A car sharing auction with temporal-spatial OD connection conditions

Hara, Yusuke; Hato, Eiji

doi:10.1016/j.trpro.2017.05.003

Cited by 17 publications

(11 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The literature offers a number of case studies [21][22][23] focusing on the impacts [24], travel behaviour [20,[25][26][27], comparisons of car-sharing systems [28], technical papers on how to coordinate/ manage shared mobility [29][30][31][32][33], and hypothetical uptake [34][35][36][37][38]. The research has also focused on Uber [39][40][41], probably because it has grown substantially since it started in 2009.…”

Section: Introductionmentioning

confidence: 99%

Sustainability and Shared Mobility Models

Santos

2018

Sustainability

View full text Add to dashboard Cite

Shared mobility or mobility in the sharing economy is characterised by the sharing of a vehicle instead of ownership, and the use of technology to connect users and providers. Based on a literature review, the following four emerging models are identified: (1) peer to peer provision with a company as a broker, providing a platform where individuals can rent their cars when not in use; (2) short term rental of vehicles managed and owned by a provider; (3) companies that own no cars themselves but sign up ordinary car owners as drivers; and (4) on demand private cars, vans, or buses, and other vehicles, such as big taxis, shared by passengers going in the same direction. The first three models can yield profits to private parties, but they do not seem to have potential to reduce congestion and CO2 emissions substantially. The fourth model, which entails individuals not only sharing a vehicle, but actually travelling together at the same time, is promising in terms of congestion and CO2 emissions reductions. It is also the least attractive to individuals, given the disbenefits in terms of waiting time, travel time, comfort, and convenience, in comparison with the private car. Potential incentives to encourage shared mobility are also discussed, and research needs are outlined.

show abstract

Section: Introductionmentioning

confidence: 99%

Sustainability and Shared Mobility Models

Santos

2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Lu et al [9] built a two-stage stochastic integer programming model, which was to maximize the profit of the car sharing platform. Hara and Hato [10] proposed a Vickrey Clarke Groves mechanism for a car sharing system. ey found that the negative price (or benefit) could encourage the relocation of vehicles under the auction mechanism.…”

Section: Literature Reviewmentioning

confidence: 99%

A Bi-Level Optimization Model for Ride-Sourcing Platform’s Spatial Pricing Strategy

Tang

Wang

et al. 2022

Journal of Advanced Transportation

View full text Add to dashboard Cite

This article investigates a long-term optimal spatial pricing strategy for a ride-sourcing platform that serves a particular (possibly populated) area with profit-driven service providers (i.e., drivers) and time- and price-sensitive customers (i.e., passengers). By observing that oftentimes, the price strategy is anisotropic and spatial-dependent, both the supply and request are endogenous, and we build an analytical bi-level optimization mode. In the upper-level formulation, the ride-sourcing platform aims at setting up the spatially heterogeneous pricing strategy to maximize its total profit. However, in the lower level, we solve the trip distribution model that characterizes the flow rates among zones given the travel demand rate at each zone. We prove that when the platform seeks to expand its business, the optimal number of participating drivers and their optimal wages will be influenced not only by the pricing strategy but also by the level of service of the entire platform. Our further investigation shows that the profit at a particular zone can be influenced by the potential customers’ service requests from other zones. Finally, we use the real-world data provided by DiDi Chuxing to numerically illustrate our model and theoretical results.

show abstract

“…[23] proposed a stochastic optimization framework to address the dynamic vehicle allocation problem for car sharing systems, where both temporal and spatial vehicle allocation were optimized to maximize profits. More recently, a tradable permit mechanism was proved to be computationally viable for car sharing with temporalspatial OD connection conditions [25]. Also, some works have studied the future operative systems of autonomous shared fleets [26]- [28], or their electric version [29].…”

Section: State Of the Artmentioning

confidence: 99%

The Potential of Flexible Reservations in a Car Sharing System With an Auction Scheme

Roca-Riu

Menéndez

2019

IEEE Access

View full text Add to dashboard Cite

In the last 20 years car sharing has been a growing trend in personal mobility. Multiple aspects of these systems have been already discussed: different forms of car sharing, user's preferences and behavior, or benefits estimation. Nevertheless, the management of these systems needs to be continuously improved to remain a competitive alternative. In this work, we propose a reservation scheme to manage rental reservations of a two-way station-based car sharing system. It allows the operator to better plan the necessary vehicles at each station, and encourages the drivers to make better use of the existing vehicles, by showing flexibility in the starting rental time. The reservation scheme is organized with an auction, where drivers bet for their preferred rental start time. Drivers participating in the auction are offered a reduced rental fare, which is then complemented with the reservation fee that results from the auction. The auction is solved under Vickrey-Clarke-Groves (VCG) mechanism for combinatorial auctions, which guarantees the desired properties for the operator and a fair assignment for the drivers. The proposed scheme is tested on instances inspired by the Mobility car sharing system in Zürich, Switzerland. The results show that operators could decrease their fleets with low to no impacts on the overall rental revenues, especially when drivers show flexibility in their rental start times. For certain levels of demand price elasticity, even positive impacts on the overall rental revenues can be expected. Moreover, reservation fees are proven to partially compensate for the decrease in rental revenues provided to the auction users. INDEX TERMS Car sharing, combinatorial auctions, reservation system.

show abstract

A car sharing auction with temporal-spatial OD connection conditions

Cited by 17 publications

References 23 publications

Sustainability and Shared Mobility Models

Sustainability and Shared Mobility Models

A Bi-Level Optimization Model for Ride-Sourcing Platform’s Spatial Pricing Strategy

The Potential of Flexible Reservations in a Car Sharing System With an Auction Scheme

Contact Info

Product

Resources

About