A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Development of Accident Prediction Model under Mixed Traffic Conditions:A Case Study

Accident prediction models are developed under mixed traffic conditions.Two models have been developed.The first model is a city based traffic accident prediction model.City population and vehicle ownership are the two parameters used to develop the model.A case study of Surat city in Gujarat is taken up.Total accident occurred in the city are regressed with population and vehicle ownership.Second model is the urban arterial based accident prediction model.Past accident record of ring road of Surat city shows that there are eight different locations on a ten kilometer stretch of ring road where the accidents took place consistently.These locations are picked up as accident spots.As there are many contributing factors and causes to road accidents.A comprehensive study of road safety found that human error was the sole cause in 57%of all accidents and was a contributing factor in over 90%.Keeping this in view a new term driver-pedestrian index is used to develop this model.Regression function of Microsoft excel is used for model development.Both the models are checked with R-statistics and t-statistics further the models are validated by using statistical goodness of fit(chi square test).Hence these models can be used to predict number of accidents in future subjected to the same geometric standards.Keeping this in mind improvement measures can be taken up by the district authorities.

Injury patterns of seniors in traffic accidents: A technical and medical analysis

AIM:To investigate the actual injury situation of seniors in traffic accidents and to evaluate the different injury patterns.METHODS:Injury data,environmental circumstances and crash circumstances of accidents were collected shortly after the accident event at the scene.With these data,a technical and medical analysis was performed,including Injury Severity Score,Abbreviated Injury Scale and Maximum Abbreviated Injury Scale.The method of data collection is named the German InDepth Accident Study and can be seen as representative.RESULTS:A total of 4430 injured seniors in traffic accidents were evaluated.The incidence of sustaining severe injuries to extremities,head and maxillofacial region was significantly higher in the group of elderly people compared to a younger age(P<0.05).The number of accident-related injuries was higher in the group of seniors compared to other groups.CONCLUSION:Seniors are more likely to be involved in traffic injuries and to sustain serious to severe injuries compared to other groups.

Study of vehicle accident reconstruction based on the information of the tire marks

The tire mark is the important legacy information left at the accident scene. Based on the vehicle collision dynamics model, this study provided an optimized algorithm with vehicle final location and other related information for the tire marks. When the tire marks simulation results fit the real one well, the state of vehicle can be understood as the real state in the accident. Based on above, the vehicle velocity and direction are decided. According to the velocity and direction of the vehicle, the complete accident process can be simulated. With the help of the Pc-Crash software, the method has been applied in typical collision accident cases analysis. The reconstruction results will provide the scientific and numerical references for vehicle collision accidents analyzing and appraising.

Road Traffic Accidents (RTAs) Trends on Kathmandu-Bhaktapur Road after Addition of Lanes

Road traffic accidents are the outcome of the factors associated with the traffic system namely road users, road environment and vehicles. Despite good road surface, the Kathmandu-Bhaktapur road has high accident records. The traffic police record shows that 1530 accidents have occurred from July 2009 to June 2012. The area of study of this research is the Kathmandu-Bhaktapur road which starts at Tinkune Kathmandu and ends at Suryabinayak with a length of 9.1 kilometer, a section of Araniko highway heading towards China. The road is the first ever six lane road constructed in Nepal. The objectives of this research work are to identify locations with high accident numbers, to investigate possible causes of accidents, and to propose countermeasures for traffic safety along the Kathmandu-Bhaktapur road.

An Investigation on Safety Performance Assessment of Close-Following Behavior of Heavy Vehicle Using Empirical-Simulation Technique

One of the main causes of rear-end crashes is attributed to close-following and hazardous driving behavior. A study was conducted to investigate the close-following behavior of heavy vehicle under various heavy vehicle categories, travel speeds and gross vehicle weights (GVW). Investigation is based on data obtained from simulation and empirical observations. A safety performance assessment of close-following behavior of heavy vehicles by using empirical-simulation technique is proposed. The simulation, which incorporates vehicle dynamics, is to generate the minimum safe time gap (MSTG) for truck-following-car situations. MSTG is defined as the minimum time required by the following vehicle to decelerate and stop without hitting the leading vehicle when both leading and following vehicles apply the emergency brakes. Based on comparison between the actual time gap data and the MSTG, a safety performance assessment technique that considers vehicle type, vehicle braking characteristics, truck GVW and speed is proposed for truck-following-car situation.

