夜间动态环境中空间距离驾驶员判识变化

为研究驾驶员在夜间地面动态环境中距离判识变化的规律,改进行车安全.选取32名驾驶员进行实际道路试验.被试在自车行进方向不同的深度距离、车速下,判识前方障碍物的绝对距离和相对距离.统计距离判识值,得出夜间距离判识值数据分布,取得距离判识特征值.回归分析判识距离与速度的关系,建立障碍物判识变化的数学模型.比较昼夜距离判识差异,分析其对夜间行车安伞的影响.结果表明:在车辆行驶深度方向,夜间距离判识值随速度增加而不断下降,两者之间呈负指数关系;在相同深度距离和速度下,夜间判识距离大于昼间;夜间行车时,需适当降低车速,确保有效的安伞距离.     

驾驶中使用手机对驾驶员行为安全绩效影响综述

驾驶中使用手机与交通事故之间存在着高度相关性。为揭示使用手机对驾驶行为安全绩效的影响,探索影响驾驶安全的理论机制,采取更有效的干预措施,结合近10 a来相关研究,综述了与驾驶安全密切相关的驾驶分心问题,主要包括:驾驶员分心的定义及其分类;使用手机对驾驶行为安全绩效的影响,如反应时(RT)、行车速度、路线保持和跟车距离;手机使用对驾驶员分心影响的理论机制,如信息加工理论和计划行为理论(TPB)。分析表明,使用手机会导致驾驶员的反应时延长15%～40%,驾驶路线发生明显偏移,对于行车速度减缓和跟车距离延长的假设需结合驾驶员主客观数据进行比较做进一步验证;驾驶过程中使用手机会增加驾驶员的认知负荷,TPB能够对使用手机行为进行有效的解释和预测,但对该理论中基于信念测量的研究还很少;除手机操作任务,影响驾驶员分心的其他操作任务还需做进一步的研究。     

面向驾驶员心电数据的交叉口驾驶风险评估方法

为更精准地评估交叉口范围内的驾驶风险,首先,引入驾驶员心电(EGG)数据,提出基于余弦相似性距离的逼近理想解排序(TOPSIS)模型;其次,建立滚动时间窗法,并改进传统的短期频域指标计算方法,计算模型中低频(LF)变化率指标和低频与高频之比(LF/HF)等心率变异性(HRV)指标,模型时域指标有心脏搏动周期(R-R间期)变化率和其标准差(SDNN);然后,根据心电频域和时域指标与静息状态下对应指标的接近程度进行综合排序,按照越接近驾驶风险越小的原则,评估交叉口区域的驾驶风险;最后,选择30名驾驶员,在西安市23个交叉口开展实车试验,采集试验数据并验证模型方法。结果表明：驾驶员在相同交叉口环境下的驾驶风险评估结果相似性超90.1%,所提方法可应用稀疏样本评估交叉口的整体驾驶风险;高驾驶风险的交叉口评估方差较中、低驾驶风险路口分别高38.8%和67.9%,表明低风险交叉口区域驾驶风险的评估更精准。     

黄昏时段驾驶员对红绿色障碍物空间距离判识差异

为研究黄昏时段不同颜色引起驾驶员空间距离判识差异的变化规律,选用32名驾驶员,在黄昏环境照度变化的实际道路中,对不同深度距离下红、绿色障碍物的空间绝对距离和相对距离进行判识.比较人在三维空间中对红、绿色障碍物距离判识结果,获得判识距离差异特征值.对所获得的试验结果,运用BP神经网络模拟距离判识差异随照度和深度距离不同而变化的规律.结果表明:在三维空间,红、绿色障碍物黄昏时段距离判识差异显著,绿色障碍物判识距离大于红色,BP网络可以很好地拟合距离判识差异变化规律;随着外界环境照度的下降,红、绿颜色引起的距离判识值差异均增大,其中绝对距离差异增加明显;随着空间深度方向距离增加,判识差异也增大,其中相对距离判识差异增加量较绝对距离小.     

高速公路广告牌设置参数对安全驾驶的影响

基于眼动试验,以广告牌设置参数(面积、高度、距离道沿距离)为分析对象,对驾驶员注视高速公路广告牌的视觉特性进行分析,研究广告牌设置参数对安全驾驶的影响.利用眼动仪测试驾驶员对广告牌的平均眼球移动速度、注视时间等数据,通过分析采集的数据,得出高速公路广告牌设置时应在满足相应法规的条件下以大面积、高尺寸为宜,距道沿的距离以...     

