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Research on Intelligent Vehicle Collision Warning Model Based on Intervehicle Communication

机译：基于车辆间通信的智能车辆碰撞预警模型研究

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摘要

Using inter-vehicle communication, vehicle real-time traveling state information, such as acceleration, is shared, and time-to-collision and time-to-avoidance matrices are established. Considering driver type and traveling relationship between leading vehicle and following vehicle, a collision warning model based on inter-vehicle communication is studied. From aspects of inter-vehicle experiment system composition, component modules are analyzed in detail. For leading vehicle stationary, sudden deceleration, and normal traveling, three experimental schemes are proposed, and model warning performance is verified using the experiment system. Experiment results show that the algorithm model can effectively identify the collision, and precise warning rate is more than 90％. Conclusion of the study can provide a reference for research in relevant fields, such as vehicle adaptive cruise control.
机译：使用车辆间通信，共享诸如加速之类的车辆实时行驶状态信息，并建立碰撞时间和避免时间矩阵。考虑驾驶员类型和前车与后车之间的行驶关系，研究了基于车内通信的碰撞预警模型。从车载实验系统的组成方面，详细分析了组件模块。针对主导车辆的静止，突然减速和正常行驶，提出了三种实验方案，并通过实验系统验证了模型预警性能。实验结果表明，该算法模型能够有效识别碰撞，准确预警率达到90％以上。研究结论可为车辆自适应巡航控制等相关领域的研究提供参考。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第1期|208603.1-208603.7|共7页
  • 作者

    Jiangfeng Wang; Xuedong Yan; Shuo Nie; Xiaomeng Li;

  • 作者单位

    MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing 100044, China;

    MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing 100044, China;

    MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing 100044, China;

    MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing 100044, China;

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