首页> 外文会议>Autonomic and Autonomous Systems, 2009. ICAS '09 >Particle Filters for an Accurate Localization of Communicant Vehicles
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Particle Filters for an Accurate Localization of Communicant Vehicles

机译:粒子过滤器可精确定位战车

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This paper presents an accurate localization strategy for vehicles in urban environments by using the communication between vehicles and the vision systems when GPS data is unavailable or has a poor quality of signal due to multi-tracks or bad satellite visibility. The new generation of the advanced driver assistance systems (ADAS systems) based on cooperation between vehicles can offer serious perspectives to the road security. The inter-vehicle cooperation is made possible thanks to the revolution in the wireless mobile ad hoc network. The method relies on the Monte Carlo Method or what we call a particle filter for the treatment of the GPS data and the vision data that will be collected from the loading system in the vehicles. From the modelling point of view, a particularity of the method is due to the use of vision systems and the communication through a wireless communication devices. The experiments on our fleet of communicating vehicles carried out in real conditions prove the feasibility of this approach.
机译:当GPS数据不可用或由于多轨或卫星能见度差而信号质量差时,本文通过使用车辆与视觉系统之间的通信,为城市环境中的车辆提供了一种精确的定位策略。基于车辆之间合作的新一代高级驾驶员辅助系统(ADAS系统)可以为道路安全提供严肃的视角。得益于无线移动自组织网络的革命,车辆之间的合作成为可能。该方法依赖于蒙特卡洛方法或所谓的粒子过滤器,用于处理将从车辆装载系统中收集的GPS数据和视觉数据。从建模的角度来看,该方法的特殊性归因于视觉系统的使用和通过无线通信设备的通信。在实际条件下对我们的通信车辆进行的实验证明了这种方法的可行性。

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