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Evaluation of automated vehicle behavior in intersection scenarios

Abstract : The development of automated vehicles (AVs) is ongoing and soon the first versions will enter the up to now exclusively human controlled traffic environment. In previous research, we developed an approach for an automated vehicle control in intersection scenarios. The focus was on the decision-making process to either enter the intersection before another car or wait to let the other car pass. While objective risk features were used to evaluate the performance, the interaction with real human drivers remains uncertain. Therefore, we propose a method to evaluate the automated vehicle behavior from an outside perspective by introducing a human driver and our automated vehicle in the same simulation environment. We conducted a study to examine the interaction and evaluate the automated vehicle behavior from another driver's perspective. The focus of the study was on the naturalness and risk of the behavior and how the subjective risk evaluation is linked to our main objective risk feature. For comparing the results, we used two different setups for our automated vehicle (aggressive vs. passive) and varied the starting position to create either of the two situations (AV first vs. driver first) as mentioned above. The results show a high overall naturalness score. The risk score was related to the outcome of the situation and the AV setup. A weak correlation between the subjective risk assessment and the objective risk feature indicated the necessity to evaluate automated vehicle control from an outside perspective to achieve a better assimilation in human traffic environments. Since the identification of automated vehicles can influence the driver behavior, the integration of a human-like behavior for AVs seems highly desirable.
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Contributor : Pierre de Beaucorps Connect in order to contact the contributor
Submitted on : Friday, November 10, 2017 - 11:02:20 AM
Last modification on : Wednesday, June 8, 2022 - 12:50:05 PM
Long-term archiving on: : Sunday, February 11, 2018 - 1:20:40 PM


2017-10 RSS paper final.pdf
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  • HAL Id : hal-01632434, version 1



Thomas Streubel, Pierre de Beaucorps, Fawzi Nashashibi. Evaluation of automated vehicle behavior in intersection scenarios. RSS2017 - Road Safety & Simulation International Conference, Oct 2017, The Hague, Netherlands. ⟨hal-01632434⟩



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