Optimization Approach to Improve the Ridesharing Success Rate in the Bus Ridesharing Service

In high-capacity ridesharing, increasing the number of passengers per shared vehicle can achieve long-term profitability for the public transport providers; hence, the ridesharing success rate (i.e., the percentage of successful applicants) is an important indicator of monetary cost. Unlike peer-to-peer ridesharing vehicles, to open a route, high-capacity ridesharing vehicles need to satisfy the minimum loadable capacity. However, an insufficient amount of similar travel demands gathered on less popular routes can result in the forced cancellation of many bus lines, thereby reducing the ridesharing success rate. In this paper, for a bus ridesharing service, we present an optimization approach for maximizing the ridesharing success rate. Utilizing this approach, we solve the problem of low vehicle utilization by using a dynamic grid-based heuristic algorithm with performance guarantees and a novel bus ridesharing model of a hybrid form of ridesharing that combines slugging with hitchhiking. To further assess the effectiveness of the proposed approach, we evaluate the solution by using benchmarks from a real-life dataset that contains 65,065-trip instances extracted from 10,585 Shanghai taxis from one day (April 1, 2018), and we compare our results with solutions provided by the existing forms of ridesharing. The experimental results demonstrate that the proposed approach can improve the ridesharing success rate by 79.6%.