Modeling Drivers in Route Diversion Behavior During Congestion: A Pilot Study

This study investigates factors influencing drivers’ decisions to divert their routes in response to congestion and delays on coastal road networks. Key variables examined include information-seeking behavior, travel time, trip factors, demographics, and disruption scenarios such as emergency evacuations. The research utilized a comprehensive survey distributed to U.S. drivers to assess diversionary choices on coastal road networks based on travel habits, information sources, and demographic characteristics. The survey included questions about routine travel behaviors, sources of traffic information, and intended diversion actions under various scenarios, including severe weather events common to coastal regions. Logistic regression models, including multinomial and ordinal logit models, were employed to analyze the data. Results indicate that receiving real-time traffic information significantly increases the likelihood of diversion, particularly during work zones and adverse weather conditions such as fog or heavy rain. Travel time and delays emerged as critical motivators for route changes in coastal areas, with drivers experiencing longer delays being more likely to divert. Demographics impact diversion behavior: drivers aged 18 to 30 tend to choose “No Divert” during morning commutes and are less often “Unsure” during afternoon commutes.