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.

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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
Controls
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article

Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing

Xiqun Chen, Jintao Ke, Wang Chen
6 citations
Transportmetrica B Transport Dynamics
Transportation and Mobility Innovations
1.22
article

Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing

Xiqun Chen, Jintao Ke, Wang Chen
article en
6 citations

Abstract

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.

Transportmetrica B Transport DynamicsVol. 12(1)
Zhejiang University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 21%
Transportation and Mobility Innovations
1.22
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