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• W2968782003 abstract "This paper presents the results of a Carbon Footprint (CF) study of Autonomous Vehicles (AVs) and their environmental impact on the transportation network. By assuming that fully AVs are battery electric vehicles (BEVs) with connectivity, light detection and ranging sensors, this study measures the environmental impact at the urban mobility level. The AV complete life cycle impact was firstly evaluated. Next, by comparing the current situation with a future hypothetical scenario (100% AVs penetration), the positive environmental effect of the adoption of AVs on a real road network (city of Rome) is shown. For this scope, a traffic simulation-based approach was used to investigate the effects of AVs on the network congestion. The results show that the full AVs penetration scenario leads to an improvement in the network performances in terms of travel time and average speed. The Total Time Spent (TTS) decreases (−35% for intra-urban roads and −21% for highways), and the average network speed increases (48% for intra-urban road and 37% for highways). Moreover, the final amount of Vehicle Kilometer Traveled (VKT) shows an 8% increase on longer extra-urban routes, due to the higher capacity impact of AVs on highways, with a consequent load reduction for intra-urban shortcutting routes. In terms of life cycle impacts, AVs are characterized by the highest Greenhouse Gases (GHG) emissions related to construction, maintenance and end-of-life processes (on average 35% compared to internal combustion engine vehicles, 22% compared to hybrid electric vehicles and 5% compared to battery electric vehicles). Nevertheless, a 100% AVs penetration scenario generates a reduction of the environmental impact at the mobility system level of about 60%." @default.
• W2968782003 created "2019-08-22" @default.
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• W2968782003 date "2019-09-01" @default.
• W2968782003 modified "2023-10-11" @default.
• W2968782003 title "Carbon Footprint of autonomous vehicles at the urban mobility system level: A traffic simulation-based approach" @default.
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• W2968782003 doi "https://doi.org/10.1016/j.trd.2019.08.007" @default.
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