Abstract
Ignoring the complicated traffic condition and limited field-of-view at unsignalized intersection leave us a major challenge on preventing potential collision scenarios. This paper proposed a novel rule-based graded brake mechanism for intersection collision avoidance (ICA), using simulator-based techniques for combining the two-vehicle collision model and an automatic braking system. In particular, vehicle-to-vehicle communication was employed to ensure real-time interaction between the driving states of two vehicles, i.e., object vehicle and ego vehicle that identified as the controlled agent. Additionally, the intersection collision warning (ICW) threshold based on time to collision (TTC) was presented to warn in advance while a crash is determined. Collision scenario was constructed in PreScan simulation platform, and experimental results show the feasibility of the proposed method, and the two-stage braking strategy might accomplish stable and reliable performance for ICA.
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Acknowledgment
This work was supported in part by Projects of the National Science Foundation of China (41971340, 41471333, 61304199), project 2017A13025 of Science and Technology Development Center, Ministry of Education, project 2018Y3001 of Fujian Provincial Department of Science and Technology, projects of Fujian Provincial Department of Education (JA14209, JA15325, FBJG20180049).
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Chen, B., Liao, L., Zou, F., Zheng, Y. (2020). Rule-Based Graded Braking for Unsignalized Intersection Collision Avoidance via Vehicle-to-Vehicle Communication. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_16
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DOI: https://doi.org/10.1007/978-981-15-3308-2_16
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