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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2022

Confidentiality

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

Name of the periodical

Journal of Intelligent Transportation Systems

ISSN

1547-2450

e-ISSN

1547-2442

Volume of the periodical

28

Issue of the periodical within the volume

2

Country of publishing house

GB - UNITED KINGDOM

Number of pages

22

Pages from-to

189-210

UT code for WoS article

000894280500001

EID of the result in the Scopus database

2-s2.0-85143292722