Stochastic service network design for a platooning service provider

Automated driving is expected to support a wide range of transportation applications in the near future. However, especially in urban environments, not all streets may be feasible for automated driving which restricts the operation of autonomous vehicles (AVs) to certain zones. Outside of these zones, AVs may be safely navigated by a leading vehicle that is operated by a human driver using the concept of platooning. In this paper, we consider the service network design problem of a service provider that offers platooning services to AV operators in an urban environment in exchange for monetary compensation. Tactical planning decisions comprise determining the fleet size and scheduling platooning services for a planning horizon such as a season. Those decisions are supported by the quoting of rates to potential customers that reflect their willingness to pay depending on the received service level. A second stage of decisions, made on each day of the planning horizon, comprises the acceptance or rejection of individual platooning requests and the routing of AVs through the platooning services. Since the platooning demand is assumed to be stochastic, we model the problem as a two-stage stochastic integer program. On a real-world based network, we perform computational experiments that indicate potential profits for a platooning service provider and considerable savings for AV operators with different demand characteristics. We further assess the value of considering uncertainty.