An Urban Traffic Monitoring System Based on the ArcGIS Engine

The growing number of vehicles makes traffic jams and accidents significant problems. Making people get to know the real-time road condition can mitigate the effect of congestions greatly, but this is not supported by traditional traffic assistant systems. The intelligent traffic system is born to settle these problems. By making full use of the ArcGIS （Arc Geographic Information System） Engine characteristics, this paper designs and imple- ments an urban traffic monitoring system. The main functions of the system include the real-time road condition information display, layer-control, supervisory control management and the basic operations of a map. With the data collected by monitors deployed in intersections, different road conditions are calculated and shown with dif- ferent colors on the map and users can choose suitable roads to get away from the traffic congestion; meanwhile it can offer a reference for a traffic management department to make decisions on traffic control. The system has been deployed and shows high practicability and reliability in practical use.

Research on the Drunk Driving Traffic Accidents Based on Logistic Regression Model

Most of the current studies on drunk driving accidents focus on law making and public education. However, especially in China, there is less statistical analysis on the severity of drunk driving accidents between driving under the influence of alcohol (DUI) and driving while intoxicated (DWI). 3368 drunk driving related crashes were collected from the blood-alcohol test report in a city of China at 2012 and 2013. After data pre-processing, Chi-square tests were used to analyze the association between different variables and the type of drunk driving. The logistic regression model is conducted to estimate the effect of the variables under DUI and DWI. The results show that Hour of the day, Driver’s age, Driver’s casualties and Accident area have significant correlation with drunk driving. There was a slightly decrease by 0.995 per year with age and a slightly increase by 1.014 with time in the possibility of DWI. DWI is more likely to cause death in traffic accidents (OR = 1.316) than DUI. Driver’s deaths (OR = 2.346) is more likely to happen than the injuries (OR = 1.910) under DWI cases. These findings show that more attention should be paid to strengthen controls on the DWI. It also can provide important basis for accident prevent, traffic law enforcement and traffic management.

GIS在不动产测绘中的应用及前景分析

地理信息系统技术(GeographicInformation System,以下简称GIS)在不动产测绘能够提供不动产测绘数据空间基准、进行对不动产数据整合处理、建立不动产数据库、完成不动产数据质量检验。GIS具有工作效率高、测量精度大、应用便捷等优势,GIS与大数据、人工智能、实景三维技术融合不动产测绘行业中应用前景广阔。

Present Assessment of Public Traffic System Based on GIS in Kitakyushu

With increasing of serious environment problems and the coming of the aging society, new traffic systems should be urgently rebuilt. It is necessary to evaluate the traffic service level by utilizing new technique and tool. This paper takes Kitakyushu city as case study to carry out an evaluation of urban traffic system. The concept of accessibility and mobility is used to evaluate the present condition of existing public traffic system based on GIS technology, and then establishment of new route is discussed according to the evaluation results. Additionally, this paper established GIS database and illustrated the relationship between the public traffic and population density. The regions without enough existing traffic were identified. Moreover, the essential terms and considerations were put forward to simulate a new route of public traffic line.

TransCAD and GIS Technique for Estimating Traffic Demand and Its Application in Gaza City

In the early nineties of the last century, the transportation system in Gaza Strip was born and new infrastructure projects, especially road networks, were constructed. However, the construction lacked efficient application of a transportation planning process. Transportation planning relies on traffic demand forecasting process. The conventional process is impeded by extensive amount of socioeconomic data. One of the most widely-used models which mitigate this problem is the TransCAD Model. This model is rarely used in Gaza Strip for traffic demand forecasting, and most of the practices depend mainly on a constant growth rate of traffic. Therefore, the main objective of this research is to apply this model in Gaza City for traffic estimation. This model estimates the origin-destination matrix based on traffic count. The traffic count was carried out at 36 intersections distributed around Gaza City. The results of traffic flow estimation obtained from TransCAD are assigned to the Gaza maps using the GIS techniques for spatial analysis. It is shown that the most congested area at present is the middle of the city especially at Aljala-Omer Almokhtar intersection. Therefore, improvement scenarios of this area should be carried out. The results of calibration of traffic flow estimation show that the differences between the estimated and the actual flows were less than 10%. In addition, network evaluation results show that the network is expected to be more congested in 2015. This work can be used by transportation planners for testing any network improvement scenarios and for studying their network performance.

