On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment.

ABSTRACT: Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm

SUBMITTER: Alonso-Mora J 

PROVIDER: S-EPMC5255617 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature