We introduce an improved algorithm for the dynamic taxi sharing problem, i.e. a dispatcher that schedules a fleet of shared taxis as it is used by services like UberXShare and Lyft Shared. We speed up the basic online algorithm that looks for all possible insertions of a new customer into a set of existing routes, we generalize the objective function, and we efficiently support a large number of possible pick-up and drop-off locations. This lays an algorithmic foundation for taxi sharing systems with higher vehicle occupancy - enabling greatly reduced cost and ecological impact at comparable service quality. We find that our algorithm computes assignments between vehicles and riders several times faster than a previous state-of-the-art approach. Further, we observe that allowing meeting points for vehicles and riders can reduce the operating cost of vehicle fleets by up to 15% while also reducing rider wait and trip times.

翻译：我们提出了一种针对动态拼车问题的改进算法，即调度共享出租车车队的方法（如UberXShare和Lyft Shared等服务所使用的技术）。我们加速了基础在线算法——该算法通过遍历所有可能的插入位置，将新乘客插入现有路线集合中；同时我们推广了目标函数，并高效支持大量可选的上车点和下车点。这为提升车辆载客率的拼车系统奠定了算法基础——在保持同等服务质量的前提下，大幅降低成本和生态影响。实验表明，我们的算法在计算车辆与乘客匹配时，速度比现有最优方法快数倍。此外，我们观察到，允许车辆与乘客在会合点交接，可降低车队运营成本高达15%，同时减少乘客等待时间与行程时间。