车载GPS数据驱动的危货运驾驶员安全绩效评价

为提高危化品道路运输驾驶员日常安全绩效考核的科学性与便捷性,首先,从车载全球定位系统(GPS)中挖掘自然驾驶数据,运用改进的基于坐标系自适应变换的行驶轨迹分段拟合方法,提取行驶速度、加速度、平面曲率、道路坡度与坡长等动态驾驶数据;然后,结合车辆侧翻车速预测模型、长大下坡制动鼓温升模型,建立行驶速度稳定性、车辆横向稳定性、长大下坡制动稳定性和驾驶状态稳定性4个层次共7个指标的安全评价体系;最后,采用组合赋权法,构建10分制的危化品道路运输驾驶员安全绩效评价模型。研究结果表明:基于坐标系自适应变换的行驶轨迹分段拟合方法平均减少19.23%的拟合残差,构建的评价模型对危险驾驶行为反应灵敏。     

注意瞬脱效应对驾驶安全性影响的ERP试验研究

为预防驾驶员注意瞬脱效应导致的交通事故,首先,开展模拟驾驶任务试验,并在此过程中加入刺激颜色、时间间隔等因素,分别检测驾驶员的注意瞬脱反应;然后,基于试验数据,分析不同条件下驾驶员的驾驶行为指标(反应时和正确率)与事件相关电位(ERP)指标(P3波幅和潜伏期)的差异。结果表明:较红色警示牌和2、3 s的刺激时间间隔(SOA),在黄色警示牌和1 s的SOA条件下驾驶行为绩效显著降低(反应时延长,正确率降低),且P3潜伏期在顶叶区显著延长、波幅显著减小。注意瞬脱效应影响驾驶员对驾驶事件的脑内加工进程及投入的认知资源量,导致驾驶安全性降低。     

城市水下特长隧道中部光环境优化设计方法

为进一步优化城市水下特长隧道中部的光环境,基于设置多频率多尺度韵律型信息的思路,提出一种隧道光环境优化设计方法,利用3ds Max仿真软件制作行车仿真模型,以刺激物的主观等同速度(SSES)和安全感知距离为评价指标,采用E-prime软件组织车速感知心理物理试验,并分析试验数据。结果表明:隧道光环境优化后,驾驶员的速度感知能力由优化前的速度低估(14. 40%)提高为速度高估(15. 89%),反应时间由优化前的4. 11 s降低为2. 19 s;驾驶员的距离感知能力得到显著提高,同时行驶速度对于驾驶员距离感知能力的影响不再显著。     

道路交通事故与驾驶员群体心理品质关联模型构建

构建驾驶员心理品质与道路交通事故之间的关联模型,以准确反映机动车驾驶员的心理品质和安全驾驶的关系。依据事故倾向性理论,采用对照研究方法,随机选取253名事故驾驶员和254名优秀驾驶员,用艾森克人格问卷(EPQ)和卡特尔16种人格因素问卷(16PF)进行调查。比较2组驾驶员群体的气质类型和人格特征,通过因子分析计算驾驶员心理品质的综合得分。将所有驾驶员系统聚类,建立参照模型,区分驾驶员的不同类型。结果表明,驾驶员的心理品质直接制约驾驶行为,事故驾驶员和优秀驾驶员之间在心理品质上有显著差异,事故倾向性驾驶员筛查有可操作性。     

行车距离为安全

安全行车距离包括反应距离和停车距离。影响汽车安全行驶距离的因素很多，主要有以下几种因素：车辆的行驶速度，驾驶员的反应能力、时间，路面状况，天气变化，载重量的多少及车辆制动系统的结构形式等等。如何掌握判断汽车的安全行车距离，对驾驶安全十分重要。由于前后车的行驶速度一般都差不多，同时，制动过程也     

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.     

