Trip Purposes of Automobile Users Inference Using Multi-day Traffic Monitoring Data

Determining trip purpose is an important link to explore travel rules. In this paper,we takea utomobile users in urban areas as the research object,combine unsupervised learning and supervised learningm ethods to analyze their travel characteristics,and focus on the classification and prediction of automobileu sers’trip purposes. However,previous studies on trip purposes mainly focused on questionnaires and GPSd ata,which cannot well reflect the characteristics of automobile travel. In order to avoid the multi-dayb ehavior variability and unobservable heterogeneity of individual characteristics ignored in traditional traffic questionnaires,traffic monitoring data from the Northern District of Qingdao are used,and the K-meansc lustering method is applied to estimate the trip purposes of automobile users. Then,Adaptive Boosting(AdaBoost)and Random Forest(RF)methods are used to classify and predict trip purposes. Finally,ther esult shows:(1)the purpose of automobile users can be mainly divided into four clusters,which includeC ommuting trips,Flexible life demand travel in daytime,Evening entertainment and leisure shopping,andT axi-based trips for the first three types of purposes,respectively;(2)the Random Forest method performss ignificantly better than AdaBoost in trip purpose prediction for higher accuracy;(3)the average predictiona ccuracy of Random Forest under hyper-parameters optimization reaches96.25%,which proves the feasibilitya nd rationality of the above clustering results.

On-line Popularity Monitoring Method Based on Bloom Filters and Hash tables for Differentiated Traffic

Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking(CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters(SBF) and Counting Bloom filters(CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40 Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.

Real-time vehicle tracking for traffic monitoring systems

A real-time vehicle tracking method is proposed for traffic monitoring system at road intersections,and the vehicle tracking module consists of an initialization stage and a tracking stage. License plate location based on edge density and color analysis is used to detect the license plate region for tracking initialization. In the tracking stage,covariance matching is employed to track the license plate. Genetic algorithm is used to reduce the computational cost. Real-time image tracking of multi-lane vehicles is achieved. In the experiment,test videos are recorded in advance by recorders of actual E-police systems at several different city intersections. In the tracking module,the average false detection rate and missed plates rate are 1. 19%,and 1. 72%,respectively.

Study on Monitoring and Analysis of TSP Caused by Road Traffic in Binzhou City

Wind speed,temperature,relative humidity and TSP concentration at three intersections in Binzhou City were monitored,and the relationships of TSP concentration with wind speed,temperature,relative humidity and traffic flow at the three intersections in Binzhou City were analyzed by using SPSS.The results show that traffic flow was the main factor affecting TSP concentration of road traffic in Binzhou City.

Two States CBR Modeling of Data Source in Dynamic Traffic Monitoring Sensor Networks

Real traffic information was analyzed in the statistical characteristics and approximated as a Gaussian time series. A data source model, called two states constant bit rate (TSCBR), was proposed in dynamic traffic monitoring sensor networks. Analysis of autocorrelation of the models shows that the proposed TSCBR model matches with the statistical characteristics of real data source closely. To further verify the validity of the TSCBR data source model, the performance metrics of power consumption and network lifetime was studied in the evaluation of sensor media access control (SMAC) algorithm. The simulation results show that compared with traditional data source models, TSCBR model can significantly improve accuracy of the algorithm evaluation.

ICT Devices: Vital Tools for Enhancing Road Traffic Monitoring

Road Traffic monitoring involves the collection of data describing the characteristic of vehicles and their movement through road networks. Such data may be used for one of these purposes such as law enforcement, congestion and incident detection and increasing road capacity. Transportation is a requirement for every nation regardless of its economy, political stability, population size and technological development. Movement of goods and people from one place to another is crucial to maintain strong economic and political ties between the various components of any given nation among nations. However, there are different modes of transportation and the most paramount one to human beings is road transportation. Due to increase in the modes of transportation, road users encounter different problems such as road blockage and incidents. Therefore there is need to monitor users incidents and to know the causes. Road traffic monitoring can be done manually or using ICT devices. This paper focuses on how the use of ICT devices can enhance road traffic monitoring. It traces the brief history of transportation;it equally discussed road traffic and safety, tools for monitoring road traffic, Intelligent Transportation Systems (ITS) use for traffic monitoring and their benefits. The result shows that the use of ICT devices in road traffic monitoring should be a Millennium Goal for all developed and developing countries because of its numerous advantages in the reduction of the intensity of traffic and other road incidents.

An Improved Histogram Equalization Method in the Traffic Monitoring Image Processing Field

To process the traffic monitoring image, a local Histogram Equalization method based on fuzzy mathematics was proposed in this paper. In this paper, firstly, we define a function to measure the similarity degree of two images. Then, a suitable Gaussian fuzzy distribution function was chose to generate a 3 × 3 matrix of influential factors. In order to reduce the artificial boundaries, we combined the 3 × 3 influential matrix with a 3 × 3 smooth filter matrix to get the final smooth-influ- ence matrix. Finally, the smooth-influence matrix was used to process the center block image. The simulation results demonstrated that the proposed method can reduce time consumption while improving the image contrast and can get satisfactory results.

