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The Cooperative Guidance Path Optimization Based on Road Network Layered

机译:基于路网分层的协同制导路径优化

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Targeting the prominent "navigation jam" phenomenon, using the optimal balance model of the system, a cooperative induction path search algorithm with complementary advantages of distributed induction and central induction is proposed. First, using the Beckmann traffic balance distribution model, the equilibrium is considered from the perspective of the road network. Then, through the dynamic search limitation of the path search in the sub-area low-level road network, the cross-layer node determination based on the improved A* is proposed. Based on this method, an improved cross-layer path search algorithm is established. Finally, a collaborative induction algorithm model is built, which breaks through the existing navigation path provision method and proposes a new phased approach to provide the optimal path. Through the new induction method, the traffic flow balance of the whole network can be guaranteed.
机译:针对突出的“航行拥堵”现象,利用系统的最佳平衡模型,提出了一种分布式感应和集中感应相辅相成的协同感应路径搜索算法。首先,使用贝克曼交通平衡分配模型,从道路网络的角度考虑平衡。然后,通过子区域低等级公路网中路径搜索的动态搜索限制,提出了一种基于改进A *的跨层节点确定方法。基于此方法,建立了一种改进的跨层路径搜索算法。最后,建立了一种协同归纳算法模型,该模型突破了现有的导航路径提供方法,并提出了一种新的分阶段方法来提供最佳路径。通过新的归纳方法,可以保证整个网络的流量平衡。

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