Huber B, Schmidl P, Sippl C, Djanatliev A (2020)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2020
Publisher: Springer
Book Volume: 1131 AISC
Pages Range: 92-98
Conference Proceedings Title: International Conference on Intelligent Human Systems Integration 2020
ISBN: 9783030395117
DOI: 10.1007/978-3-030-39512-4_15
The automation of the driving task will gain importance in future mobility solutions for private transport. However, the sufficient validation of automated driving functions poses enormous challenges for academia and industry. This contribution proposes a failure behavior model for driver models for generating skid-scenarios on motorways. The model is based on results of the five-step-method provided by accident researchers. The failure behavior model is implemented using a neural network, which is trained utilizing a reinforcement learning algorithm. Hereby, the aim of the neuronal network is to maximize the vehicle’s side slip angle to initiate skidding of the vehicle. Concluding, the failure behavior model is validated by reconstructing a real accident in a traffic simulation using the failure behavior model.
APA:
Huber, B., Schmidl, P., Sippl, C., & Djanatliev, A. (2020). A validated failure behavior model for driver behavior models for generating skid-scenarios on motorways. In Tareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar (Eds.), International Conference on Intelligent Human Systems Integration 2020 (pp. 92-98). Modena, IT: Springer.
MLA:
Huber, Bernd, et al. "A validated failure behavior model for driver behavior models for generating skid-scenarios on motorways." Proceedings of the International Conference on Intelligent Human Systems Integration (IHSI 2020), Modena Ed. Tareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar, Springer, 2020. 92-98.
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