Application of Machine Learning in App-Based Cab Booking System: A Survey on Indian Scenario

Before the advent of the app-based cab system, people used to spend a lot of time chasing down a taxi and waiting for a significant amount of time to get a cab. The online cab booking system not only saves this time for people but also picks them up from their doorstep and drops them to their exact destination. However, the demand for app cabs in the current scenario implies an even more improvement in the existing online cab booking system. Authors have studied the existing research papers related to online cab booking systems and tried to put all their proposed solutions in this paper. Different authors have proposed different ideas to make the existing system more feasible. Some of the notable features are fleet utilization, bargaining facility, trip recording, etc. The authors have also discussed all the possible implementations of these features. In addition to the above-mentioned features, we have also discussed the possible solutions to some existing problems like single point failure, low availability of cabs, etc. Technologies like distributive algorithm, PDPTW algorithm, adaptive scheduling algorithm are used to overcome these problems. This paper will help the reader to get clear information about all the research related to the online cab booking system and provides possible solutions in the context of the existing system in India.