Junietz, Philipp ; Steininger, Udo ; Winner, Hermann (2019)
Macroscopic Safety Requirements for Highly Automated Driving.
In: Transportation Research Record, 2019, 2673 (3)
Article, Secondary publication
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Macroscopic Safety Requirements for Highly Automated Driving |
Language: | English |
Date: | 2019 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2019 |
Publisher: | SAGE Publications Sage CA: Los Angeles, CA |
Journal or Publication Title: | Transportation Research Record |
Volume of the journal: | 2673 |
Issue Number: | 3 |
Corresponding Links: | |
Origin: | Secondary publication |
Abstract: | The common expectation for highly automated vehicles (HAVs) is that an introduction will lead to increased road safety and a reduction in traffic fatalities—at least in relation to the mileage. However, quantizing the safety requirements is still in discussion. This paper analyzes the risk acceptance in other fields and applies the safety level on today’s traffic to derive references for acceptable risks. The focus is on macroscopic safety requirements, meaning accident rates per mileage, and not the behavior in individual driving situations. It was concluded that the acceptable risk varies according to the group involved and with the field share of automated vehicles. Increased safety of conventional driving in the future could lead to higher requirements as well. We also point out that it is not guaranteed that the given acceptable risk levels will also accepted by the user, because factors other than the accident statistics are relevant. However, as none of these risk levels can be proven before introduction, the monitoring of vehicles in the field is suggested. Despite increased research efforts in safety validation, uncertainty surrounding the safety of HAVs will remain at the time of introduction. Different introduction and risk management strategies are briefly introduced. |
URN: | urn:nbn:de:tuda-tuprints-86569 |
Additional Information: | Copyright © 2019 National Academy of Sciences: Transportation Research Board |
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) 16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Driver Assistance 16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Test Methods |
Date Deposited: | 17 Oct 2019 12:25 |
Last Modified: | 24 May 2023 10:13 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/8656 |
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