Congestion-Avoiding Routing and Charging Scheduling Mechanism for Shared Autonomous Electric Vehicle Networks in Urban Areas

Urbanization is an inevitable trend in the future. By 2050, more than two-thirds of the world’s population is expected to live in metropolitan areas. However, traffic congestion caused by the rapid growth of vehicle traffic is getting deteriorated in metropolitan areas. Although governments of many countries have proposed various traffic management schemes to alleviate traffic congestion in urban areas during peak hours, the large volume of traffic during peak hours caused by the dramatic increase in private-owned vehicle continues to cause significant economic losses to the public and affect the future development of metropolitan areas. Meanwhile, it is well known that that the world’s vehicle manufacturers focus on the development of self-driving electric vehicles (EVs). As a result, the combination of self-driving EVs and widespread ride-sharing services will not only reduce the frequency of human traffic accidents, but will also alleviate the current traffic congestion. Although route selection and charging of conventional EVs have been extensively explored in the literature, the operational characteristics of ride-sharing services need to be investigated in the context of route selection and charging of shared self-driving electric vehicle fleets. In addition, the recent literature has focused on the mixed flow of manual vehicles and self-driving vehicles, but little attention has been paid to the future traffic management issues of the coexistence of private EVs and shared self-driving fleets. In view of this, this work considers the mixed traffic conditions of private EVs and shared self-driving fleets and proposes an integrated solution for shared self-driving EV fleet ride-sharing regulation and mixed traffic congestion prevention. The experimental results revealed that the solutions proposed in this work can not only be used by shared-vehicle operators for their fleet ride-sharing strategies, but will also be used by traffic management organizations of each country as a reference for future urban traffic management policies in light of the future mixed traffic conditions where private EVs and shared-vehicle fleets coexist.