TY - JOUR
T1 - On-demand ridesharing with optimized pick-up and drop-off walking locations
AU - Fielbaum, Andres
AU - Bai, Xiaoshan
AU - Alonso-Mora, Javier
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - On-demand
KW - Pick-up and drop-off points
KW - Ridepooling
KW - Ridesharing
UR - http://www.scopus.com/inward/record.url?scp=85102360187&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2021.103061
DO - 10.1016/j.trc.2021.103061
M3 - Article
AN - SCOPUS:85102360187
SN - 0968-090X
VL - 126
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 103061
ER -