2018 IEEE 34th International Conference on Data Engineering (ICDE) (2018)
Apr 16, 2018 to Apr 19, 2018
Ride-sharing (RS) has great values in saving energy and alleviating traffic pressure. In this paper, we propose a new ride-sharing model, where each driver requires that the shared route percentage (SRP, the ratio of the shared route's distance to the driver's total traveled distance) exceeds her expected rate (e.g., 0.8) when sharing with a rider. We consider two variants of this problem. The first considers multiple drivers and multiple riders, and aims to compute a set of driver-rider pairs to maximize the overall SRP. We model this problem as the maximum weighted bigraph matching problem. We propose an effective exact algorithm, and an efficient approximate solution with error-bound guarantee. The second considers multiple drivers and a single rider and aims to find the top-k drivers for the rider with the largest SRP. We devise pruning techniques and propose a best-first algorithm to progressively selects drivers with high probability to be in the top-k results.
graph theory, road traffic, traffic engineering computing
N. Ta, G. Li, T. Zhao, J. Feng, H. Ma and Z. Gong, "An Efficient Ride-Sharing Framework for Maximizing Shared Routes," 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 2018, pp. 1795-1796.