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A Rideshare Model based on Movement Patterns
Nhan T.H. Vu,Manh V. Tran 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
Public transportation enable people to share vehicles have been achieved a lot of attentions from transportation authorities in solving traffic problems thanks to great potential it brings without having to spend money on improving the road network. However public travel mode often requires multiple transfers and detours and is unable to provide door-to-door services. Rideshare model introduced in this paper is able to address such issues. This research especially focuses on finding people who have regular frequent routes to recommend ride shares so that they can travel costs.
A System for Rideshare Service
Manh V. Tran,Nhan T.H. Vu 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
Normally people perform frequent activities like leaving home for work and coming back on a daily basis and those who have similar routes can share a ride. Till now many ride-on-demand systems supporting rideshare function have been developed, however many fail to find a trip matching for passengers and the seating capacity is not utilized to the maximum extent because users need to be serviced in timely manner. Especially, users who have the same travel demand still have to send the ride requests every single time they use services. In this paper, we implement a static rideshare system to address mentioned problems by applying a matching mechanism based on spatial and temporal constraints, called spatiotemporal constraints to optimally match rides with rideshare requests while meeting the service quality guarantee. The users who have regular routines are enabled to send the requests in advance. Owing to the opportunity for rideshare depend on the problem if the users stay in the proximity, we apply the spatial clustering technique along with temporal constraint to form the shared groups. Thanks to this technique the communication requirements for processing rideshare requests in the system is limited.