On-demand ridesharing with optimized pick-up and drop-off walking locations

On-demand ridesharing with optimized pick-up and drop-off walking locations

Fielbaum, Andres (TU Delft Learning & Autonomous Control)
Bai, X. (Shenzhen University)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control)

2021

On-demand systems in which passengers with similar routes can share a vehicle are expected to become a relevant part of future mobility, thanks to their flexibility and their potential impact on reducing congestion. Nevertheless, due to the long detours required by a door-to-door scheme, they induce extra costs to the users in terms of delay. In this paper, we face the design of such a system in which users might be requested online to walk towards/from nearby pick-up/drop-off points if this improves overall efficiency. We show theoretically that the general problem becomes more complex (as it contains two sub-problems that extend set-cover), analyze the trade-offs that emerge, and provide a general formulation and specific heuristics that are able to solve it over large instances. We test this formulation over a real dataset of Manhattan taxi trips (9970 requests during one hour), finding that (a) average walks of about one minute can reduce the number of rejections in more than 80% and Vehicles-Hour-Traveled in more than 10%, (b) users who depart or arrive at the most demanded areas are more likely to be required to walk, and (c) the performance improvement of the service is larger when the system receives more trip requests.

On-demand
Pick-up and drop-off points
Ridepooling
Ridesharing

http://resolver.tudelft.nl/uuid:b1eb14ea-aca3-4124-b05c-c055931af54e

https://doi.org/10.1016/j.trc.2021.103061

0968-090X

Transportation Research. Part C: Emerging Technologies, 126

Institutional Repository

journal article

© 2021 Andres Fielbaum, X. Bai, J. Alonso-Mora