STOCHASTIC CONGESTION AND PRICING MODEL WITH ENDOGENOUS DEPARTURE TIME SELECTION AND HETEROGENEOUS TRAVELERS

This paper proposes a stochastic congestion model with two pricing schemes: omniscient pricing and observable pricing. Specifically, omniscient pricing assumes the transportation administrative agency is aware of each traveler's cost structure, while observable pricing considers queuing delay only. Further, travelers are characterized by their late-acceptance level, while three types of travelers are classified. Congestion patterns developed with different compositions of traveler types, with and without tolls, are discussed. Numerical simulation indicates that omniscient pricing is more effective in suppressing peak hour congestion and distributing demands over longer time horizon. Moreover, pricing schemes are found to be more effective with diversified cost structures than with identical cost structures. This is consistent with earlier studies in the literature. However, the ultimate benefits of a certain pricing scheme are found to not only depend on travelers' cost structure, but also the composition of late-tolerant, late-averse and late-neutral travelers in the entire population.