Distributed Ride-Matching for Shared Ridehailing Service with Intelligent City Infrastructure
Abstract
High computational time is one of the most important operational issues in centralized dynamic shared ridehailing services. To resolve this issue, we propose a distributed ride-matching system that is based on vehicle to infrastructure (V2I) and infrastructure to infrastructure (I2I) communication. The application on downtown Toronto road network demonstrated that the distributed system resulted in a speed-up of 125 times in terms of computational time and showed high scalability. Moreover, the service rate in the proposed system improved by 7% compared to the centralized. However, the centralized system showed 29% and 17% improvement in wait time and detour time, respectively.
- Publication:
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arXiv e-prints
- Pub Date:
- February 2022
- DOI:
- arXiv:
- arXiv:2202.01121
- Bibcode:
- 2022arXiv220201121M
- Keywords:
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- Computer Science - Distributed;
- Parallel;
- and Cluster Computing;
- Mathematics - Optimization and Control
- E-Print:
- cite as: Meshkani, S.M., Farooq, B. (2022, September). Distributed Ride-Matching for Shared Ridehailing Service with Intelligent City Infrastructure. In 2022 IEEE International Smart Cities Conference (ISC2) (pp 1-6). 2022.