山区高速公路车辆行驶状态监测及预警方法分析-analysis of monitoring and early warning methods for vehicle driving state of mountainous expressway.docx
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山区高速公路车辆行驶状态监测及预警方法分析-analysis of monitoring and early warning methods for vehicle driving state of mountainous expressway
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摘 要
随着我国高速公路的快速发展,特别是山区高速公路通车里程的迅速增长,但随之 而来的安全问题也越来越突出。山区高速公路线形和平原区高速公路有较大差异,且事 故后果较为严重。了解驾驶人在不同道路线形条件下的驾驶特性和行为,对车辆的行驶 状态进行监测,并对危险行驶状态及时预警,从而可以有效地预防交通事故的发生。因 此,研究山区高速公路驾驶人车速控制特性,实现车辆行驶状态监测及预警,对于改善 车辆的行驶安全性具有重要意义。
本研究对西汉高速公路秦岭段车速进行实地采集,运用卡尔曼算法对车速数据进行 滤波处理,分析了车辆在自由流状态下的加速度变化特性,并提出了车辆自由流状态的 甄别方法;根据试验数据分析了车辆在山区高速公路不同线形及其组合条件下的车速特 性;提出了一种基于神经网络的山区高速公路车辆行驶状态监测的方法,建立山区高速 公路驾驶人车速控制行为学习模型,经验证其误差在 6%以内,表明该方法能够很好地 适用于山区高速公路驾驶人车速控制行为学习;结合所建立的模型,对该方法在自适应 巡航系统和预警方面的应用进行了研究。
本研究得到国家自然科学基金项目和中央高校基本科研业务费专项资 金项目(CHD2012ZD018)的联合资助。
关键词:山区高速公路,车速,道路线形,神经网络,状态监测,预警
Abstract
With the rapid development of Chinas freeway, mountainous freeway mileage has rapidly improved, but the attendant security issues more accident.Owning a high accident rate, mountainous freeway was significantly different from those of other highway. Learn driving behavior on different road conditions, monitors the status of the vehicle, when the vehicle speed is greater than the critical security monitoring speed, the pre-warning system, which can effectively prevent traffic accidents. Meanwhile, the study on the adaptive cruise control system can also be (ACC) provide the basis for the ACC development.Therefore, the study on speed variation and the behavior of driver control characteristics is necessary. Cruise control and pre-warning system is able to great improvement the vehicle safety.
This study collected the speed on Xi-Han freeway of Qinling. Use Kalman theory to deal with the speed data. Study the characteristics of the vehicle in free flow, and classifyied the speed data. Based on the speed data analysed the vehicles variation. Establish the road model for acceleration speed. Combined with the speed variation and its influencing factors, based on the test data established the method of combining the use of neural networks and Markov freeway highway curve segment speed prediction model, and the model is validated, the results show that this method can be applicablespeed highway
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