Modular vehicles (MV) possess the ability to physically connect/disconnect with each other and travel in platoon with less energy consumption. A fleet of demand-responsive transit vehicles with such technology can serve passengers door to door or have vehicles deviate to platoon with each other to travel at lower cost and allow for en-route passenger transfers before splitting. A mixed integer linear programming (MILP) model is formulated to solve this "modular dial-a-ride problem" (MDARP). A heuristic algorithm based on Steiner-tree-inspired large neighborhood search is developed to solve the MDARP for practical scenarios. A set of small-scale synthetic numerical experiments are tested to evaluate the optimality gap and computation time between exact solutions of the MDARP using commercial software and the proposed heuristic. Large-scale experiments are conducted on the Anaheim network with 378 candidate join/split nodes to further explore the potentials and identify the ideal operation scenarios of MVs. The results show that MV technology can save up to 52.0% in vehicle travel cost, 35.6% in passenger service time, and 29.4% in total cost against existing on-demand mobility services in the scenarios tested. Results suggest that MVs best benefit from platooning by serving "enclave pairs" as a hub-and-spoke service.
翻译:摩托车辆(MV)具有实际连接/分解的能力,在排内旅行,能源消耗较少。具有这种技术的符合需求的临时运输车辆车队可以供乘客挨家挨户地使用,或让车辆排成排,以较低成本旅行,并允许在分解前进行路运客运转移。设计了一个混合整形线性编程模型,以解决“摩托性拨号问题”(MDARP),根据斯坦纳-树木激发的大型街坊搜索开发一种超速算法,以解决MDARP的实际情况。一套小型合成数字实验可以用来评估MDARP在使用商业软件和拟议的超高压式解决方案之间的最佳差距和计算时间。在阿纳海姆网络上进行了大规模实验,378名候选人加入/跳出节点进一步探索了MDARP的潜力,并确定MV的理想操作方案。结果显示,MV技术可以节省52.0%的车辆旅行费用,35.6%的客运服务时间和29.4%的总费用计算结果显示,MARP-DRPS-MV-S-C-S-C-C-HAL-C-C-C-SDRVD-SL-S-C-C-C-C-S-S-Sir-SLVDRVDRVD-SL-SD-SD-SD-S-S-S-S-S-S-SL-SL-SL-SL-SL-SD-SL-SL-SL-SL-SL-SD-SD-S-S-SL-SL-SD-SD-S-S-S-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-SD-SD-SD-S-SD-S-S-SL-SL-SL-SL-SL-S-SL-SL-SL-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-SL-S-S-S-S-S-S-S-S-S-S-S