Abstract

Background Surging acceptance of adaptive cruise control (ACC) across the globe is further escalating concerns over its energy impact. Two questions have directed much of this project: how to distinguish ACC driving behaviour from that of the human driver and how to identify the ACC energy impact. As opposed to simulations or test-track experiments as described in previous studies, this work is unique because it was performed in real-world car-following scenarios with a variety of vehicle specifications, propulsion systems, drivers, and road and traffic conditions. Methods Tractive energy consumption serves as the energy impact indicator, ruling out the effect of the propulsion system. To further isolate the driving behaviour as the only possible contributor to tractive energy differences, two techniques are offered to normalize heterogeneous vehicle specifications and road and traffic conditions. Finally, ACC driving behaviour is compared with that of the human driver from transient and statistical perspectives. Its impact on tractive energy consumption is then evaluated from individual and platoon perspectives. Results Our data suggest that unlike human drivers, ACC followers lead to string instability. Their inability to absorb the speed overshoots may partly be explained by their high responsiveness from a control theory perspective. Statistical results might imply the followers in the automated or mixed traffic flow generally perform worse in reproducing the driving style of the preceding vehicle. On the individual level, ACC followers have tractive energy consumption 2.7 – 20.5 % higher than those of human counterparts. On the platoon level, the tractive energy values of ACC followers tend to consecutively increase (11.2 – 17.3 %). Conclusions In general, therefore, ACC impacts negatively on tractive energy efficiency. This research provides a feasible path for evaluating the energy impact of ACC in real-world applications. Moreover, the findings have significant implications for ACC safety design when handling the stability-responsiveness trade-off.

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The different versions of the original document can be found in:

https://doaj.org/toc/1867-0717,
https://doaj.org/toc/1866-8887 under the license cc-by
http://link.springer.com/article/10.1186/s12544-020-00407-9/fulltext.html,
http://dx.doi.org/10.1186/s12544-020-00407-9
https://etrr.springeropen.com/track/pdf/10.1186/s12544-020-00407-9,
https://link.springer.com/article/10.1186/s12544-020-00407-9,
https://publications.jrc.ec.europa.eu/repository/handle/JRC120109,
https://link.springer.com/content/pdf/10.1186/s12544-020-00407-9.pdf,
https://academic.microsoft.com/#/detail/3021484354 under the license https://creativecommons.org/licenses/by/4.0



DOIS: 10.3929/ethz-b-000420711 10.1186/s12544-020-00407-9

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Published on 01/01/2020

Volume 2020, 2020
DOI: 10.3929/ethz-b-000420711
Licence: Other

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