Highly populated cities face several challenges, one of them being the intense traffic congestion. In recent years, the concept of Urban Air Mobility has been put forward by large companies and organizations as a way to address this problem, and this approach has been rapidly gaining ground. This disruptive technology involves aerial vehicles (AVs) for hire than can be utilized by customers to travel between locations within large cities. This concept has the potential to drastically decrease traffic congestion and reduce air pollution, since these vehicles typically use electric motors powered by batteries. This work studies the problem of scheduling the assignment of AVs to customers, having as a goal to maximize the serviced customers and minimize the energy consumption of the AVs by forcing them to fly at the lowest possible altitude. Initially, an Integer Linear Program (ILP) formulation is presented, that is solved offline and optimally, followed by a near-optimal algorithm, that solves the problem incrementally, one AV at a time, to address scalability issues, allowing scheduling in problems involving large numbers of locations, AVs, and customer requests.

翻译：人口稠密的城市面临若干挑战,其中之一是交通堵塞,近年来,大型公司和组织提出了城市航空流动的概念,作为解决这一问题的一种方法,这一方法已经迅速得到落实。这种破坏性技术涉及航空车辆(AVs)的租用,而客户无法在大城市内不同地点之间使用这种技术。这个概念有可能大幅降低交通堵塞,减少空气污染,因为这些车辆通常使用电动电动电动电动发动机。这项工作研究将AV派给客户的问题,目的是通过迫使客户在尽可能低的高度飞行,使服务客户最大化,将AV的能源消耗最小化。最初,提出了Integer线性方案(ILP)的配方,该配方在离线和最佳方式上解决,随后是近乎最佳的算法,逐步解决了问题,一次用AV(AV)解决可扩缩的问题,从而能够将涉及大量地点的问题、AVs和客户请求排入日程。