Optimal pricing of endogenous congestion: a disaggregated approach

We design and estimate a game theoretic congestion pricing mechanism in which the regulator aims at reducing traffic congestion by discriminating travelers according to their willingness to travel on the network. He knows that travelers learn about their environment, that their preferences are affected by the reputation of each available mode of transportation and that congestion can be seen as a Bayesian game in which travelers impose externalities on each other. We derive individual optimal fares depending on each traveler's valuation of transportation. Welfare simulation results based on a French household survey show that the travelers' perception of the mode of transportation and income sensitivity differences are important determinants of welfare improvement.