城市地下智能交通汽车侧方距离精确提示方法
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摘要
为了避免交通事故的发生,降低交通事故造成的损失,需要对汽车侧方距离提示方法进行研究。采用当前汽车侧方距离提示方法对城市地下智能交通汽车进行距离提示时,测得的车辆相对速度不准确、不能有效的对驾驶员进行距离提示,存在精准度低和有效性差的问题。提出一种城市地下智能交通汽车侧方距离精确提示方法,在侧方汽车静止和侧方汽车行驶两种状况下构建相应的安全距离估算模型和最小安全车距控制模型。以车辆之间的相对距离和相对速度为提示判断参数,构建分级提示策略,完成地下城市智能交通汽车侧方距离的提示。实验结果表明,所提方法可精准的测得车辆之间的相对速度,有效的对驾驶员发出距离提示,验证所提方法的精准度高、有效性高。
In order to avoid the occurrence of traffic accidents and reduce the loss caused by traffic accidents,it is necessary to study the method of car side distance prompting.When using the current vehicle side distance prompting method to prompt the distance of the urban underground intelligent transportation vehicle,the measured relative speed of the vehicle is inaccurate,and the driver cannot promptly perform the distance prompt,which has the problems of low accuracy and poor validity.A method for accurately recognizing the lateral distance of urban underground intelligent traffic vehicles is proposed.The corresponding safety distance estimation model and the minimum safe distance control model are constructed under the conditions of side stationary car and side car driving.The relative distance and relative speed between the vehicles are used as indicators for judging the parameters,and a hierarchical cueing strategy is constructed to complete the side-to-side distance of the intelligent traffic vehicle in the underground city.The experimental results show that the proposed method can accurately measure the relative speed between vehicles and effectively send distance hints to the driver,verifying that the proposed method has high accuracy and high effectiveness.
In order to avoid the occurrence of traffic accidents and reduce the loss caused by traffic accidents,it is necessary to study the method of car side distance prompting.When using the current vehicle side distance prompting method to prompt the distance of the urban underground intelligent transportation vehicle,the measured relative speed of the vehicle is inaccurate,and the driver cannot promptly perform the distance prompt,which has the problems of low accuracy and poor validity.A method for accurately recognizing the lateral distance of urban underground intelligent traffic vehicles is proposed.The corresponding safety distance estimation model and the minimum safe distance control model are constructed under the conditions of side stationary car and side car driving.The relative distance and relative speed between the vehicles are used as indicators for judging the parameters,and a hierarchical cueing strategy is constructed to complete the side-to-side distance of the intelligent traffic vehicle in the underground city.The experimental results show that the proposed method can accurately measure the relative speed between vehicles and effectively send distance hints to the driver,verifying that the proposed method has high accuracy and high effectiveness.
引文
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[2] 王萍,刘京茂.激光成像的汽车安全距离自动检测系统[J].激光杂志,2017,38(7):68-71.
[3] 钱立军,赵明宇,张卫国.一种电动汽车充电安全预警模型设计方法[J].电网与清洁能源,2016,32(12):114-119.
[4] 柴琳果,蔡伯根,王化深,等.车联网关键指标对车辆安全影响仿真测试方法[J].汽车工程,2017,39(11):1316-1324.
[5] 赵树恩,屈贤,李玉玲.基于人车环境协同的车辆弯道行驶安全预警系统[J].北京工业大学学报,2016,42(1):112-118.
[6] 杨刚,张东好,李克强,等.基于车车通信的车辆并行协同自动换道控制[J].公路交通科技,2017,34(1):120-129.
[7] 刘庆华,邱修林,谢礼猛,等.基于行驶车速的车辆防撞时间预警算法[J].农业工程学报,2017,33(12):99-106.
[8] 章军辉,李庆,陈大鹏.基于BP神经网络的纵向避撞安全辅助算法[J].西安交通大学学报,2017,51(7):140-147.
[9] 雷正保,易晓剑.电动汽车碰撞安全性与NVH多目标拓扑优化[J].中国公路学报,2016,29(5):144-150.
[10] 李方义,荣见华,胡林,等.基于概率-凸集混合模型的汽车正面碰撞结构可靠性优化设计[J].振动与冲击,2016,35(3):215-220.
[11] 刘守峰,胡雪芳.汽车电子控制与城市智能交通问题研究[J].中国科技投资,2016,32(17):79-87.
[12] 张岳,吴海.汽车侧方辅助安全系统设计[J].科技创新与应用,2016,42(4):2-2.
[13] 闫星培.境外城市智能交通系统建设经验及借鉴[J].汽车与安全,2017,11(5):88-93.
[14] 李文涛.汽车电子控制与城市智能交通[J].数码世界,2017,15(5):197-197.
[15] 赵鸣宇.计算机技术在智能交通系统中的应用[J].中国科技投资,2016,46(21):261-261.