汽车驾驶操作信息数据库与采集系统设计

为提高驾驶操作监控技术研究效率 ,对驾驶操作数据、影响因素、车辆状态运行数据等进行分析并在此基础上进行了驾驶操作信息数据库概念结构、逻辑结构以及物理结构的设计。同时为提高驾驶操作数据采集的真实性 ,设计由工业控制计算机、数据采集卡、视觉传感器、力传感器、光电编码器、节气门开度传感器、传感器电路等组成车载驾驶操作信息多传感器采集实验系统 ,并分析了驾驶操作信息管理软件模块构成。     

基于系统动力学的地铁火灾调度安全模型研究

全自动驾驶已经成为城市轨道交通建设发展的必然趋势,车辆火灾场景是影响列车全自动运行安全最大的场景之一,因此制定合理的火灾调度安全控制方案具有极其重要的意义。以地铁全自动驾驶中车辆火灾场景为研究对象,将系统动力学理论方法用于构建调度安全影响因子模型。与传统的地铁安全模型不同,该模型以全自动驾驶场景为标准形成影响因子库。通过德菲尔法相关思想的专家评分法确定各子系统权重比,利用Vensim-PLE软件对模型进行仿真试验,对各影响因子进行动态预测,对比不同的安全投入方案及调度人员配置比方案,优选出最有效的火灾调度安全控制方案。     

营运驾驶员驾驶事故影响因素仿真研究

解决营运驾驶员驾驶事故频发的不安全行为问题,基于复杂适应系统（CAS）理论和多主体建模与仿真（ABMS）方法,构建营运驾驶员驾驶事故模型。通过调节车辆状况、管理者管理监督水平、营运驾驶员情绪状态、安全教育水平、驾驶经验和环境综合条件等因素,运用NetLogo仿真平台分析安全管理水平、营运驾驶员安全责任意识、心理负荷水平对驾驶事故的影响。研究表明:营运驾驶员驾驶事故的发生系统是一种典型的CAS,营运驾驶员驾驶事故是三大主体属性和行为环境交互的结果,且交互作用程度不同。因此,运输企业要考虑多种因素,采取相应的措施来降低营运驾驶员驾驶事故的发生。     

人格特征对驾驶人驾驶行为的影响研究

为了解驾驶人不安全驾驶行为背后的人格特征影响因素,回顾自2000年以来国内外人格特征与驾驶行为关系的相关研究,采用系统评价和Meta分析的优先报告项目(PRISMA)标准在国内外知名数据库检索到17 688篇文献,剔除重复文献3 160篇、不相关文献14 263篇、非优秀文献198篇,最终将67篇优秀文献纳入研究,归纳并梳理文献中不同人格特征与不安全驾驶行为的关系。结果表明：大五人格的5个人格维度与驾驶行为的关系研究结果均存在不一致;感觉寻求和冲动性各自均为不安全驾驶行为的优秀预测因子,但相较之下后者的预测能力更强;驾驶愤怒对不安全驾驶行为的直接预测能力不强;无规范感、特质焦虑、利他及自恋对均不安全驾驶行为有不同程度的影响,但相关研究较少;依恋、特质情商、集体主义和异常人格特质等人格特征受关注较少,需要更多检验;中国人样本的一些研究结果与多数研究结果存在不一致,需开展跨文化研究。     

基于层级分析法的航海人员驾驶疲劳因子分析

笔者从环境不同的基本要素切入,分析个人生理、心理和技术对航海人员驾驶疲劳因子之影响,提出以全面性的环境差别建构航海人员驾驶疲劳因子指标体系,应用层级分析法对该体系进行评价,该评价方法简单、实用,且有清晰的架构,能完整呈现专家的意见。“工作疲劳靠休息;心理压力靠抒解”,建议以正面激励的安全驾驶管理,建立航海驾驶人员疏解疲劳之途径,且鼓励船员相互砥砺并适度给予奖励,以消除船员驾驶疲劳因子产生的根源。     

自适应巡航控制系统对驾驶安全性的影响研究

为探究自适应巡航控制(ACC)系统对驾驶安全性的影响,首先通过实际道路驾驶试验获取我国典型道路交通场景,用驾驶模拟器进行场景仿真,并在有/无ACC状态下开展模拟驾驶试验;然后分析ACC系统在中国典型道路中的表现,通过对比分析ACC模式下不同特征驾驶人的碰撞时间(TTC),探讨不同类型驾驶人的应急反应。结果表明,ACC能较好地处理大多数路况;但面对危险路况时,不管是哪种类型的驾驶人,ACC的应急反应都没有手动驾驶迅速;且女性、年老和对ACC认知度低的驾驶人更容易受ACC的不良影响;驾驶人对ACC的认知度决定其ACC驾驶的安全性。     

城市交通中的智能监控应用

一、市场应用广阔 智能视觉监控系统将图像信息与其它背景知识相结合,能快速提取复杂交通环境中的有用信息,进而产生合理的行为规划与决策.在自主驾驶、行车安全、车辆监控、交通数据采集等方面都起着非常重要的作用.     

