Matching algorithm for improving ride-sharing by incorporating route splits and social factors

Aydın, Ömer; Gökaşar, Ilgın; Kalan, Onur

doi:10.1371/journal.pone.0229674

Cited by 22 publications

(15 citation statements)

References 29 publications

(47 reference statements)

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“…Furthermore, the authors of [40] developed a ride-matching algorithm that splits the drivers' routes and matches riders and drivers again with an extra consideration of a Joint Socialness Score. The score involves data pertaining to the participants' gender, age, employment status and social tendencies and is used to increase the matching of riders which are in the same likelihood range.…”

Section: Heuristic and Metaheuristic Algorithms One-to-one Ridesharing Problemmentioning

confidence: 99%

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

et al. 2021

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The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world. Examples of these problems are like ridesharing, carpooling, taxisharing, buspooling, vanpooling, and multi-modal ridesharing. This is the new way to access transportation services by those who are propelling the sharing economy, where access rather than ownership is the new norm. This paper provides a systematic review of SMP using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method. A total of 110 papers from the last decade are selected from 12 abstracts and citation databases to be reviewed and classified. This is done based on the problem types, variants, characteristics, and solution approaches. The current trends and analysis of the survey findings are also summarised. From this systematic review, it is observed that both the time window and multi-objective problems are popular among the researchers, while the minimisation of the total cost is the main concern in the literature of the SMP. Both static and dynamic cases of the SMP are the most researched where heuristic and metaheuristic approaches are widely adopted by the researchers in the literature. Finally, challenges and suggestions for future work are discussed and highlighted.

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Section: Heuristic and Metaheuristic Algorithms One-to-one Ridesharing Problemmentioning

confidence: 99%

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

et al. 2021

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“…They argued that this type of matching failure could not be fixed by adjusting the compensation scheme. A matching algorithm developed by Aydin et al [21]assigned new travel requests to the unmatched distance of ridesharing drivers' routes, which improved the satisfaction levels of drivers and reported a 33% increase in matching among drivers and riders.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective

Rahman

Dey

Martinelli

et al. 2021

IET Intelligent Trans Sys

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Matching riders and drivers in ridesharing considering conflicting objectives of diverse stakeholders is challenging. The objective of this research is to formulate and evaluate the performance of four ridesharing matching-objectives (i.e. system-wide minimisation of passengers' wait time, minimisation of VMT, minimisation of detour distance, maximisation of drivers' profit) considering interests of diverse mobility stakeholders (i.e. drivers, riders, matching agencies, government transportation agencies). A grid roadway network was used to compare the performance of the four matching-objectives in serving a ridesharing demand scenario. Performance comparison of matching-objectives revealed that a systemwide VMT minimisation matching-objective performed best with least sacrifices on the other three matching-objectives from their respective best performance level. Also, systemwide VMT minimisation was the best matching-objective, when drivers' and government transportation agencies' expectations were prioritised. System-wide drivers' profit maximisation matching-objective provided the highest monetary incentives for drivers and riders in terms of maximising profit and travel cost savings, respectively. System-wide minimisation of detour distance was found to be least flexible in providing shared rides. The findings of this research provide useful insights on ridesharing matching system modelling and performance evaluation based on different matching-objectives and can be used in developing and implementing ridesharing service considering multiple stakeholders' concerns. INTRODUCTIONAccording to the 2015 Urban Mobility Scorecard, United States (US) travellers lost 7 billion hours and wasted 3 billion gallons of fuel due to traffic congestion [1]. Shared transportation modes are the emerging transportation demand management (TDM) strategies to better utilize limited transportation infrastructures and improve transportation system performance. Ridesharing, a form of shared mobility service, has been growing in popularity and has the potential to reduce emissions, fuel consumption, system-level vehicle miles travelled (VMT), and most importantly, traffic congestion [2,3]. Modern-day ridesharing services, enabled by information technology (i.e. mobile apps) face several operational challenges (e.g. efficient drivers' and riders' matching, maintaining acceptable service reliability and flexibility, integration with multimodal options, and multi-institutional collaboration) [4]. Several studies haveThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Rudnicki et al [4] studied ridesharing with walking, where the roles of drivers and passengers were known and each driver was assigned to passengers with the same destination [4,5]. Other studies [6,20] have proposed route/hop planning schemes, such as: (a) car -> car -> car; (b) car; (c) car -> airplane -> bus; (d) foot -> car -> car -> car; (e) car -> subway -> bus; (f) bicycle -> car -> bicycle; (g) foot; (h) bicycle; (i) foot -> bus -> foot. In previous studies that were completed at UC Irvine [1,7], a multimodal ridesharing system was proposed to enhance the use of the LA Metro Red Line (a subway), allowing transfers between shared-ride cars and the LA Metro.…”

Section: Multimodal Ridesharing Systemmentioning

confidence: 99%

A Study of the Factors Affecting Multimodal Ridesharing with Choice-Based Conjoint Analysis

Nam

Jayakrishnan

et al. 2021

Sustainability

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As public perception about the shared economy evolves, peer-to-peer ridesharing has been gaining increased attention worldwide. Both private and public sector entities have launched mobile app-based ridesharing services, while a range of methodologies and system architectures have been proposed in academia. Whereas traditional ridesharing methods match drivers and riders when their origin and destination are similar, recently proposed algorithms often feature multi-hop and multimodal properties that allow riders to be connected by multiple modes. Such algorithms can reduce travel time and/or travel cost; however, they may also add other travel impedances, such as requiring multiple transfers. Understanding user behavior toward such new ridesharing systems is essential for successful service design. For policymakers and service planners, identifying factors that impact traveler choices can lead to better design and improved services. This research involved a web-based survey to capture traveler preferences using a conjoint analysis framework. A choice-based method was adopted to identify factors for the estimation model and to analyze traveler willingness to pay. Among the proposed factors, the number-of-transfers was shown to be the most important, as was expected. When a multimodal ridesharing system provides less travel time, low travel cost, and sufficient ridesharing incentive, people are more likely to pay for the service.

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Matching algorithm for improving ride-sharing by incorporating route splits and social factors

Cited by 22 publications

References 29 publications

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective

A Study of the Factors Affecting Multimodal Ridesharing with Choice-Based Conjoint Analysis

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