摘要
讨论了在动态随机网基于实时信息的车辆导航问题。交通网中的每一路段的旅行时间建模为随机变量,可以在车辆进入路段前根据实时信息估计其旅行时间。与经典最短路径算法不同的是,不需要在车辆行驶前就确定一条从起始点到终点的完整固定的路径,只需要在车辆到达结点时,根据实时信息估算出从当前位置到终点的预计旅行时间,选择下一路段。这样在车辆行驶过程中就能根据提供的实时信息选择更好的路径,达到优化路径的目的。
The problem of vehicle routing is discussed in a dynamic and stochastic traffic network with real-time information. Travel time on each link can be modeled as a random variable and can be estimated with the real-time information before the vehicle enters the link. Different from the classic shortest path algorithms, this algorithm doesn' t need to determine a complete fix path from original node to destination node, only to estimate the travel time from current position to destination node with real-time data and determine the next link when the vehicle arrives at the node. Using real-time information as the routed vehicle advance, it has a chance to divert to a better path, and achieve the aim of optimizing path.
出处
《计算机工程与设计》
CSCD
北大核心
2005年第10期2662-2664,2667,共4页
Computer Engineering and Design
基金
信息产业部科研项目(2003XK320014)
关键词
最短路径
车辆导航
旅行时间
动态随机网
shortest path
vehicle guidance
travel time
dynamic and stochastic traffic network