高速公路连续长大下坡交通事故与线形特征分析

连续长大下坡路段安全问题突出,大型重载货车失控事故频现,在对连续长大下坡路段交通事故数据和道路设计指标调查的基础上,分析了连续长大下坡路段交通事故特性与车辆运行特性,分析了平曲线半径与事故率的关系,运用数理统计方法建立了平均纵坡与事故率的回归模型.分析结果表明,连续长大下坡路段的事故原因是不同车型间速度差过大,部分车头间距不满足80 km/h的停车视距要求,平曲线曲率越大、平均纵坡越大事故率越高.     

道路因素对典型较严重道路交通事故严重性的影响分析

基于道路交通事故数据探究事故影响因素对于认识事故的影响因素、提高交通安全水平具有重要意义。利用近年来国内典型较严重道路交通事故数据,应用泊松模型和负二项模型,以区分事故形态的方式建立追尾事故、侧碰事故及撞行人事故的事故死亡率的道路影响因素分析模型。这些模型以三类事故中涉及人员的死亡数为因变量,以一系列道路因素为自变量,将事故涉及人数作为偏移变量。模型的具体形式以过离散系数及赤池信息量准则(AIC)为依据进行选择。结果显示,追尾事故的死亡率与道路等级、路侧防护设施显著相关;侧碰事故则与天气、路表情况、路口路段位置、坡度以及道路结构有关;撞行人事故与路表情况、道路等级、车道数、平曲线半径有关。本文拓展了事故严重性研究的深度,其研究成果对于更好地利用重特大事故的深入调查数据有现实意义,也可为事故分析及道路设计等提供借鉴。      

半挂汽车列车高速公路弯道下坡路段运行安全研究（双语出版）

为提升半挂汽车列车在高速公路弯道下坡路段的运行安全，采用TruckSim仿真软件，构建了车辆模型、道路模型和驾驶人动力学仿真模型；基于蒙特卡罗可靠性分析法，分别建立了半挂汽车列车发生侧滑失效、侧翻失效、折叠失效和系统失效的功能函数，并选取设计速度80 km·h^-1的高速公路为研究路段，通过进行大量车辆动力学仿真试验，对不同圆曲线半径、纵坡坡度、路面附着系数、车速和车辆总质量对半挂汽车列车的运行安全的影响进行了数值分析。研究结果表明：半挂汽车列车发生侧滑和侧翻的概率随着圆曲线半径的增加而显著降低，在一般最小半径400 m的情况下，半挂汽车列车发生侧滑失效和侧翻失效的概率趋近于0；随着下坡坡度的增加，半挂汽车列车发生侧滑失效和侧翻失效的概率基本呈线性增长趋势；车速对于半挂汽车列车运行安全的影响尤为显著，当车速均值由60 km·h^-1增加到90 km·h^-1时，发生侧滑失效和侧翻失效的概率分别增加了634倍和336倍；车辆总质量的增加对半挂汽车列车侧翻有显著影响；在路面附着系数较低的条件下，半挂汽车列车的主要事故形态为侧滑和折叠，在路面附着系数较高的情况下，半挂汽车列车的主要事故形态为侧翻。因此，在道路设计中，应避免极限最小半径与陡坡组合，严格限速和限载可确保半挂汽车列车的运行安全性能。     

山区高速公路隧道路段与开放路段的事故影响因素分析

高速公路隧道构造特殊且通行环境复杂,因而通常事故多发。为探究高速公路隧道路段与开放路段事故影响因素和严重程度致因机理的差异,采集沪昆高速邵怀段2011—2016年期间1 537起事故为研究样本;以事故发生路段为响应变量构建逻辑回归模型,解释各种风险因素对事故发生路段倾向性的影响差异;分别针对隧道路段与开放路段建立模型研究事故伤害严重程度的影响因素。建立二元Logit回归模型分析事故的发生倾向性和2类路段的事故严重程度的影响因素;采用随机参数Logit模型以反映异质性条件对参数的影响。统计表明:与疲劳驾驶、未保持安全距离相关的事故发生在隧道路段的概率更高,其事故发生概率分别是开放路段的2.373和2.482倍;与隧道路段事故严重程度正相关的因素包括下坡（坡度2%以上）、夏季和超速行驶,其中下坡（坡度2%以上）段的严重事故发生的概率为上坡（坡度2%以上）的3.397倍,夏季的严重事故发生概率为秋季的3.951倍,超速行驶相关的严重事故发生概率为其他不当驾驶行为的4.242倍;与开放路段事故严重程度正相关的因素包括超速行驶和疲劳驾驶,其中超速行驶相关的严重事故概率是其他不当驾驶行为的2.713倍,疲劳驾驶相关的严重事故概率是其他不当驾驶行为的4.802倍。研究表明,山区高速公路隧道路段与开放路段的事故发生概率及其严重程度的影响因素存在一定的差异性,研究结论可为山区高速公路差异管理方案制定提供依据。      