适用于环境保护领域的数据采集系统设计

环保领域无论是环保工程还是环境监测都要大量采用数据采集系统. 以MAX PLUSII设计软件为基础,选择全加器、LED数码显示和A/D转换器组成的数据采集系统.根据各部分不同的功能,分别选择了最合适的芯片,建立了数据采集的试验装置.通过在设计软件中进行仿真测试、误差分析、调试完善,完成了模拟量到数字量的转换.试验结果表明,该数据采集系统可行可靠且性能优良,可适用于环境保护和其他工业领域.     

地铁驾驶员驾驶疲劳状态监测

为监测地铁自动驾驶系统驾驶模式下驾驶员驾驶疲劳状态,以S地铁公司的驾驶员为研究对象,开展驾驶员疲劳主、客观监测研究。主观监测应用《自觉症状调查表》调查并统计分析地铁驾驶员的驾驶主观疲劳感受;客观监测应用Eegosports 64通道无线脑电肌电系统测量地铁驾驶员在各班次、各时间段的脑电(EEG)信号,并结合Matlab工具箱中的EEGLAB分析各班次驾驶员EEG中δ波的频谱图。结果表明:驾驶员驾驶疲劳总体的平均得分为1.8分,即驾驶疲劳有些明显,且晚班和夜班驾驶疲劳比白班的大,从主客观2方面说明驾驶员处于疲劳驾驶状态。     

三维煤气管网仿真系统设计与实践

以煤气地下管网为例,按照软件工程思想,采用ArcEngine平台,使用Visual Studio.NET开发工具,结合GIS、数据库、面向对象、虚拟现实、ADO.NET等技术,设计三维煤气管网仿真系统,实现了三维管网的仿真。系统建立基础地理数据库、专题数据库、属性数据库、多媒体数据库和模型库,实现地下煤气管网的基础数据采集、信息管理、三维虚拟仿真、监测预警、专题制图和综合服务等功能。研究结果表明,基于C/S和B/S混合模式的体系结构较好地实现了多源数据管理与系统集成,利用GIS和面向对象技术可进行煤气管网快速三维建模和动态虚拟仿真。     

基于驾驶员模型参数辨识的疲劳驾驶研究

提出一种利用驾驶员模型反演方法来进行驾驶员疲劳诊断研究的新方法。首先利用预瞄神经网络建立适应于复杂路况条件下的驾驶员-汽车-道路闭环模型,然后定义特定行驶轨迹内理论数据与试验数据的近似度为目标函数,将驾驶员参数的反演问题转化为多目标优化问题,采用基于实数编码混沌变异量子遗传算法的优化方法,获得全局最优解。试验中采用脑电和主观疲劳心理评测结合的方法确定被试者的疲劳状况。在每种疲劳状况下对驾驶员参数进行辨识,对结果进行统计分析表明,在考虑到车型、道路曲率等因素条件下驾驶员参数分布与驾驶员的疲劳状况有很强的相关性。     

Multi-agent traffic simulations to estimate the impact of automated technologies on safety

Abstract

Objective: The objective of this article was to develop a multi-agent traffic simulation methodology to estimate the potential road safety improvements of automated vehicle technologies.

Methods: We developed a computer program that merges road infrastructure data with a large number of vehicles, drivers, and pedestrians. Human errors are induced by modeling inattention, aimless driving, insufficient safety confirmation, misjudgment, and inadequate operation. The program was applied to simulate traffic in a prescribed area in Tsukuba city. First, a 100% manual driving scenario was set to simulate traffic for a total preset vehicle travel distance. The crashes from this simulation were compared with real-world crash data from the prescribed area from 2012 to 2017. Thereafter, 4 additional scenarios of increasing levels of automation penetration (including combinations of automated emergency braking [AEB], lane departure warning [LDW], and SAE Level 4 functions) were implemented to estimate their impact on safety.

Results: Under manual driving, the system simulated a total of 859 crashes including single-car lane departure, car-to-car, and car-to-pedestrian crashes. These crashes tended to occur in locations similar to real-world crashes. The number of crashes predicted decreased to 156 cases with increasing level of automation. All of the technologies considered contributed to the decrease in crashes. Crash reductions attributable to AEB and LDW in the simulations were comparable to those reported in recent field studies. For the highest levels of automation, no assessment data were available and hence the results should be carefully treated. Further, in modeling automated functions, potentially negative aspects such as sensing failure or human overreliance were not incorporated.

