Traffic Modal Splitting Model Based on Game Theory with Incomplete Information

Abstract

Traffic modal splitting plays an important role in the traditional four-stages-forecast model. Usually in a stable urban traffic network, traffic supply can meet the demand basically, and a variety of traffic modal will bear a fixed proportion of passengers. Compared with other trip mode, public transportation is often influenced by some uncertain factors, e.g. transferring and waiting, which will cause different marginal cost and finally come to a new balance or imbalance between demand and supply. In this paper, traffic modal was supposed as a rational gamer, and generalized trip cost was considered as the cost of gamer. Then, traffic mode share can finally be got via comparing supply of all kinds of traffic means. A case study is conducted and compared with disaggregate modal, which shows the game theory-based model is more effective and the outcome is closer to the real traffic modal share.