Dynamic ridesharing with intermediate locations

Ridesharing concerns people that are willing to intelligently ride in order to save money and protect environment. The idea is based on a better use of private car. More precisely, it aims to bring together individuals that share, even partially, a trip. In the recurring ridesharing problem, when an offer is matched with a demand, the driver picks-up the rider at his starting location, drops him off at his ending location and continues to his target location. This approach lacks of flexibility and misses some possible matchings. In this paper, we propose a new ridesharing approach in which a driver and a rider accept to meet in an intermediate starting location and to separate in another intermediate ending location. This allows to reduce both the driver's detour and the total travel cost. We propose exact and heuristic methods to compute meeting points that minimize the total travel cost of the driver and the rider. We analyze their empirical performance on a set of real road networks consisting of up to 3,5 million nodes and 8,7 million edges. Our experimental analysis shows that our heuristics provide efficient performances within short CPU times and improves the recurring ridesharing approach.