Assessing the Potential Impacts of Connected Vehicles: Mobility,Environmental, and Safety Perspectives

The connected vehicle is a rapidly emerging paradigm aimed at deploying and developing a fully connected transportation system that enables data exchange among vehicles, infrastructure, and mobile devices to improve mobility, enhance safety, and reduce the adverse environmental impacts of the transportation systems. This study focuses on micromodeling and quantitatively assessing the potential impacts of the connected vehicle (CV) on mobility, safety, and the environment. To assess the benefits of CVs, a modeling framework is developed based on traffic microsimulation for a real network located in the city of Toronto, Canada, to mimic communication between enabled vehicles. In this study, we examine the effects of providing real-time routing guidance and advisory warning messages to CVs. In addition, to take into account the rerouting in nonconnected vehicles (non-CVs) in response to varying sources of information such as apps, global positioning systems (GPS), variable message signs (VMS), or simply seeing the traffic back up, the impact of fraction of non-CV vehicles was also considered and evaluated. Therefore, vehicles in this model are divided into; uninformed/unfamiliar not connected (non-CV), informed/familiar but not connected (non-CV) that get updates infrequently every 5 minutes or so (non-CV), and connected vehicles that receive information more frequently (CV). The results demonstrate the potential of connected vehicles to improve mobility, enhance safety, and reduce greenhouse gas emissions (GHGs) at the network-wide level. The results also show quantitatively how the market penetration of connected vehicles proportionally affects the performance of the traffic network. While the presented results are pertinent to the specifics of the road network modeled and cannot be generalized, the quantitative figures provide researchers and practitioners with ideas of what to expect from vehicle connectivity concerning mobility, safety, and environmental improvements.     

网联环境下高速公路辅助驾驶车辆编队评估

为评估智能网联环境下高速公路辅助驾驶车辆编队的效果，首先基于V2X （Vehicle to Everything）和智能驾驶人模型（Intelligent Driver Model，IDM）对网联环境下的车辆跟驰行为进行建模，并对其进行参数校准；其次从安全性评价指标和通行效率两方面构建编队效果评价体系；然后通过VISSIM和VBA联合仿真，改变编队的车道、交通流量、网联车渗透率等变量进行试验。仿真结果表明，网联环境下车辆辅助驾驶编队在不同层面对于安全性与效率性都有提升；最后以不同期望速度在网联环境和非网联环境下分别进行实车辅助驾驶编队试验，以验证评价指标体系以及仿真试验的有效性。其中，实车试验结果显示，期望速度为70 km·h^-1时，网联环境下的辅助驾驶编队通行效率比非网联环境提升56%，90 km·h^-1时提升37.2%，110 km·h^-1时提升39.8%。通过与仿真试验结果对比，表明网联环境下车辆辅助驾驶编队对交通流安全性有一定程度的提升。     

智能网联混合交通流交叉口控制：研究进展与前沿

交叉口是城市道路交通运行的瓶颈点，是造成交通拥堵的问题所在。交通控制是调控交通流、预防和缓解交通拥堵的关键策略，在效费比上具有较大优势。智能网联、自动驾驶技术的发展催生了常规车辆(Regular Vehicle, RV)、网联车辆(Connected Vehicle, CV)和智能网联车辆(Connected and Automated Vehicle, CAV)组成的智能网联新型混合交通流，推动着城市道路交通控制对象、数据环境和控制手段的变革，为交通控制提出巨大挑战的同时，也为交通控制理论方法的创新发展创造了新的条件。智能网联混合交通流交叉口控制已成为国内外研究热点，尚处于研究起步阶段。根据路权特征，先从单点交叉口、干线交叉口和路网多交叉口3个层面梳理智能网联混合交通流环境下的共用设施交叉口控制研究，包括交通信号配时、车辆轨迹/路径规划以及车辆轨迹-信号配时协同控制。然后介绍自动驾驶专用设施交叉口控制研究，包括CAV专用车道、CAV专用路段、CAV专用区域和快速公交-CAV混合专用车道。通过对现有成果的梳理发现：虽然新型混合交通流交叉口控制研究取得了部分进展，但RV驾驶行为的随机性、...     

