Abstract

With low-level vehicle automation already available, there is a necessity to estimate its effects on traffic flow, especially if these could be negative. A long gradual transition will occur from manual driving to automated driving, in which many yet unknown traffic flow dynamics will be present. These effects have the potential to increasingly aid or cripple current road networks. In this contribution, we investigate these effects using an empirically calibrated and validated simulation experiment, backed up with findings from literature. We found that low-level automated vehicles in mixed traffic will initially have a small negative effect on traffic flow and road capacities. The experiment further showed that any improvement in traffic flow will only be seen at penetration rates above 70%. Also, the capacity drop appeared to be slightly higher with the presence of low-level automated vehicles. The experiment further investigated the effect of bottleneck severity and truck shares on traffic flow. Improvements to current traffic models are recommended and should include a greater detail and understanding of driver-vehicle interaction, both in conventional and in mixed traffic flow. Further research into behavioural shifts in driving is also recommended due to limited data and knowledge of these dynamics.

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http://downloads.hindawi.com/journals/jat/2017/3082781.xml,
http://dx.doi.org/10.1155/2017/3082781
http://resolver.tudelft.nl/uuid:9c70c190-742d-44aa-b4b4-2b8849343990 under the license http://creativecommons.org/licenses/by/4.0/
https://doaj.org/toc/0197-6729,
https://doaj.org/toc/2042-3195
http://downloads.hindawi.com/journals/jat/2017/3082781.pdf,
https://www.narcis.nl/publication/RecordID/oai%3Atudelft.nl%3Auuid%3A9c70c190-742d-44aa-b4b4-2b8849343990,
https://repository.tudelft.nl/islandora/object/uuid:9c70c190-742d-44aa-b4b4-2b8849343990/datastream/OBJ/download,
https://core.ac.uk/display/87536312,
https://academic.microsoft.com/#/detail/2756577398
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Published on 01/01/2017

Volume 2017, 2017
DOI: 10.1155/2017/3082781
Licence: Other

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