Analysis of Road Traffic Accident Costs in Sudan Using the Human Capital Method

In this study, we used the Human Capital (HC) accident analysis method, to determine the road traffic accident costs in Sudan in two successive years (2010 and 2011) with slight modifications to the recommended and known framework in the way it handles currently and future accident cost components. We evaluated and compared the significance and impact of the economic loss caused by road traffic accidents in Sudan using detailed information on road traffic accident casualties, classified by severity level, vehicle type, and other key parameters such as discount rates and medical and insurance information for Sudan in its entirety. The total cost of road traffic accidents in Sudan in 2010 was estimated at US $391 million, which represents 0.57% of the Gross Domestic Product (GDP), while in 2011 the cost was calculated to reach US $413 million, representing 0.62% of GDP. Findings show that the amount of accident costs is estimated to a certain extent at less than 1% of the total GDP of the country in the two estimation years, but we believe that the evaluation process used fulfilled the eligibility criteria of HC studies and that the produced values for Sudan are valid and reliable. Unit costs for each crash severity level were also estimated in the two years such as death, disability, serious injury, slight injury, and vehicle damage. Death or fatality was equal to US $38,932 and 39,508;disability was equal to US $43,113 and US $45,165;serious injury was equal to US $6963 and US $7596;slight injury was equal to US $2570 and US $3198 and vehicle damage only was equal to US $2268 and US $2579 in the assessment years 2010 and 2011, respectively.

Traffic accidents of autonomous vehicles based on knowledge mapping:A review

As a characteristic representative of the new generation of vehicles,autonomous driving is expected to improve people's driving experience.The study on traffic accident of autonomous vehicles(AVs)helps provide suggestions for autonomous driving safety from multiple disciplines and perspectives,and provide support for formulating traffic accident treatment schemes.Knowledge mapping,as a cutting-edge research method in bibliometrics,scientifically and objectively displays the relevant research status using visual means.This paper uses CiteSpace 6.1.r3 to analyze 5068 related literature on the Web of Science database from 1991 to 2022 and finds out major thematic clusters,important documents and representative journals according to citation frequency.The results show that research on traffic accidents involving AVs focuses on accident preventing technologies,including how to avoid collisions,track lane-position,and enhance vehicle-toeverything(V2X)communication.This paper extracts the mean research topics and key points involved in the field and illustrates journals related to AVs and traffic accidents,which provides guidance for subsequent researchers to carry out in-depth research and contribute their papers.Popular journals are in disciplines of mathematics,systems,computer,economics,and social science.This paper also suggests scholars to consider the aspects of scene reconstruction,cause analysis,and injury of vulnerable road users,so as to investigate traffic accidents and put forward effective treatment schemes to reduce AV accidents,and ultimately improve road safety.

Vehicle Operating, Accident and User Time Costs in Pavement Management Systems： Approach for Portuguese Conditions

This paper presents a description and analysis of the most important models to predict each of the Road User Costs components （Vehicle Operating Costs, Accident Costs and Value of Time） and proposes a model for estimating RUC components suitable for the Portuguese road network. These results are part of a research which aimed to obtain a Road User Cost Model to be used as a tool in road management systems. This model is different from other models by the fact that it includes a simple formulation that allows calibration and calculation of cost parameters, for any year, in a simple and fast way, providing trustworthy results. The required data is already available in Portuguese institutions, allowing periodic revision of cost parameters to insure accuracy.

