A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 1: Background

This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpose of the series is to develop a trajectory-oriented road network data mode l, namely carriageway-based road network data model (CRNM). Part 1 deals with t he modeling background. Part 2 proposes the principle and architecture of the CR NM. Part 3 investigates the implementation of the CRNM in a case study. In the p resent paper, the challenges of managing trajectory data are discussed. Then, de veloping trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approa ches of a road network are introduced as well as its constitution.

A Trajectory-Oriented, Carriageway-Based Road Network Data Model,Part 2:Methodology

This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introduced a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. Based on it, this paper describs the CRNM in detail. At first, the notion of basic roadway entity is proposed and discussed. Secondly, carriageway is selected as the basic roadway entity after compared with other kinds of roadway, and approaches to representing other roadways with carriageways are introduced. At last, an overall architecture of the CRNM is proposed.

A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 3: Implementation

This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.

A Spatio-temporal Data Model for Road Network in Data Center Based on Incremental Updating in Vehicle Navigation System

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.

Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.

The Shortest Path Analysis Based on Road Network

Rational planning of agricultural product transport route from initial node to destination node can effectively reduce the cost price of agricultural products,and the calculation of shortest path between any two points also affects people’s daily travel.Taking Heze Railway Station to Heze College for example,with remote sensing image data as the base map,we conduct vectorization and topological analysis on roads in the target area.With Dijkstra as theoretical basis of shortest path algorithm,we use ArcG IS network analysis method to build road network,and calculate the planning program of the shortest distance path,the shortest path by driving and the shortest path by walking.

Landscape Network Approach to Assess Ecological Impacts of Road Projects on Biological Conservation

Awareness of the adverse ecological effects of road and other large construction projects has resulted in a rapidly growing demand to quantitatively predict and evaluate the effects on gene flow among plants and animals in natural habitats.In this study,we evaluated the effects of different road construction scenarios on animal species movement by using the methods of ecological landscape connectivity in the typical regions of Yunnan Province,China.The results showed landscape connectivity levels(Probability of Connectivity(PC))decreased after road construction and species with lower dispersal abilities were more affected to the subsequent habitat fragmentation.First level roads affected landscape connectivity most significantly.At a distance of 100 m,the PC index decreased more than 50%.Further analysis suggested that the use of landscape connectivity to assess landscape processes revealed the adverse effects on the species movement more effectively compared with the traditional landscape pattern analysis.In addition,we conducted a graph theory and a least-cost modeling discussion,it is obvious that they are powerful tools to represent and analyze landscape networks with respect to related species movement.Network analysis offers a quantitative and simple but effective tool for ecological process assessment and biological conservation on large scales.

“一带一路”共建国家农业科技创新合作网络结构演化及影响因素探究

基于WOS数据库中跨国农业科技论文合著数据,借助社会网络分析法和QAP回归模型,剖析2006—2020年“一带一路”共建国家农业科技创新合作网络结构演化特征及影响因素。研究发现:(1)“一带一路”共建国家农业科技创新合作网络整体结构指标均得到了不同程度的优化,且各指标优化速度快于全球农业科技创新合作网络。(2)“一带一路”共建国家和全球国家农业科技创新合作网络去中心化趋势均较明显,多核共存特征更加突出。(3)中国和意大利在合作网络中同时扮演着核心者和中间人角色。(4)合作网络呈现出双向溢出、主受益、“经纪人”3种类型的块集聚特征,亚洲国家是推动农业科技创新合作的主引擎。(5)制度、经济、科研和认知邻近对3个阶段的合作网络都具有显著的正向影响,而空间邻近对合作的阻碍作用逐渐减弱。“一带一路”共建国家应进一步重视跨国农业科技创新合作,明确自身在合作网络中的地位与角色,充分借助网络核心国家的重要作用,加速融入农业科技创新国际合作核心网络.

多因素下基于路网拓扑的电动汽车充电路径规划策略

随着电动汽车产业的发展,电动汽车的充电需求也日益增加.为了满足电动汽车用户充电多样性需求并提高充电设施利用率,本文在考虑出行距离、充电电价以及充电站排队情况等三种影响因素下构建混合整数线性规划模型,提出了一种多因素下基于充电站路网拓扑结构的电动汽车充电路径规划方法,为用户规划充电路径与充电站选择.首先,该方法在能耗约束的前提下基于Dijkstra最短路径算法进行充电引导,为求解多目标最优引入信息熵的概念来确定各参数影响权重.其次,针对用户充电需求的差异性问题,提出了三种不同目标下的规划方法以降低用户充电成本.此外,本文构建了站点随机充电服务排队模型并进行敏感性分析以研究充电站服务能力对充电成本的影响.以某地区路网为算例进行仿真,结果表明本文提出的方法能够有效降低用户充电出行成本并合理规划出行路径,验证了所提模型的可行性和有效性,对充电选择和站点配置具有一定的决策参考意义.