Assessment of the effectiveness of connected vehicle weather and work zone warnings in improving truck driver safety

Improving work zone safety remains a prime challenge for the transportation sector in the United States. In particular, the frequency and severity of work zone crashes involving large trucks in rural freeways are alarming. Lack of compliance with the instructions provided at work zones results in increased crash risk. In-vehicle advanced warning systems enabled by Connected Vehicle (CV) technology have the potential to prompt appropriate driver response, make navigation more predictable, and improve overall work zone safety. This study falls under the umbrella of the WYDOT Connected Vehicle Pilot Program and seeks to investigate the impacts of the Pilot's real-time weather and work zone notifications on the behavior of truck drivers in rural freeway work zone settings under poor visibility. Twenty professional truck drivers participated in this simulator study. The driving scenarios were designed to mimic the driving conditions experienced on Wyoming Interstate 80. Findings suggest that exposure to the CV notifications has promising safety benefits manifested in improved driver behavior and response. Furthermore, both the weather and work zone notifications acquired high approval from the participants in terms of usefulness and ease of understanding. Nonetheless, the display of multiple work zone warnings on the Human Machine Interface may had introduced little to moderate distraction for some participants. Overall, this study brings forth valuable lessons that are being funneled to support informed decision making to enhance the Pilot's existing Human Machine Interface design.     

隧道与互通出口小净距路段换道可靠性研究

为分析高速公路隧道与互通出口小净距路段在不同交通流状况下的车辆驶出概率,提出了基于交通仿真的安全换道概率模型。首先,采用VISSIM标定仿真模型并进行正交试验,获取小净距路段在不同净距长度、交通量、驶出比例、大型车比例下的交通数据,在此基础上确定瞬时交通流密度及相应车流平均速度的计算方法,构建相应的分布模型,通过K均值聚类算法研究不同速度下的瞬时交通流密度大小和出现概率;同时引入可靠度方法并利用微分法来构建车辆安全换道概率模型,综合考虑车速、车流密度、目标车道临界可插入间隙等因素的不确定性,应用蒙特卡罗仿真法搭建求解概率模型的算法,并通过MATLAB对模型进行求解;针对分流车初始位置的不同,分别得到了不同交通量、大型车比例、净距长度下的换道驶出成功率,进而研究不同交通流状况组合下的净距长度。结果表明：交通量、大型车比例、净距长度对净距路段内侧车道车辆换道驶出成功率有显著性影响,研究结果可为规范的进一步完善提供参考。     

多车道高速公路路侧交通标志遮挡概率研究

为了计算不同交通量、不同运行车速情况下,多车道高速公路路侧交通标志视认中大型车对小型车的动态遮挡概率,将内侧车道小型车与外侧车道大型车车头间的垂直距离作为判断路侧交通标志遮挡的依据,根据视距几何关系确定多车道高速公路驾驶人在视认区域内视线被遮挡的最大和最小临界距离;建立路侧交通标志遮挡模型,根据视认距离确定内侧及外侧车道仿真路段长度,以0.1 s为仿真步长,借助VISSIM交通仿真软件获取车辆车头坐标、与前车跟车距离等动态基础数据,实现高速公路交通标志遮挡概率计算过程的动态化。结果表明：外侧车道的车型、交通量、视认距离以及大小车运行速度都对路侧交通标志遮挡率有一定的影响;在交通量一定的情况下,驾驶人视线被遮挡的概率随着外侧车道大型车数量的增加而增大;在外侧车道大型车数量一定的情况下,驾驶人视线被遮挡概率随着小型车数量的增加而增大;在小型车速度一定的情况下,驾驶人视线被遮挡概率随着大型车速度的增大呈降低趋势;小型车速度增大时,驾驶人视线被遮挡的概率会有所提高。     

穿村镇公路交叉口合理间距探讨

为解决穿村镇公路由于交叉口频密造成的交通安全问题,以北京琉辛路密云县不老屯路段为例,根据驾驶员连续驾驶模型理论,以驾驶员的心生理特性为切人点,研究穿村镇公路村镇路段内交叉口的合理间距,获得在限速60 km/h的穿村镇公路上,交叉口的合理间距至少为150 m的结论,并利用模拟驾驶实验测得驾驶员的心生理数据加以验证.认为合...     

Investigating performance of a novel safety measure for assessing potential rear-end collisions: An insight representing a scenario in developing nation

Road safety is one of the major concerns in the ever-growing traffic network. In addressing this, surrogate safety measures play a critical role in identifying collision instincts. Besides the added advantage of quantifying collision instincts in advance, surrogate safety measures have their limitations. For example, in some instances, those measures tend to show erroneous results. In this paper, a new surrogate safety measure Instant Heeding Time (IHT), is presented based on follower vehicle attention in the traffic streams. This new measure is integrated with a distance gap and the vehicles' speeds to assess probable rear-end collisions. Further, along with other safety measures, the developed safety framework is tested over a study section, with the help of trajectory datasets at three traffic flow conditions (free flow, capacity, and congested) under prevailing heterogeneous (mixed) traffic conditions. Based on the safety framework, it is observed that, in the case of free flow and capacity conditions, 23 and 55 probable rear-end collisions points are detected. At the congested conditions, no rear-end collision points are observed. Further, smaller vehicles in the traffic stream are associated with a higher number of rear-end collision instincts than other vehicle categories. The conceptualized safety framework can be applied on a real-time basis for monitoring the safety measures for vehicles in a mixed traffic stream.     