Optimal Logistics Activities Based Deep Learning Enabled Traffic Flow Prediction Model

Traffic flow prediction becomes an essential process for intelligent transportation systems(ITS).Though traffic sensor devices are manually controllable,traffic flow data with distinct length,uneven sampling,and missing data finds challenging for effective exploitation.The traffic data has been considerably increased in recent times which cannot be handled by traditional mathematical models.The recent developments of statistic and deep learning(DL)models pave a way for the effectual design of traffic flow prediction(TFP)models.In this view,this study designs optimal attentionbased deep learning with statistical analysis for TFP(OADLSA-TFP)model.The presentedOADLSA-TFP model intends to effectually forecast the level of traffic in the environment.To attain this,the OADLSA-TFP model employs attention-based bidirectional long short-term memory(ABLSTM)model for predicting traffic flow.In order to enhance the performance of the ABLSTM model,the hyperparameter optimization process is performed using artificial fish swarm algorithm(AFSA).A wide-ranging experimental analysis is carried out on benchmark dataset and the obtained values reported the enhancements of the OADLSA-TFP model over the recent approaches mean square error(MSE),root mean square error(RMSE),and mean absolute percentage error(MAPE)of 120.342%,10.970%,and 8.146%respectively.

Logistic Regression Based Model for Improving the Accuracy and Time Complexity of ROI’s Extraction in Real Time Traffic Signs Recognition System

Designing accurate and time-efficient real-time traffic sign recognition systems is a crucial part of developing the intelligent vehicle which is the main agent in the intelligent transportation system.Traffic sign recognition systems consist of an initial detection phase where images transportaand colors are segmented and fed to the recognition phase.The most challenging process in such systems in terms of time consumption is the detection phase.The trade off in previous studies,which proposed different methods for detecting traffic signs,is between accuracy and computation time,Therefore,this paper presents a novel accurate and time-efficient color segmentation approach based on logistic regression.We used RGB color space as the domain to extract the features of our hypothesis;this has boosted the speed of our approach since no color conversion is needed.Our trained segmentation classifier was tested on 1000 traffic sign images taken in different lighting conditions.The results show that our approach segmented 974 of these images correctly and in a time less than one-fifth of the time needed by any other robust segmentation method.

RESEARCH ON FRACTAL CHARACTERISTICS OF URBAN TRAFFIC NETWORK STRUCTURE BASED ON GIS

Traffic network is an importance asp ect of researching controllable parameters of an urban spatial morpholo-gy.Based on GIS,traffic network str ucture complexity can be understood by using fractal geometry in which th e length-radius dimension describes change of network density,and ramification-radius dimension describes complexity and accessibility of urban network.It i s propitious to analyze urban traffic network and to understand dynamic c hange process of traffic network using expanding f ractal-dimension quantification.Meanwhile the length-radius dimension and ramifica-tion-radius dimension could be rega rd as reference factor of quantitative describing urban traffic network.

Black Spot Determination of Traffic Accident Locations and Its Spatial Association Characteristic Analysis Based on GIS

In general, the location of traffic accidents is described as an address with text, so they are difficult to display on the map. The paper discusses how to utilize the geocoding technology and VRS-GPS positioning technology to record the traffic accidents with Geo-spatial information. Based on the spatial relationship between traffic accidents and road network elements, two-way association relationship is defined by spatial relationship computation. Then the paper presents the method which takes the potential of reducing accidents as an index to extract the black spots. Finally, in the discussion, the association relationship between black spots and traffic attributes is used to analyze the factors that resulting in traffic accidents.

