A game-theoretical analysis of route information cooperative update for road networks with mixed vehicles

Abstract

With the development of vehicle-to-everything technologies, both RVs and CAVs coexist on urban road networks in the foreseeable future. In the mixed driving traffic flow scenario, although the mixed vehicles can obtain the same route information, the systems by which they obtain and process this information are independent. To improve the operation efficiency of urban road networks, this study proposes a cooperative route information update strategy for the mixed traffic flow. Dynamic traffic assignment of the mixed vehicles is taken into account based on the game theory, and a travel cost model for the mixed traffic flow scenario is established using the macroscopic fundamental diagram theory. Furthermore, a Stackelberg-cooperative strategy is proposed to optimize the information update mechanism by adjusting the route information update frequency and route guidance criteria, considering the mixed vehicles routing characteristics. Third, to ensure benefits for both travelers and managers, the study analyses the impact of Stackelberg-Cooperative strategy on the mixed driving traffic flow scenarios and proposes a Stackelberg-Evolutionary-Cooperative strategy to periodically revise the information update strategy. Finally, numerical experiments on Hefei road networks are conducted to validate the effectiveness of the proposed Stackelberg-Evolutionary-Cooperative strategy.