Dynamic ridesharing: Is there a role for dedicated drivers?

Lee, Alan; Savelsbergh, Martin

doi:10.1016/j.trb.2015.02.013

Cited by 97 publications

(32 citation statements)

References 21 publications

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“…Uber data was available only for May through October 2014, but it was sufficient for estimating trends in the production function. Second, the number of drivers per month was a determinant of the scale of availability of the service in the region-drivers are critical for all other ridesharing affordances to be accessed (Lee & Savelsbergh 2015;O'Brien & Wattles 2016).…”

Section: Methodsmentioning

confidence: 99%

Co-producing Mobility: Lessons from Ridesharing for a More Just and Sustainable Autonomous Future

Griffin¹

2019

Preprint

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Big changes in technology create big opportunities for sustainability. Decreasing the number of cars on the road through carpooling can mitigate many problems related to transportation, including traffic congestion, emissions, and safety. Mobile information and communication technologies (ICTs) provide communicative and financial capabilities, termed affordances; to make carpooling much more convenient. However, research has yet to distinguish the role of affordances in reaching a critical mass of drivers. This chapter showcases empirical results from an in-depth study of a carpooling app, coupled with an innovative policy pilot to provide toll road discounts for carpool trips registered with the program. Results from the pilot countered with a for-profit model suggest drivers require sufficient reimbursement for travel costs and coordination time, to reach a critical mass needed to support a competitive travel option. However, recruitment tactics such as paid and organic media coverage, face-to-face events and incentives, and driver-focused outreach support growth of the carpool system registration, and use. Additional studies are needed to evaluate different combinations of ridesharing affordances and transportation policies to determine whether communities can realize the benefits of a critical mass of ICT-supported carpooling.

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Section: Methodsmentioning

confidence: 99%

Co-producing Mobility: Lessons from Ridesharing for a More Just and Sustainable Autonomous Future

Griffin¹

2019

Preprint

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“…Dynamic ride-matching includes many parameters, and this renders the problem to be non-deterministic polynomial-time hard (NP-hard) [15][16][17]. Therefore, many solutions to the ride-matching problem that have been proposed in the literature use either heuristics or metaheuristics [6,[15][16][17][18][19][20][21][22][23]. Although heuristic and meta-heuristic methods offer feasible processing times, they may not find the best possible matches.…”

Section: Related Studiesmentioning

confidence: 99%

“…A multi-hop ride-sharing system was also modeled as a binary optimization problem and the researchers introduced an algorithm to solve this problem [6]. Another study even considered employing dedicated drivers in order to achieve a satisfactory number of drivers in the start-up phase [22].…”

Section: Related Studiesmentioning

confidence: 99%

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

2020

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Increasing traffic congestion and the advancements in technology have fostered the growth of alternative transportation modes such as dynamic ride-sharing. Smartphone technologies have enabled dynamic ride-sharing to thrive, as this type of transportation aims to establish ride matches between people with similar routes and schedules on short notice. Many automated matching methods are designed to improve system performance; such methods include minimizing process time, minimizing total system cost or maximizing total distance savings. However, the results may not provide the maximum benefits for the participants. This paper intends to develop an algorithm for optimizing matches when considering participants' gender, age, employment status and social tendencies. The proposed matching algorithm also splits unmatched parts of drivers' routes and creates new travel requests to find additional matches using these unmatched parts. Accordingly, this paper performs an extensive simulation study to assess the performance of the proposed algorithm. The simulation results indicate that route splits may increase the number of matches significantly when there is a shortage of drivers. Furthermore, the paper demonstrates the effects and potential benefits of utilizing a social compatibility score in the objective function.

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“…The work in this area typically considers door-to-door trips in which a driver moves one or more riders from their origin to their destination (see for example Agatz et al [2011], Wang et al [2015], Lee and Savelsbergh [2015], and Stiglic et al [2016]). Furuhata et al [2013] and Agatz et al [2012] provide a detailed overview of this line of research and the links to other modes of transportation.…”

Section: Literaturementioning

confidence: 99%