Application of GIS for Urban Traffic Accidents: A Critical Review

The analysis of huge data is a complex task that cannot be executed without a proper system. Geographic information systems (GISs) have been used by many transportation agencies and police departments to analyze and manage urban traffic accident (UTA) data and for decision making aimed at decreasing accident rates and increasing safety. The exact location of accidents and environmental characteristics must be analyzed as UTAs occur in specific locations with specific characteristics. ArcGIS software is the best choice for obtaining meaningful information and analysis results from UTAs in an observational time span. GIS technology is a fundamental element for investigating and evaluating the complex spatial relationship among different components and urban traffic accident is one of them. Micro or macro analysis of UTAs through the spatial prospective within the geographical environment and urban structure can make a deep micro understanding of UTAs patterns in addition to assisting in decision making. UTAs can be considered complex events that occur in two aspects which are spatial and temporal or space and time in other word. A GIS can integrate more than two different and unrelated databases. The evaluation among different spatial objects in a geographical environment and associated factors in urban structure which are included but not limited to land use category, road transportation network qualification, population density, etc., is one of the GIS specification. Traffic safety organizations and UTA researchers use GISs as a key technology to support their research and operational needs. In particular, GIS-T is an often-used GIS application used for planning and decision-making in transportation.

Spatial Analysis of Traffic Accidents in the City of Medina Using GIS

The general objective of this research is to determine how to use the spatial analysis of traffic accidents in Medina Menorah City through geographic information systems. This research aimed to identify, locate and define the sites where traffic accidents are concentrated and determine the need to apply specific safety standards to reduce accidents and identify their causes thereof. This current research applied the analytical descriptive approach for its relevance with this specific research. This research collected traffic accidents data from the Ministry of the Interior, Department of General Traffic. That data captured the hotspots accidents in Medina Menorah City. Some of the most important results of the study are as follows: many roads were selected as High Accident Location HAL, such as Central Ring Roads, King Faisal bin Abdul-Aziz Road, Prince Abdul Majid bin Abdul-Aziz Road, and King Abdulla bin Abdel-Aziz Road. The high-speed roads are heavily linked to the massive increase of traffic accident rates, and the increase in the street section length led to the soaring number of total accidents. The study recommended performing more studies and different highway safety studies to identify and locate accident patterns on road networks. Due to the fact that the accidents concentration is intensely focused on Medina City center and Prophet’s Mosque, it is a must to increase the number of public transportations to and from Prophet’s Mosque, particularly during the Hajj period, because of the fact that the visitors of Prophet’s Mosque is on the increase during the said period. This study can be applied in other cities because knowing the locations of traffic crash hotspots can provide us with valuable insights into the causes of accidents and this knowledge helps decision-makers to better assess the risk associated with accidents.

Evaluation of Traffic Network between Tourist Attractions Based on GIS in Tai’an City

Tai’an City is rich in tourism resources,and there are many A-class tourist attractions.Based on the functions and characteristics of geographic information system(GIS),as well as the spatial distribution characteristics and distribution structure of tourist attractions,the research methods of nearest-neighbor distance,connectivity,accessibility and closeness analysis are used to analyze road traffi c distribution between tourist attractions in Tai’an City.①The R value of the nearest-neighbor point is 0.27,which proves that tourist attractions in Tai’an City are in the state of clustering,and the spatial distance of tourist attractions in clustering area is small.②Theβindex andγindex of connectivity are 1.42 and 0.58,respectively,indicating that the traffi c network connectivity between tourist attractions is low,there is no dense traffi c network,and the optimal combination of tourism resources in tourist attractions is not high.③The accessibility index Ai is 37.68 km,indicating that the accessibility is low and the traffi c between tourist attractions is not perfect.The research results will provide the reference for scientifi c,systematic and objective comprehensive evaluation of existing A-class scenic areas and traffi c conditions in Tai’an City.

