Traffic Data Evaluation for Automated Driving Handover Scenarios

Eugenia Rykova, Eugenia Rykova, Juri Golanov, Jonas Vogt, Daniel Rau, Horst Wieker

2023

Abstract

At the current stage of automated vehicle development, the control handover from the system to a human driver (and back) is inevitable. It is essential to distinguish between situations in which the handover is possible and in which it could be dangerous and is therefore highly undesirable. We evaluated traffic situations based on two modalities: own vehicle state and traffic objects. To assess the former, supervised machine learning was applied, reaching an accuracy of 80.3% and specificity of 77.8% with Multilayer perceptron Classification. Traffic objects data were subject to different clustering techniques. The final grouping was done according to manually elaborated rules, resulting in a range of situation complexity scores. Improving the discriminative power of vehicle state classification, including driver’s state and weather information, and predicting situation complexity are to be addressed in future research.

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Paper Citation


in Harvard Style

Rykova E., Golanov J., Vogt J., Rau D. and Wieker H. (2023). Traffic Data Evaluation for Automated Driving Handover Scenarios. In Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-652-1, SciTePress, pages 125-134. DOI: 10.5220/0011599900003479


in Bibtex Style

@conference{vehits23,
author={Eugenia Rykova and Juri Golanov and Jonas Vogt and Daniel Rau and Horst Wieker},
title={Traffic Data Evaluation for Automated Driving Handover Scenarios},
booktitle={Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2023},
pages={125-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011599900003479},
isbn={978-989-758-652-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Traffic Data Evaluation for Automated Driving Handover Scenarios
SN - 978-989-758-652-1
AU - Rykova E.
AU - Golanov J.
AU - Vogt J.
AU - Rau D.
AU - Wieker H.
PY - 2023
SP - 125
EP - 134
DO - 10.5220/0011599900003479
PB - SciTePress