基于NAR-ARIMA组合模型的高速公路沥青路面破损状况预测

基于NAR神经网络模型和ARIMA传统时间序列预测模型,对高速公路沥青路面的破损状况进行预测,再分别通过最优加权法和残差优化法对两种预测模型进行组合,得到两种组合模型.对各单一模型和组合模型的精度和稳定性进行了比较分析.实例分析表明,组合模型相较于单一模型的精度和稳定性均有所提升,NAR-ARIMA最优加权组合模型预测效果最佳.该组合模型所需样本量较小,且基于时间序列.由于采用历史数据作为影响因素代替指标,该组合模型计算速度快、精度高,适用于日常的预测工作,为后续合理的道路养护决策提供了重要的理论依据.

基于Transformer的路网轨迹重建方法

轨迹重建是针对低采样轨迹数据进行轨迹补充还原的一类轨迹数据处理研究。为了提高轨迹重建的准确性,一些工作通过引入Seq2Seq等深度学习模型来提升轨迹重建的效率与精度,但由于现有工作忽略了轨迹间的长距离依赖问题,导致轨迹还原中还存在准确率不高等问题。本文提出一种基于Transformer的轨迹重建模型ZTrajRec(Zero-based trajectory recovery),通过Transformer编码器捕获轨迹间的长距离依赖,注意力机制用于当前轨迹和历史轨迹相似性查询来进行轨迹在路网上的重建。实验结果表明,在真实北京出租车数据集上,ZTrajRec比基准模型最好效果在召回率上提升3%∼4%。本文最后对重建结果进行了可视化分析以展示其合理性。

基于城市雨洪模型的长治市某城区应急救援路径规划研究

在洪水应急管理中,合理设计救援路线,有助于提高救援效率,减少灾害损失。在建立的内涝灾害救援路径规划框架中,采用高效高分辨率雨洪模型,模拟区域的内涝过程,基于内涝结果,采用原始法重构路网拓扑结构。考虑道路风险及水深对车速的影响,构建以时间为指标的路段权重矩阵,采用Floyd算法推求最短路径。另构建了以路径长度为指标的权重矩阵,作为对照。以长治市某城区为例,设置5种情景条件(无降雨、50 a、100 a、200 a、500 a),比较不同情景下的救援路线。结果表明:分别以通行时间、路径距离为指标构建路网权重进行计算,其结果有明显变化。500 a降雨条件下,以通行时间为指标构建的路网权重得到的规划路线,在通行距离上增加了12.43%,而在行驶时间上少了14.07%。

基于激光点云数据的室内路网构建方法

面对价格昂贵的专业级三维激光扫描仪,针对使用现有二维底图或人工建模可能使得在构建跨楼层路网的过程中出现准确性或效率性低等情况,且考虑如何对室内过道、走廊等区域进行抽象,提出一种基于激光点云数据的室内路网构建方法。该方法以消费级激光雷达扫描设备采集的建筑物内部点云为基础数据,结合直通滤波和投影滤波对点云进行预处理,得到去噪后的平面二维点云,进行栅格二值化处理,针对性填充点云孔洞,抽取骨架线,剔除毛刺并提取骨架线节点,将节点间的拓扑关系存储为邻接表形式的图模型,得到可利用Dijkstra算法寻径并将寻得的最短路径可视化的三维路网模型。

高速公路实时交通流模糊逻辑优化控制系统设计

针对高速公路交通流特征复杂多变,并受到天气、道路状况和车辆类型等多种因素影响的问题,设计了一种新的高速公路实时交通流模糊逻辑优化控制系统,包括硬件和软件两部分;在硬件方面,设计了车流控制模块、无线传输车载终端、实时交通流逻辑调度模块和模糊控制器模块,并确定了它们之间的实时连接关系;在软件方面,求解了交通流逻辑控制条件,联合了高速公路实时通行相位条件,调节了模糊控制器,并根据高速公路交通路网模型推导了交通流优化控制条件的求解表达式;实验结果表明,该系统可以解决逻辑协调错误的问题,并有效控制高速公路车流量。

