’ response to information in a simulated day-to-day route choice experiment

• Published in: Travel, behaviour & society Vol. 15; pp. 146 - 156
• Main Author: Meneguzzer, Claudio
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2019
• Subjects: Day-to-day traffic dynamics; Dynamic process model; Experimental analysis; Pre-trip information; Route choice behavior; Route switching; Day-to-day traffic dynamics; Pre-trip information; Route switching; Route choice behavior; Experimental analysis; Dynamic process model
• ISSN: 2214-367X
• DOI: 10.1016/j.tbs.2019.02.003

•Laboratory-like experiment to investigate day-to-day route choice dynamics.•Different information provided to subjects in two sequential phases of experiment.•Subjects enacting contrary responses to information achieved better performance.•Effects of memory depth were significant under conditions of partial information.•Dynamic process model of route choice estimated on experimental observations. This paper reports the results of a laboratory-like experiment aimed at investigating some key aspects of day-to-day route choice behavior in a simple two-link network. Two different information scenarios (full vs. partial information about previous travel times) were implemented as sequential phases of the experiment. It was found that User Equilibrium conditions, though reached on several occasions, did not persist as a steady state. The temporal evolution of route changes showed no significant trend within each phase of the experiment, but a considerable “between-phase” decrease in route switching activity was detected. The analysis of participants’ modes of response to information reveals a prevalence of direct (“naïve”) over contrary (“strategic”) behavior, and shows that contrarian subjects are, on average, more successful in terms of individual travel time than those reacting in a direct manner. Memory depth (the number of past values of travel times typically considered by participants as the basis for their next route choice) was found to be significantly associated with individual performance and prevailing mode of response only under conditions of partial information. Finally, the implementation of a discrete-time, deterministic process model of day-to-day route choice dynamics on the experimental network enabled the derivation of empirically based estimates of the route choice reviewing rate, the weight of the most recent experience in the formation of travelers’ forecasts of travel times, and the dispersion parameter of the underlying route choice model.