Hyper pooling private trips into high occupancy transit like attractive shared rides

Rafał Kucharski, Oded Cats
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Abstract

The size of the solution space associated with the trip-matching problem has made the search for high-order ride-pooling prohibitive. We introduce hyper-pooled rides along with a method to identify them within urban demand patterns. Travellers of hyper-pooled rides walk to common pick-up points, travel with a shared vehicle along a sequence of stops and are dropped off at stops from which they walk to their destinations. While closely resembling classical mass transit, hyper-pooled rides are purely demand-driven, with itineraries (stop locations, sequences, timings) optimised for all co-travellers. For 2000 trips in Amsterdam the algorithm generated 40 hyper-pooled rides transporting 225 travellers. They would require 52.5 vehicle hours to travel solo, whereas in the hyper-pooled multi-stop rides, it is reduced sixfold to 9 vehicle hours only. This efficiency gain is made possible by achieving an average occupancy of 5.8 (and a maximum of 14) while remaining attractive for all co-travellers.

Abstract Image

将私人出行过度集中到高乘座率的公交系统中,如极具吸引力的共享乘车服务
与出行匹配问题相关的求解空间之大,使得寻找高阶合乘问题变得困难重重。我们引入了超级合乘,以及在城市需求模式中识别超级合乘的方法。超级合乘的乘客步行到共同的上车点,乘坐合乘车辆沿一系列站点行驶,然后在站点下车,再步行前往目的地。虽然超级拼车与传统的公共交通非常相似,但它纯粹是由需求驱动的,其行程(停靠站点、顺序、时间安排)是为所有共同出行的人优化的。在阿姆斯特丹的 2000 次旅行中,该算法生成了 40 次超级拼车,共运送 225 名乘客。单人出行需要 52.5 个车时,而超级拼车的多站搭乘则减少了六倍,仅需 9 个车时。这种效率的提高得益于平均载客量达到 5.8 人(最多 14 人),同时对所有共乘者保持吸引力。
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