Map Matching Algorithm for the ”Spar p ̊a farten” Intelligent Speed Adaptation Project
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The availability of Global Navigation Satellite Systems (GNSS) enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as GNSS positioning are often inaccurate, a technique known as map matching is needed that aims to use this inaccurate data for determining a vehicle’s real road-network position. Then, knowing this position, an ISA system can compare speed with the speed limit in effect and take measures against speeding. This paper presents an on-line map matching algorithm with an extensive number of weighting parameters that allow better determination of a vehicle’s road network position. The algorithm uses certainty value to express its belief in the correctness of its results. The algorithm was designed and implemented to be used in the large scale ISA project ”Spar p ̊a farten” . Using test data and data collected from project participants, the algorithm’s performance is evaluated. It is shown that algorithm performs correctly 95 % of the time and is capable of handling GNSS positioning errors in a conservative manner.
全球导航卫星系统（Global Navigation Satellite Systems, GNSS）的普及，为智能速度适配（Intelligent Speed Adaptation, ISA）系统等先进的车辆导航与辅助警示系统提供了技术支撑。在ISA系统中，实现车辆在道路网络内的准确定位是一项核心要求。由于数字道路网络与GNSS定位本身均存在一定误差，因此亟需采用一种被称为地图匹配（map matching）的技术，利用这类存在误差的数据来确定车辆在真实道路网络中的位置。在此基础上，ISA系统可将车辆行驶速度与当前生效的限速标准进行比对，并针对超速行为采取应对措施。 本文提出一种具备大量加权参数的在线地图匹配算法，可实现车辆道路网络位置的精准判定。该算法采用置信度值来表达其对匹配结果正确性的置信判断。本算法专为大型ISA项目"Spar på farten"设计并实现。通过测试数据与项目参与者采集的实测数据，对该算法的性能展开了评估。评估结果表明，该算法的正确匹配率可达95%，且能够以稳健保守的方式处理GNSS定位误差。