泉南高速公路柳南段事故黑点鉴别及组合因素影响分析

针对泉南高速公路柳南段交通事故，采用累计频率法对道路黑点进行鉴别，曲线中累计频率大于95.0%路段有12处，即为事故黑点（段）。结合贝叶斯定理，建立了道路联合概率分布模型，以泉南高速公路柳南段94.1 km的184起交通事故数据，进行模型检验，结果表明:大雾天气时道路小半径平曲线处发生事故概率最大，约37.3%；大雨天气时12∶00～18∶00时间段发生事故概率次之，约25.7%，其中大部分事故发生在时间段12∶00～15∶00；晴天时大半径平曲线处发生事故概率最小，占事故总数约4.5%。     

高速公路连续下坡路段线形指标与视觉特性关系研究

高速公路连续下坡路段平、纵线形指标组合及相邻分路段线形指标是否一致,对行车驾驶员视觉有较大的影响,从而影响行车安全。本文应用雅泸高速公路一段12 km长连续下坡路段,将其制作成驾驶模拟舱里的试验路段,采集驾驶模拟舱里做行车试验驾驶员的视觉指标数据,通过分析,建立线形指标与视觉特性之间关系模型,最终获得了不同的平曲线半径对驾驶员视觉构成不同的压力,不同的分路段线形指标对驾驶员视觉也产生不同的压力,这些成果可用于评价高速公路连续下坡路段线形设计质量。     

高填方路基沉降的泊松模型预测方法应用

根据高填方路基沉降的发展规律,建立了泊松曲线预测模型。结合工程实例,证实了泊松曲线能很好地反映高填方路基的沉降变化过程,该模型预测结果与实测沉降值十分接近。     

半挂汽车列车高速公路弯道下坡路段运行安全研究

为提升半挂汽车列车在高速公路弯道下坡路段的运行安全,采用TruckSim仿真软件,构建了车辆模型、道路模型和驾驶人动力学仿真模型;基于蒙特卡罗可靠性分析法,分别建立了半挂汽车列车发生侧滑失效、侧翻失效、折叠失效和系统失效的功能函数,并选取设计速度80 km·h~(-1)的高速公路为研究路段,通过进行大量车辆动力学仿真试验,对不同圆曲线半径、纵坡坡度、路面附着系数、车速和车辆总质量对半挂汽车列车的运行安全的影响进行了数值分析。研究结果表明:半挂汽车列车发生侧滑和侧翻的概率随着圆曲线半径的增加而显著降低,在一般最小半径400 m的情况下,半挂汽车列车发生侧滑失效和侧翻失效的概率趋近于0;随着下坡坡度的增加,半挂汽车列车发生侧滑失效和侧翻失效的概率基本呈线性增长趋势;车速对于半挂汽车列车运行安全的影响尤为显著,当车速均值由60 km·h~(-1)增加到90 km·h~(-1)时,发生侧滑失效和侧翻失效的概率分别增加了634倍和336倍;车辆总质量的增加对半挂汽车列车侧翻有显著影响;在路面附着系数较低的条件下,半挂汽车列车的主要事故形态为侧滑和折叠,在路面附着系数较高的情况下,半挂汽车列车的主要事故形态为侧翻。因此,在道路设计中,应避免极限最小半径与陡坡组合,严格限速和限载可确保半挂汽车列车的运行安全性能。     

高速公路连续下坡路段线形质量评价方法研究

针对高速公路连续下坡路段交通事故频繁发生,而设计规范对该类路段线形设计又没有制定特别标准的状况,通过分析高速公路连续下坡路段线形指标的特点构造线形质量评价参数,通过收集国内多条高速公路10个连续下坡路段的线形几何指标、交通事故数、交通量等数据,应用统计分析方法,建立了连续下坡路段线形评价参数与亿车公里事故率之间的关系模型,通过分析线形评价参数与亿车公里事故率之间关系曲线的拐点及事故多发的阈值,确定了线形质量评价参数的行车安全区间,为高速公路连续下坡路段线形设计提供指导。     

基于行驶轨迹的双车道公路弯道路段交通安全特性研究

针对双车道公路曲线路段碰撞事故高发的特点,选取某双车道公路5个简单平曲线,实测弯道路段车辆行驶轨迹,分析大货车、大客车、小货车和小客车等主要车型在上行、下行方向的轨迹中线偏移量,研究不同车型的行驶轨迹偏移特性.通过测定不同车型在不同半径平曲线行驶的轨迹交叉面积,建立车型、平曲线半径与行驶轨迹交叉面积关系模型,为双车道公...     

