A persuasive real-time carpooling service in a smart city: A case-study to measure the advantages in urban area

Mallus, Matteo; Colistra, Giuseppe; Atzori, Luigi; Murroni, Maurizio; Pilloni, Virginia

doi:10.1109/icin.2017.7899428

Cited by 6 publications

(1 citation statement)

References 22 publications

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“…Zhang et al [9] proposed a win-win carpool fare model to encourage both drivers and passengers to participate in carpooling. Li et al [17] proposed a dynamic pricing method and divide the payoffs according to the contribution of each individual. However, all the above studies cannot guarantee the quality of experience (QoE) of passengers.…”

Section: Introductionmentioning

confidence: 99%

Coalitional Game Based Carpooling Algorithms for Quality of Experience

Huang

Chen

2018

2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS)

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Carpooling service is an effective solution to balance the limited number of taxicabs and the soaring demands from users. Thus, how to motivate more passengers to participate in carpooling is essential, especially in extreme weather or in rush hours. Most of existing works focus on improving the availability, convenience and security of carpooling service, while ignoring to guarantee the quality of experience (QoE) of passengers. In this work, we focus on how to fulfill the expected sojourn time of passengers in carpooling service using coalition game.We formulate the QoE-guarantee problem as a benefit allocation problem. To solve the problem, we quantify the impatience of passengers due to detouring time delay, depending on their own expected sojourn time and expected compensation per unit time of delay. The algorithm named PCA is proposed to minimize the impatience of all passengers, under which we calculate the compensation for passengers based on Shapley value. We prove that PCA can guarantee the fairness of passengers. Extensive simulation results demonstrate that PCA can minimize the impatience of passengers. Moreover, compared with the existing algorithm DST, PCA can reduce the payment of each passenger by 14.4% averagely with only 13.3% loss of driver's revenue. However, the least expected revenue of the driver can still be fulfilled, which produces a win-win solution for both passengers and drivers in carpooling.

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Section: Introductionmentioning

confidence: 99%

Coalitional Game Based Carpooling Algorithms for Quality of Experience

Huang

Chen

2018

2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS)

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Information Technology Solutions and Challenges for Healthy Urban Environment

Lemeš

2021

Lecture Notes in Networks and Systems

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A web-based multiple criteria decision support system for evaluation analysis of carpooling

Petrillo

Carotenuto

Baffo

et al. 2017

Environ Dev Sustain

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Several researches in the scientific, industrial and commercial fields are supporting the reduction of traditional combustion carsâ\u80\u99 use. The main purpose is to increase the quality of life into the metropolitan cities through the reduction of CO2 emissions and global warming. Accordingly, one of the most successful models is the carpooling system. Currently, people are investigating the sustainability and durability of carpooling business model from both economic and organizational point of view. The present research aims to develop a Multicriteria Decision Support System (MDSS) in order to offer a carpooling systemâ\u80\u99s platform based on different criteria. The MDSS is developed from driverâ\u80\u99s point of view and settled on two levels of optimization. Firstly, a genetic algorithm is proposed to solve an orienteering problem that optimizes the total revenue of driver based on the carâ\u80\u99s capability and the time schedule. Secondly, the best optimization solutions are compared with multicriteria analysis respect to other criteria not included in the first optimization. The outcome of MDSS is a schedule for drivers, which gives maximum satisfaction in terms of profitability, punctuality and comfort of the travel

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A persuasive real-time carpooling service in a smart city: A case-study to measure the advantages in urban area

Cited by 6 publications

References 22 publications

Coalitional Game Based Carpooling Algorithms for Quality of Experience

Coalitional Game Based Carpooling Algorithms for Quality of Experience

Information Technology Solutions and Challenges for Healthy Urban Environment

A web-based multiple criteria decision support system for evaluation analysis of carpooling

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