改进的混合高斯与YOLOv2融合烟雾检测算法

提出一种融合了改进的混合高斯和YOLOv2的烟雾检测算法。首先,针对烟雾的早期特征对混合高斯算法进行改进,有效框定动态目标感兴趣区域,提取出烟雾前景;在此基础上将烟雾检测转换为回归问题,利用端对端目标检测算法YOLOv2训练烟雾数据集,进行二次检测和筛选,最终框定出烟雾发生区域的具体位置和范围,满足对不同场景火灾烟雾的有效检测。实验结果表明,融合算法改善了烟雾区域的检测效果,提高准确性并有效降低烟雾误检率。     

浅析桥面危险液泄漏收集系统设计

桥梁跨越江河等水源地保护区,一旦有运输危险液体的货车在桥上发生交通事故,危险液体就随桥面排水系统流入水源地保护区,污染水体。某市某湘江大桥桥位于市二级饮用水源保护区范围之内,大桥建设后营运期的影响主要是桥梁上发生交通事故,导致危险化学品及有害物品泄漏排入湘江的风险事故。以本工程为例,危险品运输车辆发生事故时危险品泄漏量概率为小概率事件,不可预见,发生的最不利时间点,即事故发生时,同时暴雨出现时,雨水径流量混合危险液,量大。设计的收集系统将桥面危险液导流至桥头岸边危险液体收集池,收集处理,达标排放。     

比例图分析方法在道路交通事故分析中的应用

随着道路车辆日益增多，道路交通事故日趋严重，而弄清事故的发生过程，准确划分事故责任是交通管理部门所面临的很大问题。事故发生后如何快速、准确分析事故发生过程，这也是目前从事交通事故司法鉴定部门所面临的难题。针对交通事故中的这一特征，本人通过多年从事交通事故司法鉴定工作中总结出，应用比例图分析法在实际分析交通事故中有较高的实用价值，分析结果往往快捷、准确。     

事故树图形的计算机辅助绘制算法研究

提供了一种有效的算法,根据输入的各种事件的基本信息及其因果逻辑关系,利用树的深度优先遍历后序算法,实现事故树的自动绘制,体现事故树模型分析形象、直观、明了的特点.该算法能即时计算出事故树顶事件发生的概率、最小割集、概率重要度、关键重要度等参数,为对事故树进行定性、定量分析提供强有力的图形和数据支持.     

公路事故风险动态预警检测设备布局的优化方法

针对现有公路事故风险动态预警检测设备布局方案无法满足当前道路承载力条件和降低交通事故发生频率的问题,本文进行公路事故风险动态预警检测设备布局优化方案研究。通过公路事故风险动态预警路段划分、构建初始检测点集、基于AHP的设备布局节点重要度评估,实现公路事故风险动态预警检测设备初始点位集构建与重要度计算方法。通过建立检测设备多目标优化布局模型、基于模拟退火算法的布局优化求解,提出一种新的优化方法。将该方法应用于实际可以有效提升道路承载能力,并减少甚至避免交通事故发生。     

基于海因里希事故致因理论的道路交通事故案例分析

目的运用事故致因理论分析实际道路交通事故案例。方法结合轨迹交叉理论,对海因里希事故致因理论的基本模型进行改进。以2017年8月10日发生在京昆高速公路西安方向秦岭一号隧道南口的特大交通事故为案例,运用改进后的海因里希事故模型对事故进行分析。结果 (1)驾驶人疲劳驾驶、夜间驾驶是造成事故的直接原因,乘客未系安全带是造成事故伤害极其严重的重要原因;(2)驾驶人安全意识和责任意识严重忽视、车辆管理者(公司)安全意识和责任意识的忽视、乘客对交通安全的自我规范自觉执行的法规意识的缺失,是造成事故及事故严重伤害的深层次因素。结论通过分析,折射出对预防道路交通事故前端管理的重要性,预防道路交通事故教育、道路交通事故主动防御势在必行且任重道远。     

基于眼动跟踪的驾驶员疲劳检测

驾驶疲劳是引发交通事故的主要原因之一,如果可以实时监测驾驶员的疲劳状态,在疲劳发生时给予警告,可以避免大量交通事故的发生。本文主要介绍了几种基于眼动跟踪的驾驶员疲劳检测的基本算法,并进行了比较和评述。     