Modeling injury severity of crashes involving trucks: Capturing and exploring risk factors associated with land use and demographic in addition to crash,driver, and on-network characteristics

Nearly 499,000 motor vehicle crashes involving trucks were reported across the United States in 2018, out of which 22% resulted in fatalities and injuries. Given the growing economy and demand for trucking in the future, it is crucial to identify the risk factors to understand where and why the likelihood of getting involved in a severe or moderate injury crash with a truck is higher. The focus of this research, therefore, is on developing a methodology, capturing and integrating data, exploring, and identifying risk factors associated with surrounding land use and demographic characteristics in addition to crash, driver, and on-network characteristics by modeling injury severity of crashes involving trucks. Crash data for Mecklenburg County in North Carolina from 2013 to 2017 was used to develop partial proportional odds model and identify risk factors influencing injury severity of crashes involving trucks. The findings indicate that dark lighting condition, inclement weather condition, the presence of double yellow or no-passing zone, road sections with speed limit >40 mph and curves, and driver fatigue, impairment, and inattention have a significant influence on injury severity of crashes involving trucks. These outcomes indicate the need for effective geometric design and improved visibility to reduce the injury severity of crashes involving trucks. The likelihood of a severe or moderate injury crash involving a truck is also high in areas with high employment, government, light commercial, and light industrial land uses. The findings can be used to identify potential risk areas, proactively plan and prioritize the allocation of resources to improve safety of transportation system users in these areas.     

基于负二项分布的高速公路交通事故影响因素分析

为分析高速公路交通事故的影响因素,构建基于负二项分布的事故分析模型,探究事故数与交通特性、公路线形及路面性能间关系.鉴于传统固定参数模型难以刻画各因素对事故风险影响的异质性,引入了随机参数建模方法.结果表明:相比于固定参数负二项模型,构建的随机参数负二项模型有更好的拟合优度,且能更合理地反映各因素对事故的作用效果;将随...     

一种用于货车的坡度提示系统

针对大型货车驾驶员对道路坡度把握不准确而容易导致长大下坡路段出现制动器失效的问题,提出一种用于货车的坡度提示系统。该系统采用陀螺仪实时探测货车所处道路的坡度,并实时显示,当检测到货车连续下坡超过一定长度且没有采取制动时,系统提示驾驶员适当制动,以避免后期车速加大而频繁制动导致制动器失效。经实际验证本系统能有效给驾驶员提示,对减少交通事故有一定实际应用价值。     

自然驾驶状态下重型工程车驾驶人驾驶稳定性分析

重型工程车行驶过程中事故风险大,发生恶性事故的概率高,易造成重大生命和经济损失,其运输安全管理问题面临挑战.为探究重型工程车驾驶人驾驶稳定性与相关影响因素之间的关系,开展重型工程车自然驾驶试验,提取车辆运动学、道路条件、驾驶人状态和工作时间等数据;采用速度均值和速度标准差表征驾驶人驾驶稳定性,以睡眠模式、道路线形、道路...     

Crash prediction model for two-lane rural highways in the Ashanti region of Ghana

Crash Prediction Models (CPMs) have been used elsewhere as a useful tool by road Engineers and Planners. There is however no study on the prediction of road traffic crashes on rural highways in Ghana. The main objective of the study was to develop a prediction model for road traffic crashes occurring on the rural sections of the highways in the Ashanti Region of Ghana. The model was developed for all injury crashes occurring on selected rural highways in the Region over the three (3) year period 2005–2007. Data was collected from 76 rural highway sections and each section varied between 0.8 km and 6.7 km. Data collected for each section comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM) with Negative Binomial (NB) error structure was used to estimate the model parameters. Two types of models, the ‘core’ model which included key exposure variables only and the ‘full’ model which included a wider range of variables were developed. The results show that traffic flow, highway segment length, junction density, terrain type and presence of a village settlement within road segments were found to be statistically significant explanatory variables (p < 0.05) for crash involvement. Adding one junction to a 1 km section of road segment was found to increase injury crashes by 32.0% and sections which had a village settlement within them were found to increase injury crashes by 60.3% compared with segments with no settlements. The model explained 61.2% of the systematic variation in the data. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads. It is recommended that to improve safety, highways should be designed to by-pass village settlements and that the number of junctions on a highway should be limited to carefully designed ones.     

Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia

This study aims to determine risk factors contributing to traffic crashes in 9,176 fatal cases involving motorcycle in Malaysia between 2010 and 2012. For this purpose, both multinomial and mixed models of motorcycle fatal crash outcome based on the number of vehicle involved are estimated. The corresponding model predicts the probability of three fatal crash outcomes: motorcycle single-vehicle fatal crash, motorcycle fatal crash involving another vehicle and motorcycle fatal crash involving two or more vehicles. Several road characteristic and environmental factors are considered including type of road in the hierarchy, location, road geometry, posted speed limit, road marking type, lighting, time of day and weather conditions during the fatal crash. The estimation results suggest that curve road sections, no road marking, smooth, rut and corrugation of road surface and wee hours, i.e. between 00.00 am to 6 am, increase the probability of motorcycle single-vehicle fatal crashes. As for the motorcycle fatal crashes involving multiple vehicles, factors such as expressway, primary and secondary roads, speed limit more than 70 km/h, roads with non-permissible marking, i.e. double lane line and daylight condition are found to cause an increase the probability of their occurrence. The estimation results also suggest that time of day (between 7 pm to 12 pm) has an increasing impact on the probability of motorcycle single-vehicle fatal crashes and motorcycle fatal crashes involving two or more vehicles. Whilst the multinomial logit model was found as more parsimonious, the mixed logit model is likely to capture the unobserved heterogeneity in fatal motorcycle crashes based on the number of vehicles involved due to the underreporting data with two random effect parameters including 70 km/h speed limit and double lane line road marking.     

长大下坡货车制动器温度模型

为了研究在道路长大下坡上载重货车制动器热衰减的温度曲线,应用能量守恒理论建立了载重货车在发动机制动和排气制动时制动器温度预测模型.通过在高速公路长大下坡路段进行制动器测温试验,得到了制动器在不同制动方式、载重时的连续升温数据和连续上坡时的连续降温数据;同时通过室内台架试验,得到了载重货车发动机功率曲线.最后通过试验数据...     

高速公路平面线形与安全关系的探讨

建立线形指标、交通量与事故间的模型是当前事故规律微观研究的主要方法，虽然在模型中纳入更多的指标能够提高的解释能力，但增加了模型的复杂性，加剧了数据采集困难．简洁的模型有时候在分析特定类型事故时反而更具优势，因此，作者在研究高速公路线形条件与事故的关系时，主要提取了平面线形的圆曲线、缓和曲线和超高等指标，重点分析平面线形与安全的关系。作者首先对国内外有关平面线形与安全关系的研究进行了简要回顾，利用贵州省贵黄、贵新两务高速公路的事故、线形、交通量数据建立了回归模型。此外，还结合具体案例，对曲线超高对行车安全的影响进行了剖析，并提出了一些针对平面线形安全问题的具体措施和建议。     

Predicting downgrade crash frequency with the random-parameters negative binomial model: Insights into the impacts of geometric variables on downgrade crashes in Wyoming

Road deaths, injuries and property damage place a huge burden on the economy of most nations. Wyoming has a high crash rate on mountain passes. The crash rates observed in the state is as a result of many factors mainly related to the challenging mountainous terrain in the state, which places extra burden on drivers in terms of requiring higher levels of alertness and driving skill. This study was conducted to investigate factors leading to crashes on Wyoming downgrades, with a focus on geometric variables. Traditionally, crash frequency analysis is conducted using count models such as Poisson or negative binomial models. However, factors that affect crash frequency are known to vary across observations. The use of a methodology that fails to take into account heterogeneity in observed and unobserved effects relating to roadway characteristics can lead to biased and inconsistent estimates. Inferences made from such parameter estimates may be misleading. This study employed the random-parameters negative binomial regression models to evaluate the impact of geometric variables on crash frequency. Five separate models were estimated for total, fatal/injury, property damage only (PDO), truck, and non-truck crash frequencies. Several geometric and traffic variables were found to influence the frequency of crashes on downgrades. These included segment length, vertical grade, shoulder width, lane width, presence of downgrade warning sign, vertical curve length, presence of a passing lane, percentage of trucks, number of lanes and AADT. The results suggest that segment length, lane width, presence of a passing lane, presence of a downgrade warning sign, vertical grade, and percentage of trucks are best modeled as random parameters. The findings of this study will provide transportation agencies with a better understanding of the impact of geometric variables on downgrade crashes.