Chapter
Aug 31, 2020
International Conference on Transportation and Development 2020

Investigating the Impact of Driving Style on the Take-Over Performance in Level 3 Automation

Publication: International Conference on Transportation and Development 2020

ABSTRACT

Various daily driving habits and styles may be the reason why drivers show individual differences when taking over. The purpose of this paper is to investigate the impact of driving style on take-over performance in Level 3 automation. The simulator experiments in this study consisted of two parts: a manual car-following experiment and an automated driving take-over experiment. In the manual car-following experiment, researchers used the data of maximum braking deceleration, and maximum acceleration to classify 20 participants into two driving types (12 normal drivers, 8 aggressive drivers). Then the automated driving take-over experiment was conducted to investigate the influence of driving styles (normal, aggressive) on take-over performance in different take-over time budgets (7 and 5 s) and in combination with a visual secondary task. The researchers found that normal drivers took a significant severer brake than aggressive drivers only in the condition of 5 s take-over time budget + SuRT (i.e., the most urgent of all conditions). In addition, the driving style had no significant influences on take-over time, minimum TTC, and maximum lateral acceleration. Results indicate that normal drivers’ good habits do not make their take-over performance better, while the experience of aggressive drivers in manual emergency driving makes their emergency evasive maneuvers more stable in automated take-over.

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Go to International Conference on Transportation and Development 2020
International Conference on Transportation and Development 2020
Pages: 146 - 156
Editor: Guohui Zhang, Ph.D., University of Hawaii
ISBN (Online): 978-0-7844-8314-5

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Published online: Aug 31, 2020
Published in print: Aug 31, 2020

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Facheng Chen [email protected]
1Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China. Email: [email protected]
Guangquan Lu [email protected]
2Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang Univ., Beijing, China. Email: [email protected]
3Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China. Email: [email protected]
Haitian Tan [email protected]
4Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China. Email: [email protected]

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