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Acquisition of Relative Trajectories of Surrounding Vehicles using GPS and DSRC based V2V Communication with Lane Level Resolution

机译:基于GPS和DSRC与车道水平分辨率的V2V通信获取周围车辆的相对轨迹

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Due to the anticipated benefits of connected vehicle technology, the Intelligent Transportation Systems Joint Program Office (ITSJPO) of the US Department of Transportation continues to emphasize the need for dedicated short range communication (DSRC) based vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure (V2I) communication to enhance driver safety and traffic mobility. To take full advantage of connected vehicle technology in most safety applications, precise vehicle positioning information is needed in addition to V2V communication. Many techniques, such as vision- or sensor-based systems and differential GPS receivers, can obtain the precise absolute position of a vehicle at the expense of cost and complexity. However, some critical safety applications such as merge-assist or lane-change-assist systems require only the relative positions of surrounding vehicles with lane-level resolution so that a given vehicle can differentiate the vehicles in its own lane from the vehicles in adjacent lanes. We have adopted a simple approach to acquire accurate relative trajectories of surrounding vehicles using standard GPS receivers and DSRC-based V2V communication. Using this approach, we have conducted field tests to successfully acquire relative trajectories of vehicles traveling in multiple lanes towards a merging junction with an accuracy less than half of the lane width. The achieved accuracy level of the relative trajectory was sufficient to differentiate vehicles traveling in adjacent lanes of a multiple-lane freeway.
机译:由于连接车辆技术的预期益处,美国交通部的智能交通系统联合计划办公室(ITSJPO)继续强调基于基于车辆到车辆的专用短程通信(DSRC)和/或车辆到基础设施(V2I)通信,以提高驾驶员安全和流动流动性。为了充分利用连接的车辆技术在大多数安全应用中,除了V2V通信之外,还需要精确的车辆定位信息。许多技术,例如基于视觉或传感器的系统和差分GPS接收器,可以以成本和复杂性为代价获得车辆的精确绝对位置。然而,诸如合并辅助或车道变化辅助系统的一些关键安全应用仅需要具有车道级分辨率的周围车辆的相对位置,使得给定的车辆可以将车辆与相邻车道中的车辆区分开。我们采用了一种简单的方法,使用标准GPS接收器和基于DSRC的V2V通信来获取周围车辆的准确相对轨迹。使用这种方法,我们已经进行了现场测试,以成功地获取在多个车道中行驶的车辆的相对轨迹,以精度小于车道宽度的一半。所实现的相对轨迹的精度水平足以区分在多车道高速公路的相邻车道中行进的车辆。

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