Cooperative localization based on topology matching

Seung-Tak Choi, Woo-Sol Hur, S. Seo
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引用次数: 9

Abstract

In this paper, we propose a new vehicle localization method based on topology matching in mutli-vehicle enviroment. Each vehicle is assumed to generate a local map which is a set of position measurements of nearby vehicles by using onboard low-cost GPS and ranging sensors, and share it with others by broadcasting via vehicle-to-vehicle(V2V) communication. When a vehicle receives multiple local maps from neighbors, it incorporates and fuses them with its own local map by using a local map matching algorithm. The proposed algorithm is based on the topology matching technique and the multi-sensor Kalman filter. Simulation results show that our method can extend the detection range and improve the position accuracy by 65% compared to conventional localization methods utilizing the Kalman filter with only onboard GPS measurements.
基于拓扑匹配的协同定位
本文提出了一种基于拓扑匹配的多车环境下的车辆定位方法。假设每辆车都使用车载低成本GPS和测距传感器生成一组本地地图,这是一组附近车辆的位置测量数据,并通过车对车(V2V)通信广播与其他车辆共享。当一辆汽车从邻居那里接收到多个本地地图时,它会使用本地地图匹配算法将它们与自己的本地地图进行合并和融合。该算法基于拓扑匹配技术和多传感器卡尔曼滤波。仿真结果表明,与仅使用车载GPS测量值的传统卡尔曼滤波定位方法相比,该方法可以扩大探测范围,提高定位精度65%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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