Shiyao Zhang, Christos Markos, and James Jianqiao Yu*
IEEE Transactions on Intelligent Transportation Systems, Volume 23, Issue 10, Oct. 2022, Pages 18466-18477
Autonomous vehicle (AV) integration poses a significant challenge for intelligent transportation systems (ITSs). The ability to automatically coordinate complex AV operations at scale is crucial for advancing the quality of core transportation services, such as ride-sharing and parcel delivery. However, existing studies have only considered either of these two services independently from the other, disregarding the potential benefits of their combined optimization. To address this open problem, we design an autonomous vehicle intelligent system (AVIS) providing joint ride-sharing and parcel delivery services under realistic ride and route constraints. We formulate the joint optimization problem through the scope of mixed-integer linear programming and solve it using the Lagrangian dual decomposition method to ensure scalability. We conduct extensive case studies to evaluate the performance of the proposed AVIS and its constituting components. Our experimental results demonstrate that AVIS can effectively provide both ride-sharing and parcel delivery services while satisfying service requests in transportation networks of various scales. In addition, the distributed method is shown to generate near-optimal solutions in reduced computation time.