基于心理安全距离的行人风险评价及预警算法研究

为实现在机非混行的交通环境下,对动态、随机弱势道路使用者的准确风险评估,基于行车安全场理论提出了考虑行人心理安全距离的碰撞行人风险评价模型.首先通过考虑行驶车辆是否会危及行人的心理安全,提出了心理安全距离的概念,包括心理安全通行距离和心理安全制动距离2个方面,并通过问卷调研挖掘其可能的影响因素进行数值分析;接着将心理安...     

视线遮挡条件下面向弱势道路使用者的避撞策略研究

由于视线障碍物造成的"鬼探头"事故已经成为当前城市道路交通事故的主要类型之一.针对汽车碰撞视线遮挡条件下横穿的弱势道路使用者(VRU)的场景,设计了1种基于碰撞时间比和安全制动距离的避撞策略,建立车辆与VRU的交通状态数学模型,分析"鬼探头"场景下的制动避撞临界距离.结合临界距离和车辆与VRU的碰撞时间比,将可以避免碰...     

基于多任务迁移学习的交通警情信息自动处理方法

从交通警情数据中自动获取信息对于快速处理交通事故和提高交通管理水平具有重要的意义。为此，提出了一种基于多任务迁移学习的交通警情信息自动处理方法，该方法上游采用文本预训练模型作为共享参数层，下游建立多任务并行学习方法，实现对交通警情中的关键信息、类型和语义自动处理。选取江苏省苏州市2年内共120 191条原始交通警情作为试验数据，通过自动处理方法构建了一套标准的交通警情信息数据库。试验结果表明：所建立的关键信息抽取方法可以更精准地提取警情数据中的时间、地址和车牌信息；交通警情分类模型性能优于现有的深度学习模型，分类准确率达93%；基于局部特征增强的警情语义分析方法重点识别了警情中事故的严重程度和救援需求，识别准确率达87%。研究结论显示交通警情自动化处理方法具有良好的可移植性和实用性。     

Behavioral aspects of safety culture: Identification of critical safety-related behaviors of motorcyclists in Indonesia's urban areas via the application of behavioral-based safety programs

Many violations and accidents involving motorcyclists occur in the urban areas of Indonesia. It can be said that the failure to develop a good traffic safety culture causes poor motorcyclist behavior, as shaped by existing programs and mechanisms. This study aimed to identify motorcyclists' critical behaviors by conducting investigations using the reciprocal safety culture model as a framework. We tried to identify and clarify the safe behaviors expected by local governments from the existing driving safety program. By applying the antecedent-behavior-consequence model of the behavioral-based safety program, we obtained sixty-three behaviors associated with the six criteria of safe driving. We surveyed motorcyclists (N = 97) to review the sixty-three motorcyclist behaviors in the urban area. The relationship between the behavioral and psychological aspects of the reciprocal safety culture model was investigated to obtain the motorcyclists' critical behaviors. Multiple linear regression model, optimized by the stepwise regression, described the influence motorcyclist behavior on the perception of driving safety. We identified eight critical safety-related behaviors engaged in by motorcyclists. Observation revealed some cultural issues embedded in motorcyclists' eight critical safety-related behaviors that need to be intervened by the local government. The reciprocal safety culture model could be applied in the behavioral-based safety program to approach traffic safety culture issues. In order to develop a good traffic safety culture in the urban area, the local government needs to review the existing driving safety program by understanding drivers' behaviors as they relate to such a program.     

公路绿化对行车安全的典型影响及其评价

为全面分析公路绿化在安全方面的合理性,研究了绿化导致的典型行车安全问题,包括平曲线内侧绿化对行车视距的影响;中央分隔带绿化植物株距和高度对防眩、横向通视、植物存活率等的影响;大冠径常绿类植物对道路净空、驾驶员心理的影响;绿化遮挡交通标志或高速公路出入口对行车产生的误导现象;立交匝道及其出入口绿化对行车诱导、出口缓冲及入...     

