Evaluation of Take-Over Request Lead Time Based on Driving Behavioral Interaction Between Autonomous Vehicles and Manual Vehiclesopen access
- Authors
- Ko, Jieun; Oh, Cheol; Kim, Hoseon; Kang, Kyeongpyo; Kim, Seoungbum
- Issue Date
- Nov-2025
- Publisher
- MDPI
- Keywords
- autonomous vehicles; take-over request lead time; driving behavioral interaction; multi-agent driving simulator; multi-criteria decision-making
- Citation
- Applied Sciences-basel, v.15, no.23
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences-basel
- Volume
- 15
- Number
- 23
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/81633
- DOI
- 10.3390/app152312512
- ISSN
- 2076-3417
- Abstract
- Autonomous vehicles (AVs) at SAE Levels 3 require a take-over request to switch from autonomous to manual mode when leaving the operational design domain (ODD). An appropriate take-over request lead time (TORlt) is necessary for safe interaction between AVs and non-AVs. This study developed a methodology to derive the optimal TORlt for AVs entering the area out of the ODD using a multi-agent driving simulator experiment. The multi-criteria decision-making method was adopted to integrate evaluation indicators to derive an optimal TORlt. The TORlt was defined as 3, 6, 9, 12, and 15 s in the driving simulation experiment scenario. The driving simulation experiment was conducted with a total of 60 participants. The simulation network was a two-lane urban road in each direction with a total length of 1.7 km, including a school zone where the autonomous driving mode is prohibited. Three requirements were established to determine the optimal TORlt: minimizing the take-over time, maximizing the success rate of take-over, and minimizing the potential of rear-end collisions due to vehicle interactions. After conducting comparative analyses of individual evaluation indicators for each scenario, a multi-criteria decision-making method was used for integrated evaluation to determine the optimal TORlt. It was found that the optimal TORlt for AVs on urban roads is 9 s. The results of this study can be used as valuable fundamentals in determining take-over requests for AVs toward safer vehicle interactions in the traffic stream.
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