交通事故所影响的路段车辆排队长度的预测模型

本文以2013年全国大学生数学建模竞赛A题为背景，分析出交通事故所影响的路段车辆排队长度与事故横断面实际通行能力、事故持续时间、路段上游流量间的关系。     

基于YOLOv3和DeepSort的车流量检测

针对传统多目标跟踪算法的检测跟踪精度低、鲁棒性差的缺点,基于经典的Tracking-By-Detection模式,提出一种基于YOLOv3和DeepSort的车流量检测方法,实现了车辆视频监控端到端的车流量视频的实时监测与跟踪计数。采用深度学习YOLOv3算法检测视频车辆目标,然后利用深度学习DeepSort算法对检测到的车辆进行实时跟踪计数。实验结果表明该方法应对快速移动的车辆和环境光照的影响时,对车流量的检测效果良好,平均精度达到94.7%,端到端的算法可行且有效,适用于对车辆视频的批处理。     

车道被占用对城市通行能力的影响

交通事故导致车道被占用将直接引起车辆排队,出现堵塞,使道路通行能力降低,本文主要研究交通事故造成车道被占用对通行能力的影响。首先我们将大小不同的车标准化,统计出事故发生前后每个时间段内通过发生事故横截面的车流量。然后将道路情况划分为通畅段与拥堵段,对于畅通期间,建立多车道通行能力模型计算实际通行能力,车道占用期间则用车流量表示通行能力。最后作图分析实际通行能力与时间的关系,得出结论。     

面向人体损伤的载货车-摩托车事故再现研究

面向人体损伤的交通事故再现主要依据事故遗留下的刹车印迹、车身及其他相关物体变形、人体损伤等多种信息。在此基础上利用数值模拟技术获得碰撞前的速度及接触位置,结合多刚体动力学和人体损伤分析等理论方法得出人体损伤部位的生物力学数值。通过上述方法对一起车-摩托车碰撞事故案例进行实际应用,详细介绍了多刚体模型的建立步骤,及碰撞的接触,计算得到数值模拟结果与法医鉴定结果吻合,从而通过使用上述方法可以为交通事故责任鉴定提供理论依据和数值参考,同时可以对法医勘验结果给出合理解释。     

基于边缘的背景差法在车流量检测中的应用

针对视频车流量检测容易受车辆阴影和车辆变道影响的问题,笔者提出了一种基于边缘信息的背景差车流量检测方法.该方法利用边缘信息作为车辆的检测特征,实时自动提取和更新背景边缘并采用动态开窗的方式来进行车辆计数.实验结果表明,与传统背景差法相比,该方法受车辆阴影和车辆变道影响较小,检测准确率达97.3%,是一种实用有效的车流量检测方法.     

Risk factors associated with traffic violations and accident severity in China

With the recent economic boom in China, vehicle volume and the number of traffic accident fatalities have become the highest in the world. Meanwhile, traffic accidents have become the leading cause of death in China. Systematically analyzing road safety data from different perspectives and applying empirical methods/implementing proper measures to reduce the fatality rate will be an urgent and challenging task for China in the coming years. In this study, we analyze the traffic accident data for the period 2006–2010 in Guangdong Province, China. These data, extracted from the Traffic Management Sector-Specific Incident Case Data Report, are the only officially available and reliable source of traffic accident data (with a sample size >7000 per year). In particular, we focus on two outcome measures: traffic violations and accident severity. Human, vehicle, road and environmental risk factors are considered. First, the results establish the role of traffic violations as one of the major risks threatening road safety. An immediate implication is: if the traffic violation rate could be reduced or controlled successfully, then the rate of serious injuries and fatalities would be reduced accordingly. Second, specific risk factors associated with traffic violations and accident severity are determined. Accordingly, to reduce traffic accident incidence and fatality rates, measures such as traffic regulations and legislation—targeting different vehicle types/driver groups with respect to the various human, vehicle and environment risk factors—are needed. Such measures could include road safety programs for targeted driver groups, focused enforcement of traffic regulations and road/transport facility improvements. Data analysis results arising from this study will shed lights on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other regions.     

