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Two-Dimensional Collision Risk Prediction for Intelligent Vehicles Considering the Influence of Heterogeneous Vehicle Types
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Jialiang Zhu1, Qiaobin Liu1, Fan Yang1, Lu Yang2, Weihua Li1
Automotive Engineering | 2024, 46(8) : 1414 - 1421
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Automotive Engineering | 2024, 46(8): 1414-1421
Two-Dimensional Collision Risk Prediction for Intelligent Vehicles Considering the Influence of Heterogeneous Vehicle Types
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Jialiang Zhu1, Qiaobin Liu1, Fan Yang1, Lu Yang2, Weihua Li1
Affiliations
  • 1. School of Mechanical & Automotive Engineering，South China University of Technology，Guangzhou 　510641
  • 2. School of Mechanical Engineering，Beijing Institute of Technology，Beijing 　100081
Published: 2024-08-25 doi: 10.19562/j.chinasae.qcgc.2024.08.008
Outline
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Accurate prediction of collision risk is crucial for ensuring the driving safety of intelligent vehicles. However， the risk differentiation among heterogeneity vehicle types and its coupled effect in longitudinal and lateral directions has rarely been considered in existing driving risk assessment methods. Therefore， firstly， the behavior patterns of drivers of heterogeneous vehicle types are explored to analyze the influence of vehicle types on drivers' sensitivity to risk in this paper. Secondly， the heterogeneous risk thresholds for different combinations of vehicle types are identified， and the risk differentiation in such traffic surroundings is further quantified based on two-dimensional indicators. Finally， the coupled two-dimensional collision risk prediction model considering vehicle types is proposed， and the effectiveness of the model is validated through comparative analysis. This research helps to enhance the driving safety of intelligent vehicles， which also can provide a theoretical foundation for the development of collision warning systems for human-driven vehicles.

traffic safety  /  intelligent vehicles  /  heterogeneous vehicle types  /  collision risk prediction
Jialiang Zhu, Qiaobin Liu, Fan Yang, Lu Yang, Weihua Li. Two-Dimensional Collision Risk Prediction for Intelligent Vehicles Considering the Influence of Heterogeneous Vehicle Types[J]. Automotive Engineering, 2024 , 46 (8) : 1414 -1421 . DOI: 10.19562/j.chinasae.qcgc.2024.08.008
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Year 2024 volume 46 Issue 8
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Article Info
doi: 10.19562/j.chinasae.qcgc.2024.08.008
  • Receive Date：2024-02-07
  • Online Date：2025-07-29
  • Published：2024-08-25
Article Data
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History
  • Received：2024-02-07
  • Revised：2024-03-30
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    1. School of Mechanical & Automotive Engineering，South China University of Technology，Guangzhou 　510641
    2. School of Mechanical Engineering，Beijing Institute of Technology，Beijing 　100081
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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