A Scalable Architecture for Network Traffic Monitoring and Analysis Using Free Open Source Software

The lack of current network dynamics studies that evaluate the effects of new application and protocol deployment or long-term studies that observe the effect of incremental changes on the Internet, and the change in the overall stability of the Internet under various conditions and threats has made network monitoring challenging. A good understanding of the nature and type of network traffic is the key to solving congestion problems. In this paper we describe the architecture and implementation of a scalable network traffic moni-toring and analysis system. The gigabit interface on the monitoring system was configured to capture network traffic and the Multi Router Traffic Grapher (MRTG) and Webalizer produces graphical and detailed traffic analysis. This system is in use at the Obafemi Awolowo University, IleIfe, Nigeria;we describe how this system can be replicated in another environment.

Cars as a Diffuse Network of Road-Environment Monitoring Nodes

The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and operative on commercial cars. Real sensors and car sub-systems (e.g. thermometers, accelerometers, ABS, ESP, and GPS) together with other “implicit” sensors (e.g. fog lights, windscreen wipers) acquire and contain information. They are shared inside an in-vehicle communication network using mainly the standard CAN bus and can be collected by a simple central node. This node can also be available on the market without too expensive costs thanks to some companies which business is devoted to car fleet monitoring. All the collected data are then geolocalized using a standard GPS receiver and sent to a remote elaboration unit, exploiting mobile network technologies such as GPRS or UMTS. A large number of cars, connected together in a diffuse Wireless Sensor Network, allow the elaboration unit to realize some info-layers put at the disposal of a car driver. Traffic, state of the road and other information about the weather can be received by car drivers using an ad hoc developed mobile application for smartphone which can give punctual information related to a specific route, previously set on the mobile phone navigator. The description of some experimental activities is presented, some technical points will be addressed and some examples of applications of the network of cars “as sensors” will be given.

Design of a d_(33)-mode piezocomposite electricity generating element and its application to bridge monitoring

The piezoelectric effect is used in sensing applications such as in force and displacement sensors.However,the brittleness and low performance of piezoceramic lead zirconate titanate(PZT) often impede its applicability in civil structures which are subjected to large loads.The concept of a piezocomposite electricity generating element(PCGE) has been proposed for improving the electricity generation performance and overcoming the brittleness of piezoceramic wafers.The post-curing residual stress in the PZT layer constitutes a main reason for the PCGE's enhanced performance,and the outer epoxy-based composites protect the brittle PZT layer.A d33-mode PCGE designed for bridge monitoring application was inserted in a bridge bearing to provide a permanent and simple weigh-in-motion system.The designed PCGEs were tested through a series of tests including fatigue and dynamic tests to verify their applicability for monitoring purposes in a bridge structure.A simple beam example was presented to show the applicability of the proposed bridge bearing equipped with the PCGE for adequately measuring the traffic loads.

基于改进DV-HOP的道路交通拥堵传感节点快速监测

由于现有交通拥堵监控设备在海量三维交通信息中处理数据的能力较差,导致监测目标延迟较高,故设计一种基于改进DV-HOP的道路交通拥堵传感节点快速监测方法;在待监测区域安置无线视觉传感器,划分子节点与Sink节点,采集车辆通行状况和整体长度;把异常道路数据作为小概率事件,确立速率采集周期及交通状态采集周期,推算历史车辆速率均值和交通数据方差,设定拥堵临界值,分析路段是否产生拥堵;对道路交通拥堵节点进行初始化,确定全部道路交通拥堵节点,并将其转换到二维坐标中;利用改进DV-HOP算法获取道路交通拥堵节点位置信息,得出道路交通拥堵节点监测结果;实验分析表明:设计方法的均等系数值可达0.998,数据传输延时仅为3.5 s,表明交通拥堵监测精度较高。

基于生成对抗网络的路况监控视频能见度检测方法

传统路况监控视频能见度检测方法直接对人眼可分辨最远点进行检测,未进行车道线检测及兴趣域提取,造成传统方法检测效果较差。对此,提出基于生成对抗网络的路况监控视频能见度检测方法。在车道线检测及兴趣域提取的基础上,基于生成对抗网络检测人眼可分辨最远点,进一步与计算机视觉和图形领域相结合,实现路况监控视频能见度检测。实验结果表明,该方法具有更好的检测效果,可推广应用。

