Lane recognition for moving vehicles using multiple on-car RFID receiver antennas — Algorithm and its experimental results

H. Togashi, C. Borcea, S. Yamada
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引用次数: 6

Abstract

Accurate lane recognition for moving vehicles is important for lane keeping and lane changing assistance systems. Additionally, this information could be leveraged by Intelligent Transportation Systems to suggest lane changes for improved traffic load balancing across lanes. This paper presents a position estimation algorithm for moving vehicles based on RFID (Radio Frequency Identification) active sensors placed on roadsides and lane boundaries, and multiple on-car RFID receiver antennas. To improve localization accuracy, the algorithm proposes two novel ideas: (1) compute pair-wise position estimates using the RSSI (Received Signal Strength Indication) of all pairs of signals received from RFIDs, and (2) compute the final position as a weighted average of these pair-wise estimates using a dynamic weighting function that assigns higher weights to positions estimated based on closer RFIDs. The results from our field experiments indicate that the proposed method achieves 0.7-meter localization accuracy when RFIDs are placed at 0.5-meter intervals and a vehicle has 8 antennas. This accuracy allows a moving vehicle to recognize which lane it is in. The localization accuracy of the proposed method was found to be mostly stable for any type of road shape and any number of lanes. A further 14% accuracy improvement is achieved when RFIDs are placed at 0.25-meter intervals and the RFIDs located farther than 30-meter are excluded from computation.
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基于车载RFID接收天线的移动车辆车道识别算法及实验结果
对移动车辆进行准确的车道识别对于车道保持和变道辅助系统至关重要。此外,智能交通系统可以利用这些信息来建议变道,以改善车道间的交通负载平衡。本文提出了一种基于放置在路边和车道边界的RFID(射频识别)有源传感器和车载多个RFID接收天线的移动车辆位置估计算法。为了提高定位精度,该算法提出了两个新思路:(1)使用从rfid接收到的所有对信号的RSSI(接收信号强度指示)计算成对的位置估计,(2)使用动态加权函数计算最终位置作为这些成对估计的加权平均值,该函数为基于更近的rfid估计的位置分配更高的权重。现场实验结果表明,当rfid以0.5米的间隔放置,车辆有8个天线时,所提出的方法可以达到0.7米的定位精度。这种精度允许移动的车辆识别它在哪个车道上。结果表明,该方法在任何道路形状和车道数量下定位精度基本稳定。当rfid以0.25米的间隔放置时,进一步提高了14%的精度,并且将距离超过30米的rfid排除在计算之外。
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