Automobile Crash Investigation Based on Vehicle System Related Causes: Systematic Literature Review

Automobile accidents are one of the leading causes of death worldwide. Every year, over 1.24 million people are killed in traffic accidents. Even though automobiles are designed to help people, they have been used to kill them in large numbers. Automobile accident research has primarily focused on past tragedies to develop and implement policies to combat this pandemic. The aim of this systematic review is to assess the different methods used to investigate the vehicle system-related cause factors of road traffic accidents. Police report reports have served as a foundation for providing historical facts about the causes of automobile accidents. It has been observed that police reports have limitations when it comes to reporting the involvement of vehicle systems in causing a traffic accident. The majority of the research was conducted on articles that investigated vehicle system risk factors using statistical data. Following articles that used statistical data to investigate vehicle system risk factors, the inclusion criteria were chosen. Articles on traffic accidents published in Cameroon were included on the condition that they studied at least one traffic accident risk factor. Two hundred twenty-five distinct records were identified, and 155 full texts were screened for inclusion, resulting in the inclusion of 25 studies in the review. According to the findings, failure to break the braking system, tyre puncture, poor driving, speeding, and overtaking are the leading causes of automobile crash reports reported by police. The majority of the study’s conclusions lamented that accusing vehicle systems was based on assumptions and the reporter’s judgment. It was determined that the use of stringent vetting procedures to investigate vehicle systems is the cause of a traffic accident. As a result, stakeholders will require accurate facts from a traffic crash investigation.

考虑建成环境的电动自行车事故严重程度致因分析

为探究考虑建成环境影响下,电动自行车交通事故严重程度的影响因素,本文从事故属性、骑行者属性、对象车辆及驾驶员属性、道路属性及建成环境属性这5个方面,选取18个影响电动自行车交通事故严重性的潜在变量。在此基础上,构建考虑均值及方差异质性的随机参数Logit模型,利用边际效应量化显著变量对事故严重程度的影响差异。基于北京市近5年电动自行车事故抽样数据进行实证研究,结果表明:事故时段19:00-次日7:00、骑行者年龄大于40岁、重(大)型货车、到最近医院的距离增大及恶劣天气等因素会增加电动自行车事故严重程度。建成环境属性中,到最近医院的距离在死亡事故中的参数为服从正态分布的随机参数,路段及恶劣天气会增大其均值异质性,驾驶员年龄为(40,60]岁会增大其方差异质性;其他属性中,一般城市道路在受伤事故中的参数为服从正态分布的随机参数,路段会增大其均值异质性。研究结果可以为降低电动自行车事故严重程度提供理论支撑。

建成环境对交叉口行人事故严重程度异质性影响

为探索建成环境及其他因素对行人事故伤害严重程度的影响,通过建立均值和方差异质性随机参数Logit模型对交叉口行人事故严重程度进行异质性分析。利用行人碰撞事故数据,从行人、驾驶员、车辆、道路、环境、时间、建成环境7个方面筛选出27个影响因素,通过弹性系数分析显著变量对事故严重程度的影响程度。结果表明:地铁站可达性为“存在”是随机参数,车辆状态为“其他”会减小该随机参数的均值,降低交叉口行人事故严重程度;方差与“下午”显著相关,此变量会使随机参数的离散程度增加,分布变宽,随机性增加;不同用地类型与交叉口类型对行人事故严重程度的影响具有显著差异,用地类型为商业区、地铁站的可达性为“存在”时,交叉口行人发生交通事故的概率与伤害严重程度降低;行人有不当行为等因素显著增加了交叉口行人事故严重程度。研究结果为制定交叉口建成环境的优化改善措施提供参考和依据。

