A Simulation-based Optimization Approach to Efficiently Route Air Taxis in a Cyber-Physical Network

Besides air pollution and commuter stress, traffic congestions also lead to loss of productivity, increase in delay, vehicle operating cost, and accidents. To assuage these issues, several logistics companies are planning to launch air taxis, electric-powered vehicles that aim to provide faster passenger commutes on a daily basis at an affordable cost. This research is one of the first to propose a centralized framework to dispatch and route flying taxis in a cyber-physical network considering unique constraints pertaining to air taxi operations. The feasibility of the proposed approach is tested using potential air taxi demands in New York City (NYC) provided by a prior study. The results of the experimentation suggest that the minimum number of air taxis required for efficient operation in NYC is 84, functioning with an average utilization rate of 66%. In addition, the impacts of commuter willingness to fly rate, percentage of demand fulfillment, on-road travel limit, maximum customer wait time, and arrival distribution on the optimal number of air taxis, utilization rate, number of customers served and cost incurred per customer are examined. Analyses show that the willingness to fly rate appears to have a linear influence on the number of air taxis and the efficiency, while on-road travel distance has an exponential impact on the performance measures. The routing and dispatching algorithm developed in this paper can be used by any company that is interested in venturing into the air taxi market.