An Approach for Deriving Reduced Collision Scenarios for Highly Automated Driving Systems

Author:

Khatun MarzanaORCID,Litagin Heinrich,Jung Rolf,Glaß Michael

Publisher

Springer International Publishing

Reference22 articles.

1. SAE J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, commonly referenced as the SAE Levels of Driving Automation (2019)

2. SAE blog: SAE levels of driving automation refined for clarity and international audience. https://www.sae.org/blog/sae-j3016-update. Posted 3 May 2021

3. Mobility Insider: What are the levels of automated driving? https://www.aptiv.com/en/insights/article/what-are-the-levels-of-automated-driving. Aptiv. Accessed 4 Jan 2020

4. NHTSA: Automated vehicles for safety: the evolution of automated safety technologies, United States department of transportation-benefits of automation (2019)

5. Winkle, T.: Safety benefits of automated vehicles: extended findings from accident research for development, validation and testing. In: Maurer, M., Gerdes, J.C., Lenz, B., Winner, H. (eds.) Autonomous Driving, pp. 335–364. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-48847-8_17

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Safe Scenario Boundaries Determination by Parameter Variation for an Automated Driving System;2023 IEEE 11th Conference on Systems, Process & Control (ICSPC);2023-12-16

2. Scenario-based collision detection using machine learning for highly automated driving systems;Systems Science & Control Engineering;2023-01-28

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