A Hybrid Link‐Node Approach for Finding Shortest Paths in Road Networks with Turn Restrictions

Turn restrictions, such as ‘no left turn’ or ‘no U‐turn’, are commonly encountered in real road networks. These turn restrictions must be explicitly considered in the shortest path problem and ignoring them may lead to infeasible paths. In the present study, a hybrid link‐node Dijkstra's (HLND) algorithm is proposed to exactly solve the shortest path problem in road networks with turn restrictions. A new hybrid link–node labelling approach is devised by using a link–based labelling strategy at restricted nodes with turn restrictions, and a node‐based labelling strategy at unrestricted nodes without turn restrictions. Computational results for several real road networks show that the proposed HLND algorithm obtains the same optimal results as the link‐based Dijkstra's algorithm, while having a similar computational performance to the classical node‐based Dijkstra's algorithm.     

The Minimum Step Linkage Algorithm and Cumulative Cost Model for Time‐Dependent Shortest Paths

Real‐word road networks are typically time‐dependent, but research on time‐dependent shortest paths (TDSPs) is not as rich as that on static shortest paths (SSPs). For large networks, some speed‐up techniques are usually applied to compute SSPs. Unfortunately, many of these techniques are impractical for TDSPs, especially the techniques requiring a precomputation because the number of time instances may be incredibly large or even infinite. Therefore, this study introduced a new TDSP technique that is able to overcome the issue of infinite time instances by utilizing network geometry alone for the pre‐computation, namely the Minimum Step Linkage (MSL) algorithm. It works with a data model called Cumulative Cost Model (CCM). The theoretical concepts of the new data model and algorithm are described, and its performances were tested and compared with existing algorithms through a series of simulations.     

路网环境下的混合数据最近邻查询算法

路网环境下的k最近邻查询方法在地理信息系统、智慧城市、数据挖掘、医疗营救和物流配送等领域都有着较为重要的作用,已有路网环境下的最近邻查询方法无法直接解决查询对象为点而数据对象为点和线段混合的复杂数据的近邻查询问题,为了弥补已有方法的不足,提出了路网环境下混合复杂数据的最近邻查询算法。将查询过程分为预处理、数据集约减和数据集精炼3个部分,并与3种对比算法进行对比实验,研究了测试数据对象的数量、路网规模的大小对中央处理器运行时间以及输入/输出代价的影响。结果表明,所提算法能有效地处理路网环境下混合数据的最近邻查询问题。     

Finding least-cost paths across a continuous raster surface with discrete vector networks

The problem of finding the least-cost path from a source point to a destination point can be dealt with by routing across a continuous surface or routing along a discrete network. The solutions within these two contexts are linked to the use of a raster- or a vector-based least-cost path algorithm. This study presents a technique which integrates raster- and vector-based least-cost path algorithms for determining the least-cost path across a continuous raster surface with discrete vector networks. The technique incorporates ancillary vector data sets that are required to examine the travel cost at each link, connections between nodes, and the representation of intersecting links in the discrete vector network into raster-based least-cost path analysis. The integrated technique presented here is applicable to all-terrain vehicle navigation where a continuous raster surface and discrete vector networks need to be considered simultaneously in order to find least-cost paths. This paper describes the concept behind, and details of, the integrated technique. Applications of the technique with synthetic and real-world data sets are also presented. They provide proof that the technique is effective in finding least-cost paths across a continuous raster surface with discrete vector networks.     

A topographically preserved road‐network tile model and optimal routing method for virtual globes

Virtual globes enable the combination of heterogeneous datasets for optimal routing analyses in transportation, environmental ecology, and construction engineering. In this study, considering the advantages of the hierarchical tiling structure and topography of virtual globes, we propose a tile‐based optimal routing method for large‐scale road networks in a virtual globe. This method designs a topographically preserved road‐network tile model by partitioning roads into tiles and constructs the road‐network pyramid from the bottom to the top. During construction, a TileArc is calculated and flagged as the shortest path in a tile. Based on the built road‐network pyramid carrying hierarchical TileArcs, a multi‐level and flexible shortest path query can be executed efficiently. The proposed method is implemented with large road networks with different road grades in a virtual globe. Experimental results verify its validity, efficiency, and exactness. Moreover, the length of the shortest path with surface distance is approximately 1.3 times longer than that with Euclidean distance.     

