Challenges for obtaining a system-optimal traffic distribution by giving route advice due to the biased memory of congestion

Abstract

A promising approach to avoid congestion is to distribute traffic in the street network in a system-optimal manner. This could be calculated by a centralized traffic management system to be communicated as route advice. However, human drivers can independently decide whether to follow the route advice or to dissent. When trying to influence route choice, drivers’ travel experiences may influence their reaction to route advice. When recalling past events, people tend to remember the extremes (best and worst of times) more easily than the most typical of time (called impact bias) and if unaware of the atypicality of an event, drivers may unconsciously rely on it when making an affective forecast of a similar future event and act accordingly (affective forecasting).To investigate if this behavior also occurs in route choice decisions, a conceptual replication of the study of Morewedge, Gilbert, and Wilson (2005) was made. Using an online-survey, drivers (n = 155) were asked to recall, report, and rate their affective memories of past congestion events (four recall conditions, between-subject design) and to forecast their affective reaction to an upcoming congestion on their next trip. Further, they had to make route choice decisions, given route advice with varying congestion share on the route alternatives.Results show that drivers indeed tend to recall extreme experiences. However, the affective quality of the event recalled could neither explain the affective forecast of upcoming events nor the driver’s route choice decision. Exploratively, it was found that drivers were generally more willing to face congestion than to consider bypassing it by a detour.