恒压下GIS固体绝缘界面气隙缺陷放电严重程度评估

为了研究GIS绝缘子界面气隙缺陷的放电发展过程,文中设计了空洞气隙缺陷模型,搭建了一套GIS气隙缺陷放电长期测试平台。基于缺陷模型的击穿电压对带有缺陷的试品施加90%Ub、60%Ub、30%Ub的交流恒压,使用UHF检测系统采集放电数据直至试品击穿。提取放电次数、放电幅值、放电时间间隔分析放电状态特征,发现GIS气隙缺陷放电发展过程存在两个阶段,前期放电幅值缓慢增大,放电脉冲逐渐稀疏,放电发展较为平稳;后期放电幅值急剧减小,放电脉冲密集,放电发展剧烈,采用k⁃means聚类算法及BP神经网络建立了气隙缺陷局放发展阶段的划分规则。研究表明,放电次数、放电幅值、放电时间间隔3种统计参量呈现阶段式单调性的趋势,可以用3种统计参量前向差分绝对值作为特征参量来评估GIS气隙放电严重程度;对GIS恒压试验进行聚类分析将放电过程划分为平稳劣化阶段和加速劣化阶段,随着外施电压水平的降低,平稳劣化阶段被压缩,加速劣化阶段占比升高。

基于GIS与大数据分析的矿压监测预警平台

为响应国家关于加快煤矿智能化发展的号召,针对煤矿GIS“一张图”中巷道路径不能实现精确计算,矿压数据不能实现高效甄别、有效提取的问题,以及矿压预警需要实现在线推演、可视化展示的需求,提出建立基于GIS与大数据分析的矿压监测预警平台。采用GIS“一张图”、巷道结点-路径拓扑算法、多源异构监测数据处理技术、矿压大数据分析技术,搭建成能够实现矿井下复杂情况切实反映、矿压监测数据有效提取、采掘风险在线预测、可视化程度高的矿压监测预警平台。通过在李雅庄矿的实际应用,表明该系统运行稳定可靠,可有效提升煤矿的矿压风险监测预警。

直流电压下GIS盆式绝缘子表面电荷及电场分布特性仿真研究

GIS中盆式绝缘子表面在外施直流电压时会积聚大量电荷使得沿面闪络电压大幅降低,从而引发一系列电气设备故障。基于上述问题,文中分析了盆式绝缘子表面电荷的来源与传导途径,采用有限元仿真计算方法构建了二维轴对称仿真模型以及设定相关参数,研究了电压极性、不同电压幅值以及电压极性反转对盆式绝缘子表面电荷分布的影响。结果表明,在直流电压下,凹面主要积聚与外施直流电压极性相反的电荷,凸面主要积聚与直流电压极性相同的电荷,且凹面积聚的电荷密度更大;在极性反转后-100 kV直流电压下,盆式绝缘子表面原先积聚的电荷密度呈现先增大后逐渐减小的趋势,随后转换极性并达到饱和,电场在靠近高压端以及盆式绝缘子沿面0~20 mm处的畸变程度较为明显。电场在盆式绝缘子表面电荷极性发生变化前出现峰值,相比较电荷达到饱和状态,此时盆式绝缘子凹面最大场强增加46%,凸面最大场强增加5.4%。该研究可为直流电压下盆式绝缘子表面电荷分布特性提供指导。

基于GIS的公交换乘网络构建及可达性分析

为了提高公交换乘效率、优化公交系统,基于GIS软件构建公交换乘网络,运用该网络对换乘可达性进行了测度和分析.结合Space-P模型和网络分析法,以拉萨市城关区为研究区域,基于公交线路路径、站点、交叉口等基本信息构建同站换乘子网络.结合公交站点服务范围、步行通道路径、交叉口等信息构建异站换乘子网络.二者协同实现了基于ArcGIS的公交换乘网络构建,并依据该网络对公交线路的乘客在车时间和换乘系数进行测度和分析.结果表明:构建的换乘网络能够对乘客在车时间进行良好的测度,乘客在车时间最大值为68.68 min,最小值为2.00 min,乘客换乘在车时间平均值为29.90 min.该换乘网络能够对换乘系数进行良好的测度,得到有效换乘线路90 300条,换乘系数最大为4条(线路为62条),最小为0条(线路为1 354条).采用可达性度量模型,可实现对公交站点时间可达性和换乘可达性的良好测度和分析.

