A validated failure behavior model for driver behavior models for generating skid-scenarios on motorways

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

Event location: Modena IT

ISBN: 9783030395117

DOI: 10.1007/978-3-030-39512-4_15

Abstract

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.

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How to cite

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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