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

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.