Exploring consumer preferences for traffic congestion alleviation policies in intelligent transportation systems

Traffic congestion imposes substantial social costs through longer travel times, higher operating costs, and increased accident risks. This study examines consumer preferences for traffic congestion alleviation policies in the context of intelligent transportation systems in South Korea, focusing on how consumers evaluate different infrastructure-based policy options and their expected effects. The policy options include smart-toll systems, smart road entrance, vehicle-to-everything (V2X) service, and new road construction, while the key effects include changes in travel cost, travel time, and accident risk. Using a discrete choice experiment and a mixed logit model, this study analyzes how consumers trade off these policy options and effects when evaluating congestion alleviation measures. The results show that consumers prefer policies that reduce travel time and accident risk, with stronger support for information and communications technology (ICT)-based infrastructure improvements, particularly smart-toll systems, than for conventional road expansion. However, preferences for V2X service are heterogeneous and statistically insignificant, suggesting uncertainty in consumer acceptance of emerging connected-vehicle technologies. By comparing consumer preferences for multiple congestion alleviation options and their expected effects, this study provides empirical evidence for designing traffic infrastructure policies that better reflect consumer priorities in intelligent transportation systems.