Empirical evaluation of a dynamic and distributed taxi-sharing system

d’Orey, Pedro M.; Fernandes, Ricardo; Ferreira, Michel

doi:10.1109/itsc.2012.6338703

Cited by 68 publications

(22 citation statements)

References 7 publications

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“…Tao [17] used each customer's choice for the maximum acceptable number of sharing customers and acceptable gender as inputs to an algorithm, which then selects the taxi that is able to reach the customer's location most rapidly to provide the service. Orey et al [18] proposed that a customer request be sent to all taxis or a subset of taxis and each taxi would respond with its cost associated with the trip to the customer. The customer would then determine the acceptable lowest cost for taxi sharing and choose a taxi to use.…”

Section: Literature Reviewmentioning

confidence: 99%

Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

Liu

Miwa

Zeng

et al. 2018

Journal of Advanced Transportation

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Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios-one based on historical traffic information and the other based on real-time traffic information-were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.

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Section: Literature Reviewmentioning

confidence: 99%

Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

Liu

Miwa

Zeng

et al. 2018

Journal of Advanced Transportation

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“…d'Orey [46] presents a taxi sharing algorithm with two parts, namely a customer algorithm and a taxi algorithm. The customer algorithm receives user-defined parameters such as ride time or distance and sends the information to a selected range of taxis.…”

Section: Categories and Examples Of Ridesharing Systemsmentioning

confidence: 99%

A Partition-Based Match Making Algorithm for Dynamic Ridesharing

Pelzer¹,

Xiao²,

Zehe³

et al. 2015

IEEE Trans. Intell. Transport. Syst.

112

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Abstract-Ridesharing offers the opportunity to make more efficient use of vehicles while preserving the benefits of individual mobility. Presenting ridesharing as a viable option for commuters, however, requires minimizing certain inconvenience factors. One of these factors includes detours which result from picking up and dropping off additional passengers. This paper proposes a method which aims to best utilize ridesharing potential while keeping detours below a specific limit. The method specifically targets ridesharing systems on a very large scale and with a high degree of dynamics which are difficult to address using classical approaches known from operations research. For this purpose, the road network is divided into distinct partitions which define the search space for ride matches. The size and shape of the partitions depend on the topology of the road network as well as on two free parameters. This allows optimizing the partitioning with regard to sharing potential utilization and inconvenience minimization. Match making is ultimately performed using an agent-based approach. As a case study, the algorithm is applied to investigate the potential for taxi sharing in Singapore. This is done by considering about 110 000 daily trips and allowing up to two sharing partners. The outcome shows that the number of trips could be reduced by 42% resulting in a daily mileage savings of 230 000 km. It is further shown that the presented approach exceeds the mileage savings achieved by a greedy heuristic by 6% while requiring 30% lower computational efforts.

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“…Domestic structures and international institutions have done some research about the carpooling service [3][4][5]. Many scholars begin to study mobile phone-based carpooling service software.…”

Section: Related Workmentioning

confidence: 99%

Social Group Architecture Based Distributed Ride-Sharing Service in VANET

Zhao

Qin

Yang

et al. 2014

International Journal of Distributed Sensor Networks

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Lots of traditional distributed ride-sharing services match vehicles with drivers and passengers geographic information only. When urban road congestion situation is particularly serious, such as Beijing's rush hour, the waiting time for the passengers is too long which affects the quality of the service. So we propose a distributed ride-sharing service based on dual Social Group Architecture (SGA). We divide the service into Drivers Social Group Architecture (DSGA) message and Vehicles Social Group Architecture (VSGA) message. Vehicles generate dual SGA messages to complete ride-sharing service. DSGA messages focus on the relation between drivers and passengers. We make a basic geometry matching by generating the DSGA messages. VSGA messages figure out the traffic conditions through a multilevel detection. After generating VSGA messages, the final matching strategy is processed. The low level detection is finished by the limited neighbors to decrease the network consume. Dual SGA messages shorten the waiting time for the passengers and avoid traffic jams. Analysis shows that our scheme enhances the ride-sharing service quality and robust.

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Empirical evaluation of a dynamic and distributed taxi-sharing system

Cited by 68 publications

References 7 publications

Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information

A Partition-Based Match Making Algorithm for Dynamic Ridesharing

Social Group Architecture Based Distributed Ride-Sharing Service in VANET

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