Activity-Based Shared Mobility Model for Smart Transportation
Abstract
The shared mobility model of transportation services in cities has gained significant attention due to the proliferation of on-demand ride-sharing applications and the advancement of autonomous driving technologies. In this paper, a new shared mobility model is proposed accommodating the activity attribute of users' trip requests. Our key goal is to determine the minimum fleet size required to satisfy all on-demand requests while minimizing the total travel costs. Since this is an NP-hard problem, the model leverages a set of novel heuristic-based components including the clustering-based formation of ride-sharing groups, carpool-like schedule and ridesharing schedule generation, and clique-based trip integration. All work together to obtain the set of energy-efficient shared route schedules. The proposed model can also be extended for a heterogeneous vehicle fleet configuration (e.g. vehicles of various capacity and functionality) to work for different types of trip activities.
Recommended Citation
S. Yeung et al., "Activity-Based Shared Mobility Model for Smart Transportation," Proceedings of the 20th IEEE International Conference on Mobile Data Management (2019, Hong Kong), Institute of Electrical and Electronics Engineers (IEEE), Jun 2019.
The definitive version is available at https://doi.org/10.1109/MDM.2019.00126
Meeting Name
20th IEEE International Conference on Mobile Data Management, MDM (2019: Jun. 10-13, Hong Kong)
Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Second Research Center/Lab
Center for High Performance Computing Research
Keywords and Phrases
Shared Mobility; Trip Planning; Ride-Sharing
International Standard Book Number (ISBN)
978-1-7281-3363-8
International Standard Serial Number (ISSN)
2375-0324
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
13 Jun 2019