Integrated optimization of ride-pooling and shared micro-mobility services with meeting points

• Integrated optimization of ride-pooling and shared micro-mobility services. • Inter-modal transfer at meeting points is modeled. • Availability of micro-mobility vehicles at meeting points is considered. • Efficient algorithm is developed to derive optimal operational strategy in real time. This paper studies the integrated optimization of ride-pooling and micro-mobility services within a multimodal transportation network to enhance the likelihood of ride-pooling, reduce the waiting time for passengers, and improve the platform’s profit. We consider an integrated platform that simultaneously provides ride-pooling and micro-mobility services. Instead of door-to-door ride-pooling services, we consider inter-modal transfer at meeting points, where riders can access or egress nearby pickup or dropoff (PUDO) points using micro-mobility vehicles and then get picked up and dropped off at these meeting points by ride-pooling vehicles. We investigate the real-time operational strategies of such a multimodal system taking into account the availability of micro-mobility vehicles at meeting points. In view that riders’ PUDO choices are interdependent in the integrated services, we devise a new dual-graph-based method that enables the decomposition of ride-pooling vehicle routing decisions and assignment decisions. We develop several interconnected subproblems that consider the mutual impacts between ride-pooling and micro-mobility services while we jointly determine rider-vehicles assignment, PUDO selection, ride-pooling vehicle routing decisions, micro-mobility vehicles repositioning decisions, and the transportation of micro-mobility vehicles on ride-pooling vehicles along with riders. We devise efficient algorithms for constructing graphs, identifying feasible trips, and making routing decisions for ride-pooling vehicles based on dynamic programming. The proposed models and algorithms are validated using real-world ride-hailing and bike-sharing data from Manhattan, New York City. The tests demonstrate that our algorithms can efficiently compute optimal matching. The results suggest that jointly operating ride-pooling and micro-mobility services can enhance rider shareability and reduce the repositioning costs of micro-mobility vehicles, thus benefiting both systems. Compared to door-to-door services, the integrated services can increase the number of served riders by more than 10 % while reducing repositioning costs by more than 50 % in the morning peak hour.