Department of Civil & Environmental Engineering, College of Engineering and Applied Engineering, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.
Center for Environment & Water, Research Institute, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.
Int J Environ Res Public Health. 2021 May 23;18(11):5567. doi: 10.3390/ijerph18115567.
The potential effects of autonomous vehicles (AVs) on greenhouse gas (GHG) emissions are uncertain, although numerous studies have been conducted to evaluate the impact. This paper aims to synthesize and review all the literature regarding the topic in a systematic manner to eliminate the bias and provide an overall insight, while incorporating some statistical analysis to provide an interval estimate of these studies. This paper addressed the effect of the positive and negative impacts reported in the literature in two categories of AVs: partial automation and full automation. The positive impacts represented in AVs' possibility to reduce GHG emission can be attributed to some factors, including eco-driving, eco traffic signal, platooning, and less hunting for parking. The increase in vehicle mile travel (VMT) due to (i) modal shift to AVs by captive passengers, including elderly and disabled people and (ii) easier travel compared to other modes will contribute to raising the GHG emissions. The result shows that eco-driving and platooning have the most significant contribution to reducing GHG emissions by 35%. On the other side, easier travel and faster travel significantly contribute to the increase of GHG emissions by 41.24%. Study findings reveal that the positive emission changes may not be realized at a lower AV penetration rate, where the maximum emission reduction might take place within 60-80% of AV penetration into the network.
自动驾驶汽车 (AVs) 对温室气体 (GHG) 排放的潜在影响尚不确定,尽管已经有许多研究评估了这一影响。本文旨在以系统的方式综合和回顾所有关于该主题的文献,以消除偏差并提供全面的见解,同时进行一些统计分析,为这些研究提供区间估计。本文针对文献中报告的自动驾驶汽车的积极和消极影响进行了分类:部分自动化和完全自动化。自动驾驶汽车减少 GHG 排放的可能性所带来的积极影响可以归因于一些因素,包括生态驾驶、生态交通信号、车队行驶和减少寻找停车位。由于 (i) 受监管的乘客(包括老年人和残疾人)向自动驾驶汽车转移模式和 (ii) 与其他模式相比更容易出行,导致车辆行驶里程 (VMT) 增加,这将导致 GHG 排放增加。研究结果表明,生态驾驶和车队行驶对减少 GHG 排放的贡献最大,可减少 35%。另一方面,更轻松的旅行和更快的旅行显著导致 GHG 排放增加 41.24%。研究结果表明,在较低的自动驾驶汽车渗透率下,积极的排放变化可能不会实现,在自动驾驶汽车渗透率达到 60-80%时,最大的减排可能发生。