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Dynamic Guidance of an Autonomous Vehicle with Spatio-Temporal GIS

机译:时空GIS的自动驾驶汽车动态制导

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Most of computer-vision systems for vehicle guidance are tuned for highway scenarios. Developing autonomous or driver-assistance systems for complex urban traffic pose new algorithmic and system architecture challenges. This paper introduces a novel system that uses Spatio-Temporal GIS principles and a new traffic determination algorithm. The prototype system can be used as a part of autonomous vehicles controlling structure with analytical capabilities. For these purposes, predicting vehicle motion is done through trajectories. The trajectories are generated using spatial and aspatial information in GIS environment. Then, vehicle is navigated by GPS and a fuzzy logic map matching is used to locate the vehicle position on the map. Traffic congestion algorithm, which passed through 82.5% of evaluations cases successfully, is performed by vehicle's velocity in the third step. Finally, heuristic real-time route finding algorithm is used for dynamic updating of planned vehicle trajectory. Furthermore, the system is open so that further extensions such as controlling autonomous vehicle for avoiding or leaving the banned regions are possible.
机译:用于车辆导航的大多数计算机视觉系统都针对高速公路场景进行了调整。为复杂的城市交通开发自主或驾驶员辅助系统提出了新的算法和系统架构挑战。本文介绍了一种使用时空GIS原理的新颖系统和一种新的交通确定算法。该原型系统可以用作具有分析功能的自动驾驶汽车控制结构的一部分。为此,通过轨迹来预测车辆运动。轨迹是在GIS环境中使用空间和空间信息生成的。然后,通过GPS导航车辆,并使用模糊逻辑地图匹配在地图上定位车辆位置。在第三步中,通过车辆速度执行交通拥堵算法,该算法成功通过了82.5%的评估案例。最后,将启发式实时路线查找算法用于计划车辆轨迹的动态更新。此外,该系统是开放的,从而可以进行进一步的扩展,例如控制自动驾驶汽车以避开或离开禁区。

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