Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing
Despite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooked the relationship between traffic volume and the degree of traffic congestion and emissions. To address these gaps, this study develops an open-source agent-based simulation platform and a heuristic algorithm to quantify the benefits of high-capacity ride-sharing with significantly lower computational costs. The simulation platform integrates a traffic emission model and a speed-density traffic flow model to characterise the interactions between traffic congestion levels and emissions. The experiment results demonstrate that ride-sharing with vehicle capacities of 2, 4, and 6 passengers can alleviate total traffic congestion by approximately 3%, 4%, and 5%, and reduce traffic emissions of a ride-sourcing system by approximately 30%, 45%, and 50%, respectively. This study can guide transportation network companies in designing and managing more efficient and environment-friendly mobility systems.
Authors
- Xiqun Chen (ORCID: https://orcid.org/0000-0001-8285-084X)
- Jintao Ke (ORCID: https://orcid.org/0000-0001-9778-3387)
- Wang Chen (ORCID: https://orcid.org/0009-0007-7298-4191)
Institutions
- Zhejiang University (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Transportmetrica B Transport Dynamics
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1080/21680566.2024.2423235
- Citations
- 6
- Primary Topic
- Transportation and Mobility Innovations
- Type
- article
- Field-Weighted Citation Impact
- 1.22