基于典型事例推理的路径规划方法研究(英文)

Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people’s preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be? How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them? All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and completely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.     

Assessing Raster GIS Approximation for Euclidean Shortest Path Routing

Identifying a route that avoids obstacles in continuous space is important for infrastructure alignment, robotic travel, and virtual object path planning, among others, because movement through space is not restricted to a predefined road or other network. Vector and raster GIS (geographic information system) solution approaches have been developed to find good/efficient routes. On the vector side, recent solution approaches exploit spatial knowledge and utilize GIS functionality, offering significant computational advantages in finding an optimal solution to this path routing problem. Raster‐based shortest path techniques are widely applied in route planning for wayfinding, corridor alignment, robotics and video gaming to derive an obstacle avoiding path, but represent an approximation approach for solving this problem. This research compares vector and raster approaches for identifying obstacle‐avoiding shortest paths/routes. Empirical assessment is carried out for a number of planning applications, highlighting representational issues, computational requirements and resulting path efficiency.     

VC环境下最短路径算法的实现

设计了一种方便查找及显示最短路径的数据结构,对仅研究计算一条最短路径的Dijkstra算法加以了改进,并在VC下实现一个顶点到另一个顶点的所有最短路径的查找。     

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.     

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.     

基于道路网络分析的Voronoi面域图构建算法

提出一种基于网络分析的Voronoi面域图和加权Voronoi面域图构建算法。鉴于道路网络在城市中心地、公共设施引力传导与功能覆盖上的重要作用,采用网络最短路径距离分析和最短路径时间分析构建的Voronoi面域图可以模拟出中心功能的辐射影响范围空间划分的实际情形,进而为空间分析和空间优化提供有力支持。算法过程主要包括:设施邻近道路结点检索和分界结点计算;基于网络最短路径分析Dijkstra算法和分界结点计算的网络Voronoi划分;基于空间离散化、邻近道路分析的空间Voronoi划分及其矢量化处理算法。计算实验结果表明本文提出算法可靠和高效,能够模拟出具有预期精度和形态复杂的网络Voronoi面域图形。     

交通运输最短路径分析系统的设计与实现

针对目前交通运输效力发挥不足的问题,研究道路网络模型构建和道路数据库设计,探讨分析交通运输最短路径分析流程,基于Dijkstra算法的基本原理,设计实现交通运输最短路径分析系统,从而优化运输资源配置,实现高质高效的交通运输。     

一种利用双侧凸包扩张模型的路径快速规划算法

针对障碍环境中路径规划存在的运算效率低、最短路径遗失问题,根据凸包边界在构建空间网络模型过程中具有快速高效的特点,结合路径与障碍物的相对位置关系,提出了一种基于双侧凸包扩张模型的路径快速规划算法.该算法在对凸包边界算法进行改进的基础上,提取左右侧关联障碍物的凸包边界作为网络模型,利用最短路径算法搜寻目标路径,并在Arc...     

最简单路径寻找方法研究

许多认知研究表明,路径指令的复杂性和形式在人类导航中和路径的长度一样重要。在很多情形下,我们所需要的不是到达目的地的最短路径,而是一条最简单路径,也就是容易描述、理解、记忆或者执行路线的导航指令。大多数自动导航系统都依赖于计算最短路径问题的解,而不是找到最简单路径。本文在分析人们对道路转向的认知研究基础上,采用了适合道路转向的路段-链数据模型,并从权重函数选择、算法具体实现和算法分析三个方面具体论述了最简单路径算法的主要思想和具体实施。     

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。     

一个从基于位置相关服务而收集的零星位置点中获取连续车辆轨迹的方法(英文)

