Finding the robust quickest path for call-taxis in a city road network

Abstract

The increased number of vehicles on city roads has prompted a new type of transportation logistics problem of finding the quickest path for call-taxis through a city road network, where the travel times are stochastic. The stochastic nature of travel times are caused by various obstacles in a road network such as traffic signals and speed breakers. A Monte-Carlo simulation based approach is developed to identify unique quickest paths between two locations in a stochastic road network. A multi-criteria score is proposed to identify the time robust path among the unique paths. The proposed solution approach can be embedded in the navigation system of call-taxis to help them identify a path that has a higher likelihood of reaching a location on time.

Finding time‐robust fuel‐efficient paths for a call‐taxi in a stochastic city road network

“…A multi-criteria score is then assigned for each unique path based on the probability that the path is fuel-efficient, the average travel time of the path and the coefficient of variation of the travel times of the path. This is an extension of the work by Godwin [58], where the emphasis was only on finding the robust shortest time path. The solution approach proposed in this paper could be used for driver assist navigation system in call-taxis for finding time-robust fuel-efficient path.…”