Quantifying Congestion Externalities in Road Networks: A structural estimation approach using stochastic evolutionary model

This study estimates the structural parameters of a travel time function, which relates traffic volume to travel time, within the context of a traffic assignment model in which travelers strategically select routes to minimize their travel costs, influenced by congestion. The proposed model is formulated as a potential game, enabling the estimation of parameters using the maximum likelihood method based on a stochastic evolutionary process. The impact of congestion pricing on welfare is evaluated using the estimated parameters. Preliminary analysis using the Sioux Falls network shows that congestion pricing enhances overall welfare, even when accounting for estimation errors.