Evaluating economic and environmental impact of electric modular vehicles in transit system

Public transit systems with fixed-capacity electric buses (EBs) inefficiently handle fluctuating passenger demand. Automated electric modular vehicles (AEMVs), capable of capacity adjustment through coupling/decoupling, present a promising alternative. To comprehensively evaluate their economic and environmental impact, this study examines three service modes across six demand scenarios and varying automation levels: (I) AEMVs only, (II) EBs only, and (III) mixed operation. Beyond cost comparisons, we address a novel perspective of energy consumption reduction through AEMVs’ flexible capacity-demand matching capability. Results from a Zhengzhou case study demonstrate that mixed mode (III) achieves optimal cost efficiency, reducing costs by 3.3%–23.0% compared to EB mode (II) in high morning/evening peak scenarios across different automation stages. Mode (I) delivers lowest carbon emissions, with potential annual reductions of 87,000 tons across Zhengzhou’s entire bus network. However, during primary automation stages, high labor costs limit AEMVs’ viability to low-demand routes, though feasibility increases significantly as automation advances.

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Publication Details

Journal
Transportation Research Part D Transport and Environment
Published
2025-11-21
DOI
https://doi.org/10.1016/j.trd.2025.105122
Citations
1
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.68
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article

Evaluating economic and environmental impact of electric modular vehicles in transit system

Hong Gao, Kai Liu, Zhibin Chen, Jiangbo Wang
1 citations
Transportation Research Part D Transport and Environment
Transportation and Mobility Innovations
0.68
article

Evaluating economic and environmental impact of electric modular vehicles in transit system

Hong Gao, Kai Liu, Zhibin Chen, Jiangbo Wang
article en
1 citations

Abstract

Public transit systems with fixed-capacity electric buses (EBs) inefficiently handle fluctuating passenger demand. Automated electric modular vehicles (AEMVs), capable of capacity adjustment through coupling/decoupling, present a promising alternative. To comprehensively evaluate their economic and environmental impact, this study examines three service modes across six demand scenarios and varying automation levels: (I) AEMVs only, (II) EBs only, and (III) mixed operation. Beyond cost comparisons, we address a novel perspective of energy consumption reduction through AEMVs’ flexible capacity-demand matching capability. Results from a Zhengzhou case study demonstrate that mixed mode (III) achieves optimal cost efficiency, reducing costs by 3.3%–23.0% compared to EB mode (II) in high morning/evening peak scenarios across different automation stages. Mode (I) delivers lowest carbon emissions, with potential annual reductions of 87,000 tons across Zhengzhou’s entire bus network. However, during primary automation stages, high labor costs limit AEMVs’ viability to low-demand routes, though feasibility increases significantly as automation advances.

Transportation Research Part D Transport and EnvironmentVol. 150
New York University Shanghai (CN), Dalian University of Technology (CN)
Openalex Percentile: Top 23%
Transportation and Mobility Innovations
0.68
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