The Benefits of Meeting Points in Ride-Sharing Systems

Stiglic, Mitja; Agatz, Niels; Savelsbergh, Martin; Gradišar, Miro

doi:10.2139/ssrn.2567274

Cited by 55 publications

(91 citation statements)

References 14 publications

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“…To guarantee a certain service level to the riders, the ride-share service provider could use (a small number of) dedicated drivers to serve riders that would otherwise remain unmatched. Lee and Savelsbergh (2015)…”

Section: Doan Et Al (2011))mentioning

confidence: 99%

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Crowdsourced Delivery—A Dynamic Pickup and Delivery Problem with Ad Hoc Drivers

Arslan

Agatz

Kroon

et al. 2019

Transportation Science

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342

166

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The trend towards shorter delivery lead-times reduces operational efficiency and increases transportation costs for internet retailers. Mobile technology, however, creates new opportunities to organize the last-mile. In this paper, we study the concept of crowdsourced delivery that aims to use excess capacity on journeys that already take place to make deliveries. We consider a peer-to-peer platform that automatically creates matches between parcel delivery tasks and ad-hoc drivers. The platform also operates a fleet of backup vehicles to serve the tasks that cannot be served by the ad-hoc drivers. The matching of tasks, drivers and backup vehicles gives rise to a new variant of the dynamic pickup and delivery problem. We propose a rolling horizon framework and develop an exact solution approach to solve the various subproblems. In order to investigate the potential benefit of crowdsourced delivery, we conduct a wide range of computational experiments. The experiments provide insights into the viability of crowdsourced delivery under various assumptions about the environment and the behavior of the ad-hoc drivers. The results suggest that the use of ad-hoc drivers has the potential to make the last-mile more cost-efficient and can reduce the system-wide vehicle-miles.

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Section: Doan Et Al (2011))mentioning

confidence: 99%

“…As in Stiglic et al (2015), we can model this problem as a matching problem with sideconstraints. Let D = K ∪ B denote the set of all drivers, i.e.…”

Section: Offline Problem Formulationmentioning

confidence: 99%

Crowdsourced Delivery—A Dynamic Pickup and Delivery Problem with Ad Hoc Drivers

Arslan

Agatz

Kroon

et al. 2019

Transportation Science

Self Cite

342

166

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show abstract

“…In Stiglic et al [2015], we do not require door-to-door transportation but allow riders to walk to and from meeting points to facilitate more convenient rides for the drivers. Here, we extend this work by also allowing transfers to a transit service with a fixed schedule.…”

Section: Literaturementioning

confidence: 99%

“…As in Stiglic et al [2015], we create a node for each driver i ∈ D and each rider j ∈ R and an edge connecting node i and j if there is a feasible match between driver i and rider j. We also introduce nodes that represent pairs of riders ( j, k), where j, k ∈ R and j = k. We add an edge connecting node i and ( j, k) if there is a feasible match between driver i and rider pair ( j, k).…”

Section: The Matching Problemmentioning

confidence: 99%

Enhancing Urban Mobility: Integrating Ride-Sharing and Public Transit

2016

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Seamless integration of ride-sharing and public transit may offer fast, reliable, and affordable transfer to and from transit stations in suburban areas thereby enhancing mobility of residents. We investigate the potential benefits of such a system, as well as the ride-matching technology required to support it, by means of an extensive computational study. 1 Introduction People all around the world use private cars to travel to work. Most of these commuter trips are singleoccupant vehicle trips. In the U.S., for example, single-occupant trips represent approximately 77% of all commuter trips [Polzin and Pisarski, 2013]; similar percentages are found in Europe [European Environment Agency, 2010]. The low vehicle occupancy rates combined with the high number of trips during peak-hours often leads to severe traffic congestion in urban areas. The resulting stress and air pollution, caused by vehicle emissions, can have serious negative health effects. To reduce the negative externalities of car travel, local governments encourage the use of public transit. Unfortunately, many suburban and rural areas are not adequately served as they lack the population density to justify public transit, i.e., the public transit is not economically viable. In cities with sprawling suburban areas, the utilization of public transit to commute to work is often low, e.g., less than 5% in metropolitan areas like Houston and Atlanta [McKenzie, 2010]. To attract more riders from suburban areas to public transit, transportation agencies must find adequate solutions to accommodate the first and last mile from the riders' home to and from the transit stations. Possible solutions for a transportation agency include operating a fleet of demand-responsive feeder vehicles

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“…Ridesharing has received substantial attention from the research community over the last few years. In particular, Agatz et al [1] formalize the ridesharing problem in a dynamic setting and propose several optimization techniques to solve it, Bit-Monnot et al [6] introduce 2SP-SP, the two-synchronization points shortest path problem to determine the optimal meeting points (pick-up and dropoff locations), Stiglic et al [24,25] demonstrate that a reasonable increase in flexibility, in terms of desired departure and transit times and locations, results in a significant improvement of the overall performance of ridesharing services (e.g., matching rate).…”

mentioning

confidence: 99%

SRide

Aïvodji

Huguenin²,

Huguet

et al. 2018

Proceedings of the 11th ACM Conference on Security &Amp; Privacy in Wireless and Mobile Networks

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Ridesharing, in which drivers offer to share their rides, allows reduction of travel costs for both drivers and riders; such practice is increasingly popular. Modern ridesharing systems, enhanced with location-based features, have improved user experience by enabling drivers and riders to arrange a trip in near real time. However, the fine-grained nature of location data collected by the service providers and exchanged between users raises privacy issues that could disrupt the adoption of such systems. In this paper, we present SRide: a privacy-preserving protocol for ridesharing that addresses the matching problem for dynamic ridesharing systems. We design and implement a prototype of SRide that operates in four steps. First, it generalizes users spatiotemporal data of users. Next, it relies on a secure filtering protocol to compute feasible matches. Then, it uses an improved version of Priv-2SP-SPa privacy-preserving protocol to compute meeting points for ridesharing-to compute a ridesharing score for each feasible pair. Finally, it computes the optimal assignment of drivers and riders based on their ridesharing scores. We conduct an experimental trace-driven evaluation of the proposed scheme to demonstrate its practical feasibility.

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The Benefits of Meeting Points in Ride-Sharing Systems

Cited by 55 publications

References 14 publications

Crowdsourced Delivery—A Dynamic Pickup and Delivery Problem with Ad Hoc Drivers

Crowdsourced Delivery—A Dynamic Pickup and Delivery Problem with Ad Hoc Drivers

Enhancing Urban Mobility: Integrating Ride-Sharing and Public Transit

SRide

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