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Vehicle crash mitigation strategy in unavoidable collision scenarios: focusing on motion planning by considering a generalized crash severity model

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Abstract

Driving strategy in dynamic environment is crucial to the automated vehicle safety. In extremely emergency scenarios with unavoidable collision (UC), especially those with complex impact patterns, the potential crash risk should be well considered. This paper proposes a crash mitigation (CM) algorithm for UCs, which directly embeds a generalized crash severity index (CSI) model to vehicle-to-vehicle collisions of multiple impact patterns. The idea is that during the short time before a collision, the vehicle will actively adapt its position and poses to minimize the potential crash severity level after the collision. To this end, the generalized CSI model is introduced to estimate the potential crash severity of all sample paths, from which a crash-severity-optimal trajectory is obtained. To improve the inferring time efficiency of the planning module, a neural network is constructed and deployed to approximate the nonlinear severity model. The proposed algorithm is first validated through simulations of UC scenarios, including entry ramp merging, intersection crossing and downhill/uphill crossing. Then for the intersection crossing scenario, the algorithm is deployed to a real car and validated through digital-twin experiments. Results show that by combining the braking and steering interventions for better crash severity reduction, the proposed strategy can achieve better mitigation effects than commonly used collision avoidance (CA) strategies. This reveals that a new mindset of comprehensive safety strategy should not focus only on CA, but also the last resort of CM if collision is unavoidable. Our work may contribute as a promising solution to the safety problem in emergency scenarios.

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Abbreviations

AI:

Artificial intelligence

ADAS:

Advanced driving assist system

AEB:

Automated emergency braking

AES:

Automated emergency steering

C.G:

Center of gravity

CA:

Collision avoidance

CM:

Crash mitigation

CMI:

Crash momentum index

CSI:

Crash severity index

DOF:

Degrees of freedom

EES:

Equivalent energy speed

FEM:

Finite element method

IPC:

Industrial personal computer

MPC:

Model predictive control

PDOF:

Principal direction of force

POI:

Point of impact

TTC:

Time to collision

UC:

Unavoidable collision

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Authors and Affiliations

  1. Institute of Power Machinery and Vehicular Engineering, Zhejiang University, NO 38 Zheda Road, Xihu District, Hangzhou, 310027, Zhejiang, China

    Daofei Li, Jiajie Zhang, Bin Xiao, Binbin Tang & Zhaohan Hu

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  1. Daofei Li
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  3. Bin Xiao
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  4. Binbin Tang
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Correspondence to Daofei Li.

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Author Contributions

Daofei Li and Zhaohan Hu contributed to the study conception and design. Vehicle modelling, crash severity modelling and planning algorithm were performed by Daofei Li and Zhaohan Hu. Control algorithm and simulation was done by Zhaohan Hu and Bin Xiao. Experiments, data collection and analysis were performed by Daofei Li, Zhaohan Hu, Jiajie Zhang and Bin Xiao. The first draft of the manuscript was written by Daofei Li and Zhaohan Hu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Department of Science and Technology of Zhejiang (No. 2022C01241).

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The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Tecnical Editor: Rogério Sales Gonçalves.

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Li, D., Zhang, J., Xiao, B. et al. Vehicle crash mitigation strategy in unavoidable collision scenarios: focusing on motion planning by considering a generalized crash severity model. J Braz. Soc. Mech. Sci. Eng. 44, 581 (2022). https://doi.org/10.1007/s40430-022-03893-1

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