Reducing strategic uncertainty in transportation networks by personalized routing advice: A route-choice laboratory experiment

Abstract

One fundamental reason causing traffic flow instability and the difficulties in predicting traffic conditions is strategic uncertainty. This paper experimentally investigated how routing advice influenced strategic uncertainty and analyzed compliance behavior and decision time that might affect strategic uncertainty. Subjects participated in a route-choice game in which they were required to choose among three routes from one origin to one destination. Two routing advice strategies, user-optimal recommendation (UOR) and system-optimal recommendation (SOR), taking into account subjects’ choice inertia, were investigated. The experimental results indicated that (i) UOR could reduce strategic uncertainty and stabilize traffic flow, whereas SOR was counterproductive, (ii) subjects were more likely to comply with UOR compared with SOR and preferred to follow the advice with the same choices as the previous round rather than the route switching advice, (iii) the subjects with faster decisions (intuition) had higher compliance rates and lower travel costs than those with slower decisions (deliberation). Our experimental findings suggest that fairness and psychological factors are crucial in route choice, providing valuable guidance in designing personalized advanced traveler information systems.