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Risk-Averse Autonomous Route Guidance by a Constrained A~* Search

机译:通过约束A〜*搜索进行规避风险的自治路线引导

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摘要

In this article, the authors propose an efficient algorithm for finding a risk-averse path for use in autonomous vehicle navigation systems. When no dynamic traffic information is available, a risk-averse path can be found by a constrained A~* search. The accuracy of navigation on the basis of static network data is improved by taking travel-time uncertainty into account. When dynamic traffic information in the form of broadcast traffic messages is available, rerouting is achieved by a constrained A~* search, which takes congestion propagation into account. By making use of information computed at the start of the trip, the authors propose a responsive version of the constrained A~* search, which reduces the on-demand response time. An experimental performance analysis of the proposed methods on grid graphs demonstrates their efficiency.
机译:在本文中,作者提出了一种有效的算法,可找到用于自动导航系统的规避风险的路径。当没有动态交通信息可用时,可以通过约束A〜*搜索找到规避风险的路径。通过考虑旅行时间的不确定性,可以提高基于静态网络数据的导航精度。当广播交通消息形式的动态交通信息可用时,通过约束A〜*搜索实现重新路由,该搜索将拥塞传播考虑在内。通过利用旅行开始时计算出的信息,作者提出了一种受约束的A〜*搜索的响应版本,从而减少了按需响应时间。在网格图上对所提方法进行的实验性能分析证明了它们的有效性。

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