制动与转向协调动作的车辆避撞控制研究（双语出版）

为了弥补现有汽车避撞控制策略以及碰撞风险评价指标单一的不足，提出转向和制动协调的主动避撞控制系统。首先规划了五次多项式换道路径，在对其理论分析的基础上得到转向临界避撞距离和与目标车道车辆的安全距离约束。其次，考虑道路附着系数和系统延迟的影响，基于制动过程给出制动临界避撞距离，并以纵向行驶安全系数ξ和碰撞时间倒数T^-1_TC划分安全行驶区域，利用驾驶人实车跟车数据标定稳态跟随/定速巡航区域的阈值。随后，通过转向/制动临界避撞距离的对比给出2种避撞方式的安全收益范围。最后搭建Simulink/CarSim联合仿真模型，并对其进行不同初始条件下的避撞仿真试验。研究结果表明：转向操作在制动距离不足时仍是有效的；当主车高速近距离接近静止前车时，主车可以顺利采取转向换道动作，而常规ACC系统在2.5 s处的车间相对距离为-0.76 m，事实上已经发生了碰撞；当相邻车道前车与主车纵向间距不满足换道安全距离约束时，避撞控制系统进入紧急制动模式，最大制动减速度达到-0.8g（g为重力加速度），实际最小车间距为5.1 m；通过转向和制动的协调动作，充分发挥了车辆的避撞潜力；ξ和T^-1_TC指标的融合，可以更好地评估碰撞风险并实现不同控制模式的转换，在保证行车安全的同时可避免过分制动给乘客造成的紧张感。     

高速公路作业区汇入提示标志设置研究

考虑驾驶员在作业区上游过渡车道上行驶的过程中,车辆可汇入相邻车道的临界间隙的变化情况,减少作业区警告区末端由于汇入产生的冲突,提出设置汇入提示标志。利用M3分布模型与间隙接受理论,通过微分方法得到次车道上车辆的汇入概率模型。利用该概率模型,得到了在不同交通流状态下的汇入提示标志设置距离,同时对影响汇入概率的交通流参数进行了分析。计算结果表明：当自由流比例及车速均相同时,设置距离随交通流量增大而增大;而当车速与交通流量均相同时,设置距离随自由流比例增大而减小;当自由流比例与交通流量均相同时,设置距离随车速增大而增大。因此应结合作业区的限速值进行汇入提示标志的设置。     

高速公路交通安全设施工程造价审查分析

随着道路使用者对其附属设施——交通安全设施要求的提高,交通安全设施费用占高速公路项目总投资的比重加大,交通安全设施造价审查日益受到重视。系统地分析了交通安全设施工程在工可、初步设计、招标、交竣工等不同阶段中的造价审查,探讨提出适合交通安全设施的造价审查思路和方法。     

山区公路平曲线路段动态限速与预警方案

为了提高山区公路平曲线路段的行车安全性,从几何线形指标、路面状况条件与车辆动力学分析推导出临界侧滑速度与纵向行驶临界安全速度计算公式。将临界车速作为安全行驶的约束条件,提出不同路面状况、能见度条件与交通环境下动态限速值计算方法与行车安全控制标准,并考虑到驾驶员接收速度预警信息后驾驶操作过程,从预警设备组合、工作流程与对策3方面提出速度预警方案。研究成果可为山区公路交通安全预警技术提供支持。     

基于网联车辆轨迹数据的周期排队长度估计

近年，基于网联车辆轨迹数据的交通管控与服务研究方兴未艾。其中，信号控制交叉口排队长度估计备受关注。然而，在低渗透率条件下，单个周期内轨迹稀少且提供的交通信息十分有限。现有研究仅以当前周期内网联车辆轨迹数据为输入，难以获得准确且可靠的周期级排队长度估计结果。因此，融合利用历史网联车辆轨迹数据提供的车辆到达和停车位置信息以及当前周期内实时观测的网联车辆排队信息，提出一种基于最大后验概率的周期最大排队长度估计方法。首先，依据历史轨迹数据的停车位置信息，估计排队长度的先验分布；其次，依据历史轨迹数据的车辆到达信息，估计周期内车辆的历史到达分布，并结合周期内最后1辆排队网联车辆的到达时刻与停车位置，构建排队长度似然函数；最后，基于贝叶斯理论，结合前述先验分布与似然函数，推导周期排队长度的后验分布，并采用最大后验概率方法实现周期最大排队长度的估计。仿真结果表明：所提方法在不同饱和度和渗透率条件下，均优于现有的方法；即使在车辆轨迹数不超过1 veh·周期^-1的低渗透率条件下，所提方法的平均绝对估计误差也不超过2 veh·周期^-1。实证结果表明：在渗透率仅为8.96%的条件下，所提方法的平均绝对误差为2.12 veh·周期^-1，平均相对估计误差为12.4%，同样优于现有同类方法。     

基于车道线虚线角点检测的行车安全视距测算模型

开展行车视距调查对于营运期公路安全评价至关重要,这对车载条件下行车视距检测提出了要求.针对现有基于车道线图像特征点所构建的视距模型精确度不高的问题,提出了1种以车道线虚线角点为关键特征的行车安全视距测算模型.在车载设备获取的图像预处理基础上,采用轮廓跟踪法对车道线虚线轮廓进行提取,通过设定轮廓尖锐度阈值以实现对车道线虚...