人车碰撞事故中人地碰撞损伤研究进展

为了解人车碰撞事故中人地碰撞损伤的研究进展,并对可行的人地碰撞损伤防护方法做出展望。本文从人车碰撞事故特征、人体损伤评价指标、人体损伤来源、人地碰撞损伤影响因素及人地碰撞损伤防护方法5个方面回顾了已有研究成果,并对已有研究中存在的问题进行讨论,就人地碰撞防护方法的发展作出展望。人地碰撞损伤研究仍然存在许多不成熟的地方,特别是人地碰撞损伤的致伤机理和影响因素方面仍须开展深入的研究。通过回顾现有的人地碰撞损伤防护技术指出,未来可从优化车辆前部形状、安装行人安全装置以及控制车辆制动等方面来降低行人损伤风险。大部分事故中碰撞速度为中低速,而在低车速下的人地碰撞损伤不容忽视,可通过控制车辆制动降低人地碰撞损伤。此外,人地碰撞损害评价指标仍存在不足。本文可为后续更好地开展人地碰撞损伤致伤机理及防护方法的研究提供参考。

江苏省重点营运车辆技术管理现状研究

近年来,江苏省内发生多起道路运输事故。调查表明,事故发生与涉事车辆的安全技术状况均有一定的直接关系。因此,对于交通运输管理部门来说,加强道路运输企业安全监管,督促企业认真执行道路运输车辆技术管理各项标准、规范和制度就显得尤为重要。本文从车辆技术状况抽检情况、车辆检验检测信息系统应用情况、事故发生与车辆技术状况抽检对比分析、车辆技术状况管理情况四个方面对2021年度江苏省车辆技术检测情况进行分析,归纳出车辆技术状况检测与管理中存在的主要问题,并提出相应的管理措施和发展建议。

基于集成学习的交通事故严重程度预测研究与应用

目前自动驾驶技术重点是关注如何主动避免碰撞,然而在面对其他交通参与者入侵而导致不可避免的碰撞事故场景时,预测车辆在不同行驶模式下的碰撞严重程度来降低事故严重程度的研究却很少。为此,提出一种双层Stacking事故严重程度预测模型。基于真实交通事故数据集NASS-CDS完成训练,模型输入为车辆传感器可感知得到的事故相关特征,输出为车内乘员最高受伤级别。在第1层中,通过实验对不同学习器组合进行训练,最终综合考虑预测性能以及耗时挑选K近邻、自适应提升树、极度梯度提升树作为基学习器;在第2层中,为降低过拟合,采用逻辑回归作为元学习器。实验结果表明,该方法准确率达到85.01%,在精确率、召回率和F1值方面优于其他个体模型和集成模型,该预测结果可作为智能车辆决策规划模块先验信息,帮助车辆做出正确的决策,减缓事故损害。最后阐述了模型在L_(2)辅助驾驶与L_(4)自动驾驶车辆中的应用,在常规车辆安全防护的基础上进一步提升车辆的安全性。

考虑建成环境的交通事故严重程度致因交互效应研究

为探究考虑建成环境影响下各类因素对交通事故的作用机理,本文提出一种融合ADASYN(Adaptive Synthetic Sampling)平衡算法与CatBoost模型的方法,对沈阳市2015—2020年的道路交通事故进行研究,并解析事故致因的交互效应。首先,通过地理信息匹配的方法补充事故地点周围14项建成环境因子,构建多源数据集。其次,通过比较4种经典的机器学习模型,即CatBoost,Random Forest,XGBoost,LightGBM,并筛选出泛化能力最强的模型。随后,利用SHAP(Shapley Additive Explanation)归因方法对最优模型进行解释以揭示单个风险因素效应以及影响重要度排序。最后,基于单因素分析,探究建成环境与事故特征之间的交互效应。研究表明:相同的特征在单因素以及双因素交互分析中对事故影响机制存在差异。在单因素分析中,季节、交通方式这2项因素对致命事故具有显著的正向影响;而主干路密度、快速路密度、工业用地比例、现场形态、道路物理隔离这5项因素对致命事故有着显著的负向影响。在双因素交互分析中,高主路密度与秋冬季节交互以及低工业用地比例与春季交互等对致命事故具有正向影响;而高工业用地比例与行人交互则产生了负向影响。本文成果可为相关人员提供准确的影响交通事故严重程度的相关因素,为优化和建设城市交通系统提供一定的理论支撑。

