Large-scale Online Ridesharing: The Effect of Assignment Optimality on System Performance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00364463" target="_blank" >RIV/68407700:21230/22:00364463 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1080/15472450.2022.2121651" target="_blank" >https://doi.org/10.1080/15472450.2022.2121651</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/15472450.2022.2121651" target="_blank" >10.1080/15472450.2022.2121651</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Large-scale Online Ridesharing: The Effect of Assignment Optimality on System Performance

Popis výsledku v původním jazyce

Mobility-on-demand (MoD) systems consist of a fleet of shared vehicles that can be hailed for one-way point-to-point trips. The total distance driven by the vehicles and the fleet size can be reduced by employing ridesharing, i.e., by assigning multiple passengers to one vehicle. However, finding the optimal passenger-vehicle assignment in an MoD system is a hard combinatorial problem. In this work, we demonstrate how the VGA method, a recently proposed systematic method for ridesharing, can be used to compute the optimal passenger-vehicle assignments and corresponding vehicle routes in a massive-scale MoD system. In contrast to existing works, we solve all passenger-vehicle assignment problems to optimality, regularly dealing with instances containing thousands of vehicles and passengers. Moreover, to examine the impact of using optimal ridesharing assignments, we compare the performance of an MoD system that uses optimal assignments against an MoD system that uses assignments computed using insertion heuristic and against an MoD system that uses no ridesharing. We found that the system that uses optimal ridesharing assignments subject to the maximum travel delay of 4 minutes reduces the vehicle distance driven by 57% compared to an MoD system without ridesharing. Furthermore, we found that the optimal assignments result in a 20% reduction in vehicle distance driven and 5% lower average passenger travel delay compared to a system that uses insertion heuristic.

Název v anglickém jazyce

Large-scale Online Ridesharing: The Effect of Assignment Optimality on System Performance

Popis výsledku anglicky

Mobility-on-demand (MoD) systems consist of a fleet of shared vehicles that can be hailed for one-way point-to-point trips. The total distance driven by the vehicles and the fleet size can be reduced by employing ridesharing, i.e., by assigning multiple passengers to one vehicle. However, finding the optimal passenger-vehicle assignment in an MoD system is a hard combinatorial problem. In this work, we demonstrate how the VGA method, a recently proposed systematic method for ridesharing, can be used to compute the optimal passenger-vehicle assignments and corresponding vehicle routes in a massive-scale MoD system. In contrast to existing works, we solve all passenger-vehicle assignment problems to optimality, regularly dealing with instances containing thousands of vehicles and passengers. Moreover, to examine the impact of using optimal ridesharing assignments, we compare the performance of an MoD system that uses optimal assignments against an MoD system that uses assignments computed using insertion heuristic and against an MoD system that uses no ridesharing. We found that the system that uses optimal ridesharing assignments subject to the maximum travel delay of 4 minutes reduces the vehicle distance driven by 57% compared to an MoD system without ridesharing. Furthermore, we found that the optimal assignments result in a 20% reduction in vehicle distance driven and 5% lower average passenger travel delay compared to a system that uses insertion heuristic.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Intelligent Transportation Systems

ISSN

1547-2450

e-ISSN

1547-2442

Svazek periodika

28

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

22

Strana od-do

189-210

Kód UT WoS článku

000894280500001

EID výsledku v databázi Scopus

2-s2.0-85143292722