Difficulties with quasi-induced exposure when speed varies systematically by vehicle type

The attractiveness of quasi-induced exposure lies in the simplistic nature of its theory and application. As opposed to vehicle miles of travel, quasi-induced exposure is developed solely from the accident data themselves. Involvement ratios (IRs) are used to describe the relative over- or under-involvement of different driver-vehicle combinations in traffic accidents. The issue of systematic bias in the involvement ratios is explored, and it is shown both theoretically and empirically that the variation in average speeds between vehicle types can affect relative accident involvement ratios. For vehicle types that routinely travel faster, the IRs will likely be underestimated; while for slower-moving vehicle types, the IRs will be overestimated. In the case of speed, the magnitude of the effect on the IRs is dependent both on the magnitude of the speed differential and the percentage of slower vehicles in the traffic stream. Conclusions can be extended to whenever there are speed or other behavior disparities associated with the driver-vehicle combinations in the traffic stream. Other examples include the speed discrepancy caused by different drivers (e.g., younger versus older drivers). Caution must be used in interpreting results from applications of the quasi-induced technique whenever such biases might be encountered.     

The development of an automatic method of safety monitoring at Pelican crossings

This paper reports on the development of a method for automatic monitoring of safety at Pelican crossings. Historically, safety monitoring has typically been carried out using accident data, though given the rarity of such events it is difficult to quickly detect change in accident risk at a particular site. An alternative indicator sometimes used is traffic conflicts, though this data can be time consuming and expensive to collect. The method developed in this paper uses vehicle speeds and decelerations collected using standard in situ loops and tubes, to determine conflicts using vehicle decelerations and to assess the possibility of automatic safety monitoring at Pelican crossings. Information on signal settings, driver crossing behaviour, pedestrian crossing behaviour and delays, and pedestrian-vehicle conflicts was collected synchronously through a combination of direct observation, video analysis, and analysis of output from tube and loop detectors. Models were developed to predict safety, i.e. pedestrian-vehicle conflicts using vehicle speeds and decelerations.     

Factors influencing the probability of an incident at a junction: results from an interactive driving simulator

Using data generated from a fixed-base interactive driving simulator, which was used to evaluate a driver decision aid, a model is built to predict the probability of an incident (i.e. an accident or a ‘near miss’) occurring as a result of a right-turn across left-hand traffic at an unsignalised junction. This can be considered to be the product of two separate probabilities, the first being the probability that the gap between a pair of vehicles in the traffic stream is accepted, and the second the probability that the time needed to cross the on-coming stream of traffic causes the time-to-collision with the nearest vehicle in this traffic stream to be less than a second. The model is developed from the results of experimental trials involving a sample of drivers, the majority of whom were aged 60 years or older, in order to demonstrate the effect of various parameters on these probabilities. The parameters considered include the size of the gap between successive vehicles, vehicle characteristics such as size, colour and velocity, driver characteristics such as age and sex, and both daytime and night-time conditions.     

Image tracking of motorcycles and vehicles on urban roads and its application to traffic monitoring and enforcement

Abstract

Image tracking has increasingly gained attention for use in vision‐based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real‐time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.     

拆除爆破飞散物防护工程实例研究

对拆除爆破飞散物进行分类,分析爆破飞散物事故情景,识别拆除爆破飞散物事故危险有害因素。本文运用反映飞散物运动规律的经验公式和一次拆除爆破方案的设计数据,估算了飞散物抛射初速度和最大水平抛射距离,根据计算结果采取了有针对性的爆破飞散物防护措施,取得了良好的防护效果;还提出了避免拆除爆破飞散物事故的对策,并绘出其鱼刺图。     

Tobit analysis of vehicle accident rates on interstate highways

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.     

Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong

A population-based case-control study was conducted to examine factors affecting the severity of single vehicle traffic accidents in Hong Kong. In particular, single vehicle accident data of three major vehicle types, namely private vehicles, goods vehicles and motorcycles, which contributed to over 80% of all single vehicle accidents during the 2-year-period 1999-2000, were considered. Data were obtained from the newly implemented traffic accident data system (TRADS), which was developed jointly by the Transport Department, Police Force and Information Technology Services Department, Hong Kong. The effect of district, human, vehicle, safety, environmental and site factors on injury severity of an accident was examined. Unique risk factors associated with each of the vehicle types were identified by means of stepwise logistic regression models. For private vehicles, district board, gender of driver, age of vehicle, time of the accident and street light conditions are significant factors determining injury severity. For goods vehicles, seat-belt usage and weekday occurrence are the only two significant factors associated with injury severity. For motorcycles, age of vehicle, weekday and time of the accident were determined to be important factors affecting the injury severity. Identification of potential risk factors pertinent to the particular vehicle type has important implications to relevant official organisations in modifying safety measures in order to reduce the occurrence of severe traffic accidents, which would help to promote a safe road environment.