The invention discloses a high-precision and high-expansibility method for planning an optimal traffic path. The method comprises a modeling method of a traffic network and an algorithm for solving the optimal path. The modeling method of the traffic network comprises the following steps: firstly, establishing a traffic model for analyzing the optimal traffic path, considering the influence of a signalized intersection in addition to a road, and calculating the cost of a road part according to the distance and the average traffic flow speed. Improved elite ant colony algorithm for a traffic scene is used as the algorithm for solving the optimal path. According to the improved elite ant colony algorithm, two optimizations are added during pheromone initialization and global pheromone updating. By considering the influence of the signal intersection, the accuracy of the traffic model is improved, and the solving efficiency is greatly improved through the improved elite ant colony algorithm. Meanwhile, the method can be expanded according to different signal intersection scenes and vehicle driving requirements, and therefore the method has wide application prospects in modern urban traffic and unmanned vehicle navigation.
本发明公开了一种高精度、高拓展性的用于规划交通最优路径的方法包括交通路网的建模方法和求解最优路径的算法,交通路网的建模方法中首先建立用于分析交通最优路径的交通模型,该模型除了道路之外,还考虑信号交叉口的影响,对于道路部分,根据距离和平均车流速度来计算代价;求解最优路径的算法使用针对交通场景改进的精英蚁群算法,改进的精英蚁群算法在信息素初始化时和全局信息素更新加入了两个优化,通过考虑信号交叉口的影响,提高了交通模型的精确度,改进的精英蚁群算法也大大提升了求解效率,同时该方法可以根据不用的信号交叉口场景以及车辆行驶需求进行拓展,这些使得本发明在现代城市交通及无人驾驶的车辆导航中具有广泛的运用前景。
High-precision and high-expansibility method for planning optimal traffic path
一种高精度、高拓展性的用于规划交通最优路径的方法
2020-04-10
Patent
Electronic Resource
Chinese
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