基于稀疏采样数据的复杂路网地图匹配算法

地图匹配是指将GPS定位坐标正确匹配到数字地图的道路上.离线地图匹配是从记录和存储的轨迹数据中寻找车辆行驶的真实路径.采样频率和复杂路网是影响地图匹配正确率的两个最重要的因素.为了提高现有的隐马尔可夫模型地图匹配算法在复杂路网上的正确率,提出了分段验证匹配方法(SV算法).考虑到每一段子轨迹会有k条候选路径,引入一个适应度来评判候选路径与轨迹的吻合程度,选取具有最高适应度的候选路径作为局部最佳匹配路径.此外,所提算法还考虑了路段方向和车辆行驶方向的角度差和路段限速,通过这些约束条件过滤候选路段和候选点,以提高算法效率.

既有公路网决策合理性综合评价——以广州为例

对既有公路网决策的合理性进行综合评价,采用熵权、层次分析和云模型三者结合的方法,欧氏距离函数对主、客观权重组合赋权。运用云模型的逆向云发生器,生成标准云和结果云图。以广州市既有公路网作为实例,验证模型的准确性,评价结果表明:此路网决策合理性总体合理,但局部存在不足。居民消费价格总指数、公路网密度和第一产业评价期望值低于标准云合理期望值,熵和超熵均高于标准云,分析评价结果产生的原因及改进措施与当前广州公路网规划及措施一致,说明本综合评价方法科学准确。

促进时空可达的高校新校区步行路网优化——以重庆医科大学缙云校区为例

可达性是高校校园步行出行的基本要求.然而,我国高校新校区既有步行路网存在局部空间可达水平偏低、近距离绕行等问题.本研究以重庆医科大学缙云校区为例,采用空间句法理论下的线段模型和ArcGIS最优路径分析模型,量化其步行时空可达水平;结合步行空间实际使用水平,提出校园步行路网的改善方案并评估方案的步行可达性.研究发现:(1)分级的步行路网可提升全局和局部空间可达性,精细的道路设施设计可确保实际使用的可达性;(2)有序的游憩步道可增强空间感知的可达性;(3)以吸引点为导向的步行捷径可改善时间可达性.

计及多方利益的“车-路-网”三层充电优化方法

随着电动汽车(EVs)保有量逐年增加,充电需求日益增大,短时间内大规模EVs集中充电不仅会给电网稳定运行带来风险和负担,还会造成路网交通拥堵。为了缓解上述问题,提出一种兼顾配电网、路网和车主三方利益的“车-路-网”三层充电优化方法。通过三层优化模型的相互传递与配合,对配电网的等效负荷方差和有功网损、路网的通畅情况、车主的充电总成本进行协调优化。以杭州市某区域路网为例,结合IEEE-33节点配电网系统进行仿真。通过三层充电优化,系统等效负荷方差降低72.82%,有功网损降低83.41%,车主充电总成本减少8.89%。仿真结果表明,所提优化方法能够合理安排EVs充电,可以在平抑负荷波动和降低有功网损的同时,缓解路网拥堵和降低车主充电总成本。

山区小城市路网承载力评估模型及算法

为了有效评估山区小城市路网的供给能力,揭示路网联结度低、机非干扰严重等道路交通特性对其路网承载力的影响,本文在定义山区小城市路网承载力的基础上,建立了双层规划模型,并提出可变步长的迭代优化算法实现模型的近似求解。算例结果表明,模型和算法具有较高的实用性和有效性。

基于深度学习的城市主干道路交通拥堵水平预测

为了解决城市主干道路交通拥堵问题,提出一种基于深度学习的城市主干道路交通拥堵水平预测方法。建立城市主干道路交通网络的Katz相似度矩阵,保存路网的结构特征,获得城市主干道路交通流数据。采用局部敏感判别分析模型,将交通流数据映射到低维流形,获得最优投影矩阵,提取城市主干道路交通特征。结合循环神经网络模型(RNN)和长短时记忆网络模型(LSTM),设计长短时记忆循环网络(RNN-LSTM)模型,解决梯度消失问题,输入城市主干道路交通特征,经过训练输出城市主干道路交通拥堵水平预测结果。实验结果表明,所提方法预测准确度在0.8~0.98,预测所需时间平均为24.74 ms,具有一定的应用价值。