校车最优路径规划算法

提出一个基于GIS网络分析的校车路径方案规划算法。算法采用Dijkstra最短路径算法结合道路网络拓扑分析。以高效利用各种资源为目的,通过限制搜索范围提高算法效率,并用空间分析选择最佳起始节点,计算将学区内路网上各乘车节点处的学生送至学校的最优路径方案。实验结果验证了该算法的高效性和有用性。     

A^＊算法的改进及其在路径规划中的应用

A*算法是一种启发式搜索算法,在路径规划中得到广泛的应用,其中启发函数的设计尤其重要.本文针对路径规划问题,对A*算法作了以下改进:一是在估价函数中考虑以距离和方向两个要素,通过归一化处理解决了单位不统一的问题;二是利用k-d树空间索引结构,动态加载节点信息,减小内存使用空间.实验结果表明,改进后的A*算法的搜索效率得到了明显的提高.     

满足实时导航应用的路径规划算法研究

主要针对当前嵌入式导航应用中路径规划计算存在的问题,设计了一种满足实时导航应用基于转换路网的分层搜索A*算法。该算法对于大区域的路径规划采用分层搜索策略,路径计算时采用能够处理交叉口转向限制和结点权重,并且占用存储空间小,搜索速度快的基于转换路网的二次搜索A*算法。通过实际的应用表明,算法在计算速度、路径合理性等方面可以满足实时导航应用的技术需求。     

顾及转向延误的时间依赖A*最短路径算法

现有的动态路径规划算法通常只考虑当前时刻交通信息,而忽略了路段行程时间依赖于进入该路段的时刻这一现实。而且,转向延误的存在使得传统的基于节点标号的最短路径算法不再有效。本文建立了基于路段的时间依赖网络模型,将转向延误时间引入到FIFO（先进先出）条件的定义中,并给出了满足FIFO条件的路段到达时间和转向延误时间计算式。以此模型为基础,并通过将时间因子引入到启发式评价函数中,发展了基于路段标号的时间依赖A*最短路径算法。实验表明,所提出的算法能预测并回避即将发生的交通拥堵,有效节省用户的出行时间。而其平均计算时间仅比传统算法增加了10%左右。此外,由于不再需要进行频繁的路径重优化,该算法能大幅提高路径规划的整体效率。     

MapInfo中道路拓扑与最优路径的实现

文中以阜新市为例较为详细地讨论在公交线路网络中的拓扑结构建模,及基于公交线路网的弧段与节点间地理相关性的拓扑特征;并以MapInfo为平台,运用MapBasic语言,采用经典的Dijkstra最短路径算法,实现对阜新公交站点查询、公交线路查询、两站点间的最优路径查询功能.     

基于多目标决策与层次分析法的最佳路径模型

在最佳路径选择问题中,如何综合考虑多种因素的综合影响以及确定各因素的影响大小是一个关键性问题。通过建立最佳路径的道路层次模型,给出多目标决策模型和因素评分模型,并用层次分析法确定各影响因素权值的方法建立了基于多影响因素与综合评判的最佳路径模型。同时,在Dijkstra最短路径算法的基础上,应用文章所提模型方法实现了在多...     

基于VB语言的最短路径计算

基于＂邻接点＂概念,研究了最短路径的快速计算方法,并利用VB语言编写了计算所需的核心模块,最终实现了从一个节点到另一个节点的所有最短路径的快速查询和显示。     

嵌入式GIS中最优路径规划算法研究与实现

针对现有大区域范围路径规划算法存在的一些问题,提出一种多比例尺最优路径规划算法。该算法在进行路径规划时,在小区域范围内根据道路的属性信息对路网进行分层,在大区域范围内根据多比例尺信息对路网进行分级,在每级或每层内采用基于弧段的改进型A*算法。从实例分析可以看出,该算法能较好满足车载导航系统的需求。     

面向越野路径规划的多层次六角格网通行模型EI北大核心CSCD

针对大规模越野环境中规划路径效率低下的问题,本文提出了一种面向越野路径规划的多层次六角格网通行模型,该模型能在缩减格网数据规模、保持规划路径合理性的同时,提升路径规划算法的执行效率。本文首先以六角格网单元为基础,设计通行能力量化规则,赋予每个格网相应的通行能力,构建普通六角格网通行模型;然后,建立多层次格网压缩规则,对通行模型中通行能力相似的邻接格网进行合并及重构格网邻接关系,生成含有不同层次格网的通行模型;最后,针对本文提出的多层次六角格网通行模型,设计了考虑坡度和地表覆盖要素的启发函数,进一步对A*路径规划算法进行了优化。试验表明,本文提出的多层次六角格网通行模型相较于普通六角格网通行模型,格网数量缩减了53.75%,路径规划所需时间降低了57%。     

顾及天气影响的动态路网最优路径研究

针对雨雪雾天气影响下的动态路网最优路径问题,概括了天气影响行车的因子,基于停车视距模型进行了顾及天气影响的安全车速计算。在此基础上,将行车的时间和费用作为路阻,并结合现有交通模型,采用最大似然估计法确定了路阻函数,论述了在天气和交通状况已知的条件下,如何构建动态路网模型,并提出一种求解动态路网最优路径的算法。     

