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Model calibration concerning risk coefficients of driving safety field model

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Abstract

Driving safety field (DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver’s hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.

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Authors and Affiliations

  1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China

    Yang Li  (李洋) & Jian Wu  (吴剑)

  2. Collaborative Innovation Center of Electric Vehicles in Beijing, Tsinghua University, Beijing, 100084, China

    Jian-qiang Wang  (王建强)

Authors
  1. Yang Li  (李洋)
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  2. Jian-qiang Wang  (王建强)
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  3. Jian Wu  (吴剑)
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Corresponding author

Correspondence to Jian-qiang Wang  (王建强).

Additional information

Foundation item: Projects(51475254, 51625503) supported by the National Natural Science Foundation of China; Project(MCM20150302) supported by the Joint Project of Tsinghua and China Mobile, China; Project supported by the joint Project of Tsinghua and Daimler Greater China Ltd., Beijing, China

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Li, Y., Wang, Jq. & Wu, J. Model calibration concerning risk coefficients of driving safety field model. J. Cent. South Univ. 24, 1494–1502 (2017). https://doi.org/10.1007/s11771-017-3553-2

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  • DOI: https://doi.org/10.1007/s11771-017-3553-2

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