使用车对车通信的预期变道警告

Nigel Williams, Guoyuan Wu, K. Boriboonsomsin, M. Barth, Samer A. Rajab, Sue Bai
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引用次数: 7

摘要

传统的变道预警和自动变道系统使用车载传感器(如摄像头、雷达和超声波传感器)检测其他车辆。随着互联汽车(CV)技术的出现,无线通信(例如专用短程通信或DSRC)成为“感知”周围车辆的另一种选择。特别是,DSRC没有测距传感器的视线限制,因此可以“看到”前方更远的交通,这使得它能够很好地预测附近车辆的移动。我们已经开发了一种算法,该算法使用这些数据来预测期望的变道是否会导致不安全的情况,并在这种情况下阻止变道。在微观交通模拟器VISSIM中使用高速公路网络对其有效性进行了评估,该高速公路网络已根据高峰时段交通数据进行了很好的校准。使用代理安全评估模型(SSAM)在各种交通场景(不同拥堵程度、联网车辆普及率和应用装备车辆)下评估系统在安全方面的性能。初步测试表明,该算法可将潜在交通冲突的数量减少多达30%,交通量越大,配备应用程序的车辆比例越高,减少的幅度就越大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anticipatory Lane Change Warning using Vehicle-to-Vehicle Communications
Conventional lane change warning and automated lane changing systems detect other vehicles using on-board sensors such as camera, radar, and ultrasonic sensors. With the advent of Connected Vehicle (CV) technology, wireless communication (e.g, Dedicated Short Range Communications, or DSRC) becomes another option for “sensing” surrounding vehicles. In particular, DSRC does not have the line-of-sight limitation of ranging sensors and thus can “see” traffic farther ahead, which lends itself well to anticipating the movements of nearby vehicles. We have developed an algorithm that uses such data to predict whether a desired lane change will result in an unsafe situation, and prevents the lane change if that is the case. The effectiveness was evaluated in the microscopic traffic simulator VISSIM using a freeway network that has been well calibrated with rush hour traffic data. System performance in terms of safety was estimated using the Surrogate Safety Assessment Model (SSAM) under a variety of traffic scenarios (different congestion levels, penetration rates of connected vehicles and application-equipped vehicles). Preliminary tests showed that the proposed algorithm can reduce the number of potential traffic conflicts by up to 30%, with higher reductions at higher traffic volumes and higher percentages of application-equipped vehicles.
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