Conclusions: We developed a multi-agent traffic simulation methodology to estimate the effect of different automated vehicle technologies on safety. The crash locations resulting from simulations of manual driving within a limited area in Japan were preliminary assessed by comparison with real-world crash data collected in the same area. Increasing penetration levels of AEB and LDW led to a large reduction in both the frequency and severity of rear-end crashes, followed by car-to-car head-on crashes and single-vehicle lane departure crashes. Preliminary estimations of the potential safety improvements that may be achieved with highly automated driving technologies were also obtained.     

驾驶人视觉注意力需求与驾驶行为特性的关系

采用驾驶模拟系统平台,以不同车道类型及不同交通流状态(自由流/稳定流/不稳定流/强制流)为虚拟试验场,应用心理试验设计方法,测试得到21名被试在不同交通流状态下的视觉注意力需求及驾驶行为。对5种车道类型及4种交通流状态下被试驾驶时的视觉注意力需求特性和驾驶行为特性数据进行分析,得到不同车道不同交通流状态下的视觉注意力需求变化情况。利用多元回归方法分析了不同交通流状态下驾驶人视觉注意力需求与驾驶行为之间的关系,并构建了基于驾驶行为特性的驾驶人视觉注意力需求预测模型。结果表明,驾驶人视觉注意力需求与制动次数、油门踏板位移和车辆轨迹偏差之间存在相关关系。     

长时间单调模拟驾驶对疲劳的影响研究

通过模拟驾驶实验,综合评估长时间驾驶以及单调环境对驾驶员疲劳程度的影响是笔者研究的主要课题内容。借助于在模拟驾驶座舱上,4个健康样本分别参加高速公路(单调环境)和一般公路(非单调环境)的两组驾驶仿真实验,每组测试均持续两小时,一共进行10次实验。实验过程中,样本的操控数据(车速和方向盘转角)、反应时间、心电信号、主观疲劳状况等都同步记录并保存。实验结果表明长时间驾驶对操控能力、反应时间、心率、主观疲劳都有显著性影响(p<0.050),单调环境(高速公路)和非单调环境(一般公路)相比,车速方差区别显著,而尽管被试在高速公路的单调环境下驾驶后主观感觉更疲劳一些,但反应时间、心率等因素并没有显著性差异。     

Is road rage increasing? Results of a repeated survey

PROBLEM: We report on trends in road rage victimization and perpetration based on population survey data. METHOD: Based on repeated cross-sectional telephone surveys of Ontario adults between July 2001 and December 2003, logistic regression analyses examined differences between years in road rage victimization and perpetration in the previous year controlling for demographic characteristics. RESULTS: The prevalence of any road rage victimization in the previous year decreased significantly from 47.5% in 2001 to 40.6% in 2003, while prevalence of any road rage perpetration remained stable (31.0% to 33.6%). Logistic regression analyses revealed that the odds of experiencing any road rage victimization was 33% higher in 2001 and 30% higher in 2002, than in 2003. DISCUSSION: Survey data provide a valuable perspective on road rage trends, but efforts to track road rage incidents is also needed. SUMMARY: In Ontario, the proportion of adults experiencing any road rage victimization decreased from 2001 to 2003 while the proportion reporting any road rage perpetration remained stable. IMPACT ON INDUSTRY: None.     

雾霾时车辆尾气排放对驾驶员能见度的影响

针对北京道路车辆尾气排放对雾霾时驾驶员道路能见度的影响问题,建立了雾霾时车辆尾气排放与驾驶员道路能见度关系模型。该模型以车辆为单元建立车辆尾气排放元胞,考虑了车辆尾气排放后的污染物物理和化学变化,并以车道中的尾气排放位置截面及截面单元、交叉口处的尾气排放位置区间为模型单元。为验证该模型,于2016年10月-2017年2月和2017年10月-2018年2月,在北京地区部分路网检测了驾驶员道路能见度等数据,并统计了各时段驾驶员道路能见度的分布情况。对建立的关系模型进行仿真,结果表明,该关系模型的仿真结果与实际检测数据的误差占比平均值小于4. 98%,验证了该关系模型用于描述北京市道路车辆尾气排放对雾霾时驾驶员道路能见度影响的有效性。     

Risky, aggressive, or emotional driving: addressing the need for consistent communication in research

