Qi Luo (University of Michigan), Xuechun Duo (Automotive Engineering), Xuan Di (Columbia University) and Robert Hampshire assess “Multimodal Connections between Bikesharing and Ride-Hailing: An Emperical Study in New York City” in the proceedings of the 2018 IEEE International Conference on Intelligent Transportation Systems.
Abstract: Multimodal transportation systems are the foundation for mobility-as-a-service. Ride-hailing and bikesharing are complementary modes of transport because the latter one serves long-distance trips and the latter one is suitable for first-last-mile trips. Regarding transport supply, the popularity of dockless bikeshare nowadays can also fulfill excess travel demand on ride-hailing platforms. In this paper, we propose a ride-bike-share system where passengers can switch from one mode of transport to another at stationary “carpool hubs”. Passenger throughput is increased by gathering them via bikeshare at these hubs for carpooling. The goal of this paper is to test the feasibility of this multimodal scheme by using taxi cab and bikeshare data from New York City in 2015. We identified 17 carpool hubs with coverage of 1 km among existing bike stations to cover all trip demand within the region during peak hours. After designing the network, we then assign trips to carpools depending on two trips’ similarity in time and space metrics. Our results show that over 80 percent of all trips can be assigned to carpools at almost all hubs based on an offline matching algorithm on a bipartite graph. Compared to a single-modal system, we can serve the same throughput of passengers with 40 percent of existing taxi cabs. This matching rate is achieved in every month in 2015 with small variances. This paper lays a solid foundation for implementing multimodal connections between ride-hailing and bikesharing.