计及交通事故影响的电动汽车路径规划和充电导航策略

针对交通事故对电动汽车用户驾驶和充电体验的影响尚未得到充分研究这一现状,提出了一种弱化交通事故对用户不良影响的路径规划和充电导航策略。首先,以电动汽车用户重点关注的行驶能耗和行驶时间两项指标为导向,建立了基于实时交通信息的交通网综合道路阻抗模型,实现了交通流拥塞水平的动态表征。然后,考虑交通流量和道路拓扑的耦合作用,建立了基于交通事故“发生-持续-消散”动态过程的后果评估模型,实现了交通事故后果的精准量化。最后,建立了以提升电动汽车用户体验为目标的路径规划和充电导航优化模型,提出了基于Dijkstra算法的滚动优化算法,实现了模型的快速求解。以配电网与交通网组成的耦合系统进行算例分析,结果表明,所提方法能够有效减少交通事故发生后的电动汽车用户综合出行成本,并缓解交通网拥塞。

道路交通事故处置安全管控措施探讨

针对车辆交通事故类型多样、事故突发、调度力量多、救援危险性大、易引发次生灾害的5个特点,深入分析并归纳总结了造成消防救援人员伤亡的3方面原因,包括风险研判不足、阵地设置不当、安全措施不当等,并进一步提出交通事故处置过程中力量调派、人员分工、安全评估、现场警戒、救人排险、现场清理6个重点环节的安全管控措施。

苜蓿叶立交交织区冲突特征及严重程度影响因素分析

为明确城市快速路苜蓿叶立交交织区的冲突特征及冲突严重程度的关键影响因素,以重庆市北环立交为研究对象,使用无人机拍摄交织区车辆自然驾驶视频。搭建基于YOLOX和Deep-SORT的车辆目标检测和追踪框架,从航拍视频中获取10483条车辆轨迹数据,根据交互车辆的相对位置提取纵向和侧向冲突样本,并基于二维拓展碰撞时间指标将冲突事件划分为轻微、一般和严重;考虑包括宏观交通流参数和车辆微观运动参数等17个解释变量,计算多元Logistic回归模型、随机森林模型和CatBoost模型的评估指标,并分别选择对纵向冲突和侧向冲突识别性能更优的模型,进一步分析影响交织区内冲突严重程度的关键影响因素。结果表明,侧向冲突是苜蓿叶立交交织区的主要冲突类型,冲突持续时间较纵向冲突更长,碰撞风险更高;一般冲突在交织区内分布范围最广,严重冲突其次,轻微冲突分布最集中,主要分布于合流三角区附近;不同解释变量对冲突严重程度的影响程度存在一定差异,纵向严重冲突与相对速度差和目标车长度等6种指标显著相关,对于侧向冲突,重要性前5的变量分别是相对速度差、平均车头间距、目标车速度、目标车横向位置及目标车纵向位置,且当相对速度超过20 km·h^(-1),车速超过60 km·h^(-1)及平均车头间距低于12 m时,侧向碰撞风险将大幅增加。研究成果可对苜蓿叶立交交织区危险驾驶行为预警系统的设计和主动交通安全管理提供依据。

人工智能时代自动驾驶中的注意义务

如果在一场自动驾驶汽车导致的事故中有人受伤甚至死亡,要考虑自动驾驶汽车生产者的刑事责任,其他可能的责任人是汽车的所有人和司机。对于自动驾驶汽车生产者的注意义务,要求助于过失犯的一般性规定,产品责任方面公认的原则要得到运用。自动驾驶汽车所有人对该汽车有监督义务并且必须确保交通处于安全状态。对于完全自动型的自动驾驶汽车而言,司机有义务监督启动巡航定速后的危险速度,还具有对自动驾驶汽车开始行驶前运行能力的监督义务。遵守民事责任原则并非不重要,但民事过失责任与刑事过失责任通常只有一些不重要的区别,法人可能不承担刑事责任。应提高对责任而言必要的过失的程度,并考虑只将对重要注意义务的违反提升为刑法非难的对象,以及保留明确规定的故意和过失构成要件的刑事责任。