Problem. Researchers agree that a consistent definition for aggressive driving is lacking. Such definitional ambiguity in the literature impedes the accumulation of accurate and precise information, and prevents researchers from communicating clearly about findings and implications for future research directions. This dramatically slows progress in understanding the causes and maintenance factors of aggressive driving. Summary. This article critiques prevailing definitions of driver aggression and generates a definition that, if used consistently, can improve the utility of future research. Pertinent driving behaviors have been variably labeled in the literature as risky, aggressive, or road rage. The authors suggest that the term “road rage” be eliminated from research because it has been used inconsistently and has little probability of being clarified and applied consistently. Instead, driving behaviors that endanger or have the potential to endanger others should be considered as lying on a behavioral spectrum of dangerous driving. Three dimensions of dangerous driving are delineated: (a) intentional acts of aggression toward others, (b) negative emotions experienced while driving, and (c) risk-taking. Impact on Industry. The adoption of a standardized definition for aggressive driving should spark researchers to use more explicit operational definitions that are consistent with theoretical foundations. The use of consistent and unambiguous operational definitions will increase the precision of measurement in research and enhance authors' ability to communicate clearly about findings and conclusions. As this occurs over time, industry will reap benefits from more carefully conducted research. Such benefits may include the development of more valid and reliable means of selecting safe professional drivers, conducting accurate risk assessments, and creating preventative and remedial dangerous driving safety programs.     

Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran

Introduction: Digital billboards (DBs) are a competing factor for attracting drivers’ attention; evidence shows that DBs may cause crashes and vehicle conflicts because they catch drivers’ attention. Because of the complexity of a system that includes road conditions, driver features, and environmental factors, it is simply not possible to identify relationships between these factors. Thus, the present study was conducted to provide a well-organized procedure to analyze the effects of DBs on drivers’ behavior and measure factors responsible for drivers’ distraction in Babol, Iran, as a case study. Method: Corresponding data were collected through a Naturalistic Driving Study (NDS) of 78 participants when facing DBs (1,326 samples). These data were analyzed by applying structural equation modeling (SEM) to concurrently recognize relationships between endogenous and exogenous variables. Human, environmental, and road factors were determined as exogenous latent variables in a model to evaluate their influences on drivers’ distraction as an endogenous variable. Results: The results showed that road, environmental, and human factors reciprocally interact with drivers’ distraction, although the estimated coefficient of human factors was more of a factor than that of the other groups. Furthermore, younger drivers, beginner drivers, and male drivers (as human factors); night and unclear weather like a rainy day (as environmental factors); and installing DBs at complicated traffic positions like near-intersections (as road factors) were determined to be the main factors that increase the possibility of drivers’ distraction. Finally, model assessment was suggested using the goodness-of-fit indices.     

Evaluating the impact of criminalizing drunk driving on years of life lost due to road traffic deaths in one megacity,China

Objective: Road safety is an important public health issue worldwide. However, few studies have analyzed the association between criminalizing drunk driving and years of life lost (YLL) due to road traffic deaths (RTDs). Our study can provide useful information about this policy.

Methods: We used interrupted time-series analysis to find the changes in monthly YLL and RTD before and after law enforcement began using RTD data from 2008 to 2014 in Tianjin.

Results: After adjustment for seasonality, months, holidays, and the number of people in each district, criminalizing drunk driving was followed by a 11.1% (95% confidence interval [CI], 1.1–21.1%) reduction in risk of RTDs and a corresponding 778.1-year (95% CI, 200–1,355.1) reduction in monthly YLL. The reduction in YLL was especially significant among males, those aged 16–64 years old, and suburban residents.

Conclusions: This study highlights that the law can lead to a reduction in YLL due to RTDs in Tianjin, China. Large immediate public health benefits resulted from the new road traffic law in China. YLL provides a complementary measure for examining the effect of criminalization on drunk driving RTDs.     

长隧道韵律型视觉环境设计研究

采用心理物理试验分析公路隧道内部视觉环境对驾驶员行车安全的影响,将E-prime 2.0软件与仿真驾驶模拟器相结合,对驾驶员在隧道内长时间行车中的速度判断准确率及反应时间两个指标进行分析,提出了利用标志标线构建公路隧道内韵律型标线系统的改善措施,以改善隧道内视觉环境,并利用数理统计方法及Logistics拟合分析对设计方案进行评价。结果表明:1)公路隧道内韵律型标线系统能提升隧道内驾驶员的速度判断准确率3.33%~11.66%;2)普通公路隧道场景中,被试者反应时间与隧道内行车时间存在显著关系,公路隧道内韵律型标线系统的场景中,反应时间与隧道内的行车时间没有显著关系,能有效缓解视觉疲劳现象;3)被试者反应时间的增加同时受隧道内视觉环境与行车时间的影响。公路隧道内韵律型标线系统能有效提高驾驶员的反应时间,适用于行驶速度为80 km/h、大于1 333 m的隧道。