The paper proposes an economical and fast algorithm for deriving trajectories from sporadic tracking points collected in location-based services (LBS). Although many traffic studies or applications can benefit from the derived trajectories, the sporadic tracking points are always implicitly overlooked by most of existing map-matching algorithms. The algorithm proposed in this paper finds network paths or trajectories traveled by vehicles through augmenting GPS data with odometer data. An odometer can provide data of traveled distance which are compared with the lengths of candidate network paths in order to find the most approximate network path approaching the trajectory of a vehicle. Tracking points are classified into anchor points and non-anchor points. The former are used to divide trajectories, and the latter screen candidate network paths. An elliptic selection zone and a reduction process are applied to the selection of possible road segments composing candidate network paths. A brute-force searching algorithm is developed to find candidate network paths and calculate their lengths. A two-step screening process is designed to select the final result from candidate network paths. Finally, a series of experiments are conducted to validate the proposed algorithm. Supported by the National Natural Science Foundation of China (No.40701142), the Scientific Research Starting Foundation for Returned Overseas Chinese Scholars, Ministry of Education, China.     

基于二叉树的启发式搜索算法改进

最短路径是现代物流配送研究中热点问题之一,在分析传统启发式搜索算法的基础上,针对算法在路径优化中存在的不足,提出基于二叉树优化启发式搜索算法（A＊）实现所需结点之间最短路径查询,在引入已知的全局信息条件下选择下一个被检查的结点,并根据用户给出的起始顶点与目标顶点以及搜索的角度查找最短路径,从而搜索可能性较大的结点,提高搜索过程的效率.实验表明,基于二叉树的A＊比A＊效率提高11％～26％.     

基于道路连通性和最短路径的综合地图匹配算法

本文研究了要素加权法、路网拓扑法和网格划分法等地图匹配算法,分析了地图匹配过程,包括地图数据预处理、道路连通性的建立、投影点的计算和道路匹配度的计算,提出了一种基于道路连通性,采用捕捉圆获取候选道路集的地图匹配算法,并且对车辆GPS信号丢失的情况,采用最短路径算法,推算出车辆经过的道路。最后通过试验比较分析,验证了本算法具有较高的匹配准确度、匹配速度和实用性。      

北京交通网络拓扑结构及可达性格局历史变化研究

基于过去800年（1160～2000年）北京城市交通网络时间序列数据,研究了北京交通网络的发展变化。主要从交通网络的拓扑结构、可达性等角度分别对网络直径、平均最短路径长度、平均聚集指数、相对可达性等指标进行了定性定量分析。研究结果表明：第一,北京交通网络扩张呈“两段式”特点：前数百年只加密路网,近53年网络直径扩张了2．62倍;第二,从网络拓扑结构的角度分析,北京过去800年交通网络度分布结构呈现良好的一致性,交通网络中顶点与路段的比例保持不变,网络内部联系日趋紧密;第三,北京交通网络可达性格局趋于有序：从金元时期的不规则格局发展为明清时期的椭圆形格局,建国后呈圆盘形格局扩张,但可达性中心由天安门向西北方向偏移至阜成门处。通过搜集研究北京过去800年的交通网络数据,本文记录了北京交通网络演化的全过程,并揭示了其演化过程中蕴含的宏观规律。     

基于众源数据的室内外一体化行人路网构建

行人路网的完整性和准确性是保障步行导航服务的关键。当前的行人路网大多是基于室外道路设施构建的,缺乏室内可步行路径的数据支持,无法在导航应用中提供准确、真实的最优路径规划服务。鉴于此,本文提出了一种基于众源数据的室内外一体化行人路网构建方法,采用智能手机定位传感器与惯性传感器记录的众源轨迹,首先对缺失或者漂移的室内步行数据进行筛选,然后使用改进的行人航位推算(PDR)方法推算出准确的室内轨迹,进而采用莫尔斯理论生成涵盖室内外行人路径的完整行人路网。试验分析中对搜集到的260条步行轨迹数据进行行人路网构建,并使用高精度测量设备采集真实路网数据进行对比分析,结合OSM数据对试验结果进行综合评价。试验结果表明,本文方法能够准确、完整地生成室内外一体化行人路网。