Multiagent Sensor Fusion for Connected & Autonomous Vehicles to Enhance Navigation Safety
Multiagent Sensor Fusion for Connected & Autonomous Vehicles to Enhance Navigation Safety
复制标题
多智能体传感器融合互联
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
J. Dolan
中科院分区：
文献类型：
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作者：
Suryansh Saxena;Isaac K. Isukapati;Stephen F. Smith;J. Dolan
如今，自动驾驶汽车（AV）导航系统仅依靠本地传感器数据馈送来实现安全可靠的导航。然而，传感器数据包含导致错误预测的错误测量并不罕见，分类为假阳性（预测不存在的障碍）或假阴性（例如，错过障碍）。在本文中，我们提出了一种方法来识别和减少自动驾驶汽车导航中的假阴性，因为这些可以说是最危险的。根据该方法，每个自治代理同时定位和绘制其局部环境。这张地图被编码成低分辨率的信息，并通过DSRC（一种无线车辆通信协议）与附近的代理共享。接下来，智能体将这些信息分散地融合在一起，以构建一个世界解释。然后，每个智能体根据对共同感兴趣区域的世界解释，统计分析自己的解释。提出的统计算法输出本地和世界解释之间的相似性度量，并为本地代理识别假阴性（如果有的话）。这一措施，反过来，可以用来通知代理更新他们的运动学行为，以解释任何错误在局部解释。仿真显示了该方法在解决假阴性方面的有效性。
Today, autonomous vehicle (AV) navigation systems rely solely on local sensor data feed for safe & reliable navigation. However, it is not uncommon for sensor data to contain erroneous measurements resulting in false predictions, classified as either false positives (predict non-existent obstacle) or false negatives (e.g., missed obstacle). In this paper, we propose a methodology to identify and minimize false negatives in autonomous vehicle navigation, since these are arguably the most dangerous. According to the methodology, each autonomous agent simultaneously localizes and maps its local environment. This map, in turn, is encoded into a low-resolution message and shared with nearby agents via DSRC, a wireless vehicle communication protocol. Next, the agents distributively fuse this information together to construct a world interpretation. Each agent then statistically analyzes its own interpretation with respect to the world interpretation for the common regions of interest. The proposed statistical algorithm outputs a measure of similarity between local and world interpretations and identifies false negatives (if any) for the local agent. This measure, in turn, can be used to inform the agents to update their kinematic behavior in order to account for any errors in local interpretation. The efficacy of this methodology in resolving false negatives is shown in simulation.