Safety, Mobility, and Environmental Impacts of Driver-Assistance-Enabled Electric Vehicles: An Empirical Study
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866914277142560768 |
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| author | Geffen, Gabriel Zhao, Jun Shang, Mingfeng Wang, Shian Wu, Yao-Jan |
| author_facet | Geffen, Gabriel Zhao, Jun Shang, Mingfeng Wang, Shian Wu, Yao-Jan |
| contents | The advancement of vehicle automation and the growing adoption of electric vehicles (EVs) are reshaping transportation systems. While fully automated vehicles are expected to improve traffic stability, efficiency, and sustainability, recent studies suggest that partially automated vehicles, such as those equipped with adaptive cruise control (ACC), may adversely affect traffic flow. These drawbacks may not extend to ACC-enabled EVs due to their distinct mechanical characteristics, including regenerative braking and smoother torque delivery. As a result, the impacts of EVs operating under ACC remain insufficiently understood.
To address this gap, this study develops an empirical framework using the OpenACC dataset to compare ACC-enabled EVs and internal combustion engine vehicles. Dynamic time warping aligns comparable lead-vehicle trajectories. Results show that EVs exhibit smoother speed profiles, lower speed variability, and shorter spacing, leading to higher efficiency. EVs reduce critical safety events by over 85% and lower platoon-level emissions by up to 26.2%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_17256 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Safety, Mobility, and Environmental Impacts of Driver-Assistance-Enabled Electric Vehicles: An Empirical Study Geffen, Gabriel Zhao, Jun Shang, Mingfeng Wang, Shian Wu, Yao-Jan Emerging Technologies Applications The advancement of vehicle automation and the growing adoption of electric vehicles (EVs) are reshaping transportation systems. While fully automated vehicles are expected to improve traffic stability, efficiency, and sustainability, recent studies suggest that partially automated vehicles, such as those equipped with adaptive cruise control (ACC), may adversely affect traffic flow. These drawbacks may not extend to ACC-enabled EVs due to their distinct mechanical characteristics, including regenerative braking and smoother torque delivery. As a result, the impacts of EVs operating under ACC remain insufficiently understood. To address this gap, this study develops an empirical framework using the OpenACC dataset to compare ACC-enabled EVs and internal combustion engine vehicles. Dynamic time warping aligns comparable lead-vehicle trajectories. Results show that EVs exhibit smoother speed profiles, lower speed variability, and shorter spacing, leading to higher efficiency. EVs reduce critical safety events by over 85% and lower platoon-level emissions by up to 26.2%. |
| title | Safety, Mobility, and Environmental Impacts of Driver-Assistance-Enabled Electric Vehicles: An Empirical Study |
| topic | Emerging Technologies Applications |
| url | https://arxiv.org/abs/2601.17256 |