Modeling and evaluation of a ridesharing matching system from multi‐stakeholders’ perspective

Rahman, Md Tawhidur; Dey, Kakan; Martinelli, Dante Pinheiro; Mishra, Sabyasachee

doi:10.1049/itr2.12060

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…One key challenge to offering ridesharing services is how to assign passengers' requests for rides to vehicles and redefine vehicles' routes in an optimal manner. Thus, most studies focus on making scheduling plans for vehicles of a certain scale by designing optimal algorithms [21,22]. A mixed integer model is proposed to formulate the problem of assignments and routes in ridesharing services.…”

Section: Ridesharingmentioning

confidence: 99%

Passenger‐perception dynamic ridesharing service based on parallel technology

Xue

Song

et al. 2023

IET Intelligent Trans Sys

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With the emergence of new information and communication technology, mobile‐based ridesharing services have received more attention and have improved. They offer timely and convenient service and exert an enormous influence on pollution and congestion by allowing passengers to share overlapping routes. However, ridesharing services have also been discussed and called into question by people with respect to their attractiveness, their comfort, and passenger safety. This paper proposes a ridesharing algorithm with a perceived mechanism by introducing multiple dimensions of perceived value to overall assess passengers’ perceptions. The approach involved can continuously track the psychological changes in passengers during travel, capture the dynamic and comprehensive perceptions of passengers, and make real‐time adjustments on this basis. Furthermore, the proposed partition‐based parallel strategy can ensure high‐quality services and further enhance computational efficiency. Finally, numerical experiments are conducted based on the urban transportation network and the actual trip data from Manhattan to evaluate the performance of the proposed algorithm. The results show that it is important to effectively capture the passengers’ perception of ridesharing services and apply them to optimization mechanisms, which will contribute to improving the perception of ride experiences and attracting potential passengers.

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Section: Ridesharingmentioning

confidence: 99%