基于双回路反馈的光纤干涉式GIS局部放电超声传感系统研究

光纤干涉式GIS局部放电超声传感系统受到环境干扰,会导致超声检测灵敏度降低。基于单回路反馈的传感系统能够抑制振动干扰,但长时间工作仍会出现工作点漂移。文中首先分析了单回路反馈传感系统工作点漂移的原因,指出了压电陶瓷迟滞效应的影响;其次,搭建了基于双回路反馈的光纤干涉式GIS局部放电超声传感系统,引入了二次反馈回路以补偿一次反馈回路累积的低频相位调制误差;再次,通过振动干扰下的超声检测试验和GIS局部放电检测试验,证明了双回路反馈传感系统能够长时间保持稳定的超声检测灵敏度;最后,搭建了真型126 kV GIS局部放电检测试验平台,利用双回路反馈传感系统成功检测到了金属颗粒引发的局部放电和跳动声信号,检测到的最小视在放电量为5.2 pC。

基于多层融合振动数据分析的GIS设备机械缺陷诊断方法研究

气体绝缘金属封闭开关设备(gas insulated metal enclosed switchgear,GIS)机械缺陷是导致设备故障的重要因素,针对单测点、单证据机械缺陷诊断模型信息缺失和精度不足问题,该文提出一种多层融合振动数据分析的GIS设备机械缺陷诊断方法。首先,基于真型GIS设备振动模拟平台试验研究测点位置与缺陷类型对振动行为的影响特性;然后,联合统计分析、模态分解、尺度变换方法提出机械振动信号整体与局部信息关注的复合参数分析方法,引入主成分分析开展多测点振动信息的特征层融合降维;最后,提出改进放缩权重的Dempster-Shafer(DS)证据理论和Bagging投票机制的强/弱基学习器决策层融合机制,联合构建多层融合振动数据分析的GIS设备机械缺陷诊断模型。结果表明:不同类型机械缺陷信号的响应幅值、特征频点和畸变程度存在显著差异,复合特征参量大小及分散程度各不相同;同时,测点位置对缺陷信号的复合振动特征参量的表现形式及分布区间也具有一定影响;基于多层融合数据分析的诊断模型实现缺陷有效识别,辨识准确率为98.66%,相比单一分类器诊断效果提升5.83%。该文可为GIS设备机械缺陷诊断方法提供有价值的参考。

“互联网+”背景下GIS开发类课程群建设探索

在“互联网+”背景下,针对教学目标单一、教学与科研相对分离、课程体系相对混乱的问题,本研究提出要进行教学目标改革,培养创新应用型人才。教学模式创新改革可以按照“课程+专业+学科”及“教学+竞赛+科研”的总体思路,推动GIS专业开发类课程的全面优化与整合;探索课程体系建设,构建GIS开发类课程群的“四类一体”课程体系。实践表明,GIS开发类课程群建设取得了较好的效果,很大程度上促进了学生端正学习态度,提高了学生的自主学习与科研创新能力,形成了具有良性循环特征的GIS开发类课程教学体系。

基于GIS的农田墒情管理系统应用研究

以农田土壤墒情监测过程和数据分析与管理过程为研究对象,建立农田土壤墒情监测和数据分析过程模型,对当前农田土壤墒情监测过程中的不足进行分析,并结合无线网络传输技术和GIS地理信息技术构建农田墒情管理系统功能模块,实现土壤墒情数据采集、分析处理及管理输出。农田墒情管理系统运行结果表明:系统能够实时快速对农田土壤含水量进行监测,同时能够对土壤水分含量数据动态变化过程进行管理,便于土壤水分含量变化趋势的预测。