基于驾驶模拟的自动驾驶接管行为研究*

为探索有条件自动驾驶对非驾驶相关任务的允准边界,基于实车驾驶模拟器,设计自动驾驶接管试验典型场景,招募30名被试者开展驾驶模拟试验;要求驾驶人执行3种分心形式的驾驶次任务,系统发出接管请求提示后,驾驶人接管车辆控制权以避免险情发生,并分析驾驶人接管反应时间、驾驶负荷以及驾驶绩效等相关数据。结果表明:驾驶次任务涉及的分心形式越复杂,接管过程安全性越差,视觉分心任务与操作分心任务对接管行为影响显著;驾驶人更倾向于选择制动操作接管车辆,次任务分心程度越高,制动接管比例越大;与乘客聊天对接管行为影响不显著,看视频和玩手机游戏均会显著延长接管反应时间,增加工作负荷与车辆纵向减速度,玩手机游戏还会显著提升车辆横向加速度。     

Effect of age and secondary task engagement on motor vehicle crashes in a naturalistic setting

ProblemAutomobile crashes are one of the leading causes of death in the United States, especially for younger and older drivers. Additionally, distracted driving is another leading factor in the likelihood of crashes. However, there is little understanding about the interaction between age and secondary task engagement and how that impacts crash likelihood and maneuver safety.MethodData from the Naturalistic Driving Study (NDS), which was part of the Second Strategic Highway Research Program (SHRP2), were used to investigate this issue.ResultsIt was found that the distribution of crashes per one million km driven during the NDS was similar to previous research, but with fewer crashes from older drivers. Additionally, it was found that older and middle-aged drivers engaged in distracted driving more frequently than was expected, and that crashes were significantly more likely if drivers of those age groups were engaged in secondary tasks. However, secondary task engagement did not predict judgment of safe/unsafe vehicle maneuvers.Practical ApplicationsMore research is needed to better understand the interaction of age and distraction on crash likelihood. However, this research could aid future researchers in understanding the likelihood of future use of new in-vehicle technologies for different age groups, as well as provide insight to the engagement patterns of distraction for different age groups.     

Driving performance comparing older versus younger drivers

Objectives: A cross-sectional study was conducted at the Touro University California campus to compare differences in reaction times and driving performance of younger adult drivers (18–40 years) and older adult drivers (60 years and older). Each test group consisted of 38 participants.

Methods: A Simple Visual Reaction Test (SVRT) tool was used to measure reaction times. The STISIM Drive M100 driving simulator was used to assess driving parameters. Driving performance parameters included mean lane position, standard deviation of mean lane position measured, mean speed, standard deviation of mean speed, car-following delay, car-following modulus, car-following coherence, off-road accidents, collisions, pedestrians hit, and traffic light tickets.

Results: Compared to younger participants, older drivers experienced significantly slower reaction times (510.0 ± 208.8 vs. 372.4 ± 96.1 ms, P =.0004), had more collisions (0.18 ± 0.39 vs. none, P =.0044), drove slower (44.6 ± 6.6 vs. 54.9 ± 11.7 mph, P <.0001), deviated less in speed (12.6 ± 4.3 vs. 16.8 ± 6.3, P =.0011), and were less able to maintain a constant distance behind a pace car (0.42 ± 0.23 vs. 0.59 ± 0.24; P =.0025).

Conclusions: Differences exist in driving patterns of older and younger drivers as measured by reaction times and driving simulator outcomes. These results are the first to compare these 2 specific adult age groups' driving performance as measured by a standardized driving simulator scenario. Identifying these differences is essential in addressing them and preventing future traffic injuries.     

Injury prevention programs against distracted driving: Are they effective?

Introduction: Distracted driving (talking and/or texting) is a growing public safety problem, with increasing incidence among adult drivers. The aim of this study was to identify the incidence of distracted driving (DD) among health care providers and to create awareness against DD. We hypothesized that distracted driving is prevalent among health care providers and a preventive campaign against distracted driving would effectively decrease distracted driving among health care providers.

Methods: We performed a 4-phase prospective interventional study of all health care providers at our level 1 trauma center. Phase 1: one week of pre-intervention observation; phase 2: one week of intervention; phase 3: one week of postintervention observation; and phase 4: one week of 6 months of postintervention observation. Observations were performed outside employee parking garage at the following time intervals: 6:30–8:30 a.m., 4:40–5:30 p.m., and 6:30–7:30 p.m. Intervention included an e-mail survey, pamphlets and banners in the hospital cafeteria, and a postintervention survey. Hospital employees were identified with badges and scrubs, employees exiting through employee gate, and parking pass on the car. Outcome measure was incidence of DD pre, post, and 6 months postintervention.