流量在线监测综合测试管理平台应用研究

为提高河道流量测验精度,结合水文水情现状及发展需求,对河道流量在线监测综合测试的3方面关键技术进行了研究。一是探索符合水文特点的河道流量测验方法和测流传感器;二是制定ADCP和雷达波流量在线监测数据传输协议及数据库表结构;三是开发流量在线监测综合测试管理平台。研究结果表明,平台实现了对“分散”、“偏远”的无人值守ADCP、雷达波流量在线监测站进行统一管理与远程控制,实现设备厂家在流量在线监测领域互相兼容,便于系统建设及运行管理,有利于统一和规范流量在线监测市场,优化水文水资源监测方案,助力水文对传统水文站进行自动化、信息化、智能化改造。

基于FFmpeg多线程编码的智能交通监控系统设计

针对智能交通管理设备本身缺乏安全监管,传统视频监控延迟高、画质低、稳定性差的问题,提出一种基于FFmpeg的多线程编码视频流传输方案。通过FFmpeg调用h264_nvenc编码器,实现宏块行级的GPU多线程加速,降低编码延迟。使用Visual Studio 2019和QT15.5开发基于FFmpeg的音视频处理软件,对多路视频流进行封装、推流,并搭建Nginx流媒体服务器进行分发。通过实验表明,该系统整体的传输延迟低于1 s,且拥有良好的率失真特性,监控画面清晰、稳定性高,实现了对交通管理设备实时稳定的安全监控。

城市道路交通运行态势监控诱导系统设计研究

城市道路交通运行态势监控诱导系统,是基于对交通运行状况的实时监测,在交通诱导屏向广大交通参与者精准发布路况信息,诱导出行者选择适宜出行路线的智能交通系统。该系统还可为交通规划部门提供准确和实时的交通数据,帮助优化道路网络布局和交通设施建设,提高道路资源的利用效率,从根源上提升公安交通管理的科技信息化应用水平。

基于改进YOLOX的轻量化交通监控目标检测算法

交通目标检测技术是道路交通管理部门进行交通流量监测、安全管控等核心工作的重要技术之一。面对大量的交通监控视频数据,需要使用检测速度更快、精度更高、占用计算资源更少的交通目标检测技术。为了满足这一需求,根据YOLOX算法和PP-LCNet网络,提出了一种面向交通监控场景的轻量型交通目标检测算法PL-YOLO。使用基于PP-LCNet改进的网络作为目标检测器的主干特征网络,使用深度可分离卷积代替YOLOX中的普通卷积,降低模型运算过程中的复杂度;根据交通监控场景下的车辆分布密集且尺寸小的特点,添加SimAM注意力机制模块,聚焦于更有意义的特征图像。实验结果表明,相对于YOLOX-s模型,改进后的PL-YOLO检测精度提升1.89个百分点,模型大小降低了54%,FPS从20.88帧/s提升到26.68帧/s。

省域公路货物运价抽样监测方法

省域货物运价监测是道路运输市场管理的重要任务。依托省域公路规上货运企业,根据分层抽样理论,建立公路普通货物运价抽样监测体系。提出货物运价抽样体系的动态监测流程和最低样本量计算方法,结合省域公路货物品类比例拆分最低样本量。提出企业样本重点监测货物品类划分方法,引入拉依达准则筛选企业上报异常数据,构建每种货物品类运价报送范式。以某省份2019年运价为基价,按照行业通用的运价指数算法,验证监测方法的可行性。结果表明,规上企业的抽样比例为14.49%,保证监测置信度为90%的情况下提升监测效率;通过降档选取2个规下企业,有效补充规上企业对货物品类监测覆盖度的不足;2个地市内无法归置的货物品类比例分别为5.88%,7.69%,侧面展现了运价抽样监测体系的稳定性。

IPv6中一种基于卷积的DDoS攻击两阶段防御机制

针对IPv6快速普及背景下分布式拒绝服务(DDoS)攻击威胁不断增长的现状,提出一种两阶段的DDoS攻击防御机制,包括初期实时监控DDoS攻击发生的预检测阶段,以及告警后精准过滤DDoS攻击流量的深度检测阶段.首先,分析IPv6报文格式并解析PCAP流量捕获文件中的16进制头部字段作为样本元素.其次,在预检测阶段,引入轻量化二值卷积神经网络(BCNN),设计一种二维流量矩阵作为模型输入,整体感知网络在混杂DDoS流量后出现的恶意态势作为告警DDoS发生的证据.告警后,深度检测阶段介入,引入一维卷积神经网络(1DCNN)具体区分混杂的DDoS报文,从而下发阻断策略.在实验中,自建IPv6-LAN拓扑并基于NAT 4to6技术重放CIC-DDoS2019公开集生成纯IPv6-DDoS流量源测试.结果证明,所提机制提升针对DDoS攻击的响应速度、准确度和攻击流量过滤效率,当DDoS流量出现仅占总网络6%和10%时,BCNN就能以90.9%和96.4%的准确度感知到DDoS攻击的发生,同时1DCNN能够以99.4%准确率区分DDoS报文并过滤.