Hierarchical Vehicle Scheduling Research on Tide Bicycle-Sharing Traffic of Autonomous Transportation Systems

To facilitate the intelligent and automated provision of mobility services by autonomous transportation systems, bike-sharing can be a supplement to public transport for addressing their point-to-point issue, namely, “last mile” service. However, according different nature land use, uneven spatio-temporal distribution travel demand directly lead difficult access bikes with high costs users operating operators. Based on this, this paper analyzes user behavior patterns within areas using GeoHash encoding proposes hierarchical vehicle scheduling model based tide bicycle-sharing traffic, HATB. It minimizes maximizes satisfaction dynamically optimize routes required vehicles each layered zone. As extracting historical orders Mobike in Beijing, an example analysis through genetic algorithm HATB is conducted support effective efficient scheduling. Compared existing methods, has faster convergence lower time complexity, which improves bike turnaround efficiency practical application ability, thus making it more convenient during peak hours.