An optimum vehicular path algorithm for traffic network based on hierarchical spatial reasoning

Human beings’ intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms. It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic, so as to improve running efficiency and suitability of shortest path algorithm for traffic network. The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path. It is argued that the shortest path, no matter distance shortest or time shortest, is usually not the favorite of drivers in practice. Some factors difficult to expect or quantify influence the drivers’ choice greatly. It makes the drivers prefer choosing a less shortest, but more reliable or flexible path to travel on. The presented optimum path algorithm, in addition to the improvement of the running efficiency of shortest path algorithms up to several times, reduces the emergence of those factors, conforms to the intellection characteristic of human beings, and is more easily accepted by drivers. Moreover, it does not require the completeness of networks in the lowest hierachy and the applicability and fault tolerance of the algorithm have improved. The experiment result shows the advantages of the presented algorithm. The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.     

An optimum vehicular path algorithm for traffic network based on hierarchical spatial reasoning

Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.     

面向大规模道路网的最短路径近似算法

节点重要性对大规模道路网下最短路径的计算有着重要影响。本文提出了顾及节点重要性的最短路径估计方法,该方法基于Critic方法与复杂网络理论评价节点的重要性,结合限制策略实现网络划分,通过层次结构网络的构建,实现大规模道路网数据的有效化简和最短路径的快速有效计算。试验结果表明,该方法能够使中心节点均衡地分布于网络,更好地均衡划分后子网络的规模;随着限制参数的增大,网络规模逐渐降低,查询精度最高达到1.026,相比于单一指标和无限制参数的方法,本文方法显著降低了网络的规模,在最短路径的近似计算上保持了较高的准确性,为大规模复杂网络的近似分析提供分析思路。     

基于电子地图和Dijkstra算法路径规划的实现

随着城市化水平的提高,人们在道路选择问题上可能需要考虑的并非仅仅是"空间距离"的最短,还有"时间最短",本文应用Dijkstra算法解决城市中出行交通道路选择的问题,对距离最短和时间最短路径分别进行讨论,用VB语言实现算法,并且在电子地图上绘制出所求出的路径,以便人们更直接地观看到结果,基本上解决了道路选择问题。     

网络最短路径的地图代数栅格算法

在阐述网络分析和最短路径算法的现状的基础上,以地图代数为理论支撑,介绍了地图代数对于网络元素的表达,探讨另外一种途径的网络最短路径分析—基于栅格数据的最短路径分析,重点讨论了基于地图代数的网络数据模型、栅格路径距离计算方法,在此基础上论述了求取最短路径的栅格方法的具体过程。最后,通过算例证明栅格途径的网络分析有其独特的优势。     

基于模糊理论的智能最优路径算法

在经典Dijkstra算法原理的基础上,提出基于模糊理论的智能最优路径算法.该算法综合考虑静态交通信息、动态交通信息和人的主观因素等路径选择的影响因素,建立路径选取度模型,确定影响因素的隶属度函数.该方法能够根据用户出行的不同目的和需求,自动调整各影响因素之间的权重,从而使路径选择既能满足用户的主观要求,又能真实反映复...     

GIS城市道路最短路径算法研究

本文紧密结合城市公交的特点,利用改进Dijkstra算法开发出一个针对城市道路系统的最短路径自动搜索信息系统,该系统通过在ArcGIS环境下建立空间数据库和属性数据库,在VB环境下利用改进Dijsktra算法对McObjecta控件进行二次开发而设计完成,能在0.20s完成500多个交叉口的计算并找出其最短路径,是一种...     

基于正六边形格网的最短路径算法

本文在分析了现有算法的一些不足之处的基础上,结合正六边形的特点及水流扩散思想,提出了基于正六边形格网的最短路径分析算法。该算法在最短路径搜索过程中,对同一正六边形格网而言,它至起点的累计代价值,不需要进行数据比较和修正。与经典的Dijikstra算法相比,该算法大大节约了搜索的时间。     

A fewest-turn-and-shortest path algorithm based on breadth-first search

Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled. However, the optimality of paths for current navigation system is often judged purely on the distance travelled or time cost, and not the path simplicity. To balance these factors, this paper presented an algorithm to compute a path that not only possesses fewest turns but also is as short as possible by utilizing the breadth-first-search strategy. The proposed algorithm started searching from a starting point, and expanded layer by layer through searching zero-level reachable points until the endpoint is found, and then deleted unnecessary points in the reverse direction. The forward searching and backward cleaning strategies were presented to build a hierarchical graph of zero-level reachable points, and form a fewest-turn-path graph (G*). After that, a classic Dijkstra shortest path algorithm was executed on the G* to obtain a fewest-turn-and-shortest path. Comparing with the shortest path in Baidu map, the algorithm in this work has less than half of the turns but the nearly same length. The proposed fewest-turn-and-shortest path algorithm is proved to be more suitable for human beings according to human cognition research.