Results: A total of 15,416 observations (pre: 6,639, post: 4,220, 6 months post: 4,557) and 520 survey responses were collected. The incident of DD was 11.8% among health care providers. There was a significant reduction in DD in each time interval of observation between pre- and postintervention. On subanalysis, there was a significant decrease in talking (P = .0001) and texting (P = .01) while driving postintervention compared to pre-intervention. In the survey, 35.5% of respondents admitted to DD and 4.5% respondents were involved in an accident due to DD. We found that 77% respondents felt more informed after the survey and 91% respondents supported a state legislation against DD. The reduction in the incidence of DD postintervention was sustained even at 6-month follow-up.

Conclusion: There was a 32% reduction in the incidence of distracted driving postintervention, which remained low even at 6-month follow-up. Implementation of an effective injury prevention campaign could reduce the incidence of distracted driving nationally.     

生理疲劳和心理疲劳对车辆驾驶的影响对比

针对现有疲劳驾驶预警和干预技术研究鲜有对生理疲劳和心理疲劳进行区分考虑的问题,为对比这两类典型疲劳态对驾驶员车辆驾驶过程的事故倾向影响,分别从性别、年龄和驾龄的角度分3批次共招募90位驾驶员进行状态诱发和驾驶实验。结果表明:尽管生理疲劳和心理疲劳都会如传统研究所述导致各驾驶员的驾驶违规倾向增加和驾驶能力降低,但是二者对于各类别驾驶员的驾驶影响程度和规律存在差异甚至迥异。研究疲劳驾驶相关问题时有必要首先判断驾驶员是生理疲劳还是心理疲劳,这是一个被普遍忽视而又可能影响研究结论准确性和有效性的重要因素。     

基于驾驶操作行为的驾驶员疲劳状态识别模型研究

以驾驶疲劳状态监测为研究对象,介绍现有几种疲劳检测方法及其优缺点,提出把驾驶行为操作和驾驶员生理指标相结合建立疲劳识别模型的思想。通过大量模拟器驾驶实验,建立驾驶操作和驾驶员生理指标之间的关系模型,并运用最小二乘法对数学模型进行了参数识别。利用驾驶员生理指标能较好判别驾驶员状态特性的特点,找出驾驶操作行为和驾驶状态之间的关系。研究结果有助于建立驾驶操作行为和驾驶员疲劳状态之间的关系模型。     

A qualitative study of college students' perceptions of risky driving and social influences

Objectives: Young adults and teens are documented as the riskiest drivers on the road, and newer issues such as texting and driving are a growing concern. This study sought to determine the risk perceptions of young adults regarding various driving behaviors, their past experiences, how their social circles are structured, and how this might affect their driving. Methods: This study conducted qualitative research with 25 college undergraduate students to determine their peer and social influences regarding distracted driving. Data were analyzed and related to the health belief model and past research on social influence. Results: Though most participants felt that their behaviors were set after learning to drive, they were, in fact, quite susceptible to the influence of those in their social circles (e.g., fear of judgment and accountability) and, more broadly, to social norms. Texting and driving was the largest and most topical distracted driving issue and was also identified as very difficult to stop due to perceived barriers and the idea that intervening is rude. Participants identified low perceived susceptibility and severity (perceived threat) for a number of risky driving behaviors, including texting and driving. Conclusions: Training is needed to encourage people to intervene and speak up regarding behaviors other than drinking and driving, and cues to action and campaigns should target intervention to increase self-efficacy, as well as norms, susceptibility, and common rationalizations for risky behavior.     

汽车驾驶愤怒情绪研究现状与展望

系统分析愤怒驾驶的研究方法和研究难点,从汽车驾驶人愤怒情绪产生的情景、汽车驾驶人愤怒时的表现或行为、汽车驾驶人愤怒情绪对交通安全的影响、汽车驾驶人愤怒情绪识别4个方面介绍汽车驾驶人愤怒驾驶的研究进展,以及国外汽车驾驶人愤怒驾驶研究的方法和工具。提出研究汽车驾驶人愤怒情绪应该重点关注样本的选择和研究方法的突破,并对发展趋势进行了展望:准确识别汽车驾驶人开车中的愤怒情绪,预测愤怒下的驾驶人开车可能产生的不安全行为,如何有效地管理愤怒驾驶,消除驾驶人在行车中的愤怒情绪,避免或降低愤怒驾驶对交通安全的影响。     

Bibliometric analysis of simulated driving research from 1997 to 2016

Objective: The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

Methods: The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

Results: A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

Conclusions: This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.