基于驾驶适宜性检测的沙漠公路驾驶员生理、心理特性研究

采用驾驶适宜性检测仪器,在塔克拉玛干沙漠公路沿线进行驾驶员心理、生理特性的现场测试。结果表明,沙漠公路特殊的环境条件,使得驾驶员表现出有别于一般绿洲公路的心理和行为特性,其主要表现在:驾驶员动体视力较静体视力的平均降幅为44.75%,最高竟达到93%;速度估计和复杂反应时间均小于全国平均;复杂反应错误次数和处置判断错误次数均高于绿洲公路。灰色关联分析表明,沙漠公路驾驶员的年龄、驾龄、驾车时间以及气温与驾驶员的各项生理、心理特性指标都具有较强的相关性,关联度最高达到0.837,其中驾车时间对各项指标的影响最大。     

驾驶员反应特性在沙漠环境中的表现

在沙漠等特殊环境下,驾驶员的反应特性水平是衡量驾驶员驾驶适宜性的重要指标.为了探索汽车驾驶员的反应特性在特殊环境中的表现特征,本文利用复杂(选择)反应检测仪对沙漠公路行车途中汽车驾驶员进行了实地测试,测试包括反应时间和误反应次数在内的反应特性,并根据获得的有效样本检测数据进行统计整理,对受测驾驶员反应能力总体情况及与驾驶员年龄、驾龄、持续行车时间、检测时的气温等因素之间的关系进行了重点分析.研究表明,受急躁心理影响,沙漠环境下的驾驶员反应速度明显高于平均水平,而误反应次数增多,沙漠公路受测驾驶员复杂反应时间和误反应次数平均值分别为0.74 s和2.91次.关联度分析表明,沙漠公路驾驶员的年龄、驾龄、驾车时间及测试温度等因素与反应时间和错误次数均具有较强的相关性.相对于其他几项因素,驾车时间对驾驶员反应特性的影响最为明显.     

沙漠公路驾驶员心理、生理特性初探

针对沙漠公路交通安全现状,采用动体视力、速度估计、复杂(选择)反应、处置判断、血压脉搏检测仪等驾驶适宜性检测仪器,就长期从事沙漠公路运输活动的驾驶员群体进行了包括视觉、速度估计、反应、判断等在内的心理、生理特性的实地测试。检测结果初步表明,沙漠公路特殊的线形布设和修筑技术特征以及沿线的自然环境条件,使得驾驶员表现出有别于一般绿洲公路的驾驶心理和行为特性,其主要表现在在沙漠环境中,驾驶员的动体视力要较静体视力受到更大的影响;急躁心理影响,沙漠公路驾驶员的速度估计和复杂反应时间相应指标值均小于全国平均水平;沙漠公路驾驶员复杂反应错误次数和处置判断错误次数均高于绿洲公路。     

高原公路驾驶员生理心理特性现场测试研究

为分析驾驶员因高原环境影响而表现出的生理和心理特性,采用驾驶适宜性检测仪器,在高原公路沿线选定的测试点,针对过往驾驶员的特性指标进行现场测试。测试结果显示:高原公路驾驶员各项生理心理特性总体处于一般水平,其中,较差的是反应能力和判断能力;随着海拔增高,静视力和动视力显著降低,速度估计时间、反应时间、误反应次数、处置判断错误次数等指标均明显上升。关联分析表明:各特性指标与高原公路海拔、驾驶员年龄、驾驶时间等3个因素均有较强的关联性,关联度依次为海拔年龄驾驶时间。与不同环境地区相比,高原地区公路驾驶员总体表现出反应相对迟钝的特征。     

驾驶员感知特性对隧道群交通安全的影响

针对高速公路隧道群对驾驶员感知特性的影响,以驾驶员的感知特性与高速公路隧道群行车安全的关系为研究对象,采用速度估计测试仪和深度知觉测试仪,在"铜汤高速-安徽段"沿线对高速公路隧道群行车途中的160名驾驶员进行实地测试,所得数据进行t检验和方差分析,用灰色建模软件V2.1进行关联度分析。结果表明:驾驶员的速度估计特性与高速公路隧道群驾驶员的年龄、驾龄以及连续行车时间具有较强的相关性,其中连续驾车时间的影响最大。年龄对驾驶员深度知觉准确性无显著影响;驾龄、连续行车时间对驾驶员的深视力准确性有显著影响。     

高原公路驾驶员应激反应能力分析

为分析驾驶员在高原公路环境下的应激反应能力,利用驾驶适应性检测仪器和辅助设备在现场试验中获得高原公路驾驶员的生理心理指标数据,研究其应激反应行为。测试结果表明:驾驶员的血压、心率与高原海拔、年龄、驾龄和连续驾驶时间显著相关。具体地说是,驾驶员的血压随着海拔上升及驾驶时间的延长出现下降,驾驶员的心率与年龄和驾龄成正相关。对驾驶适宜性检测的样本数据进行配对T检验发现,随着海拔升高,高原公路驾驶员的驾驶行为能力表现出选择反应迟缓,选择错误水平上升,应激反应能力减弱等特点。     

基于灰色关联度理论的沙漠地区道路强制休息处运用体系研究

从驾驶员生理、心理特性角度,阐述了沙漠地区道路交通安全的各影响因素,分析了长距离公路驾驶员出现疲劳现象时的生理、心理特性变化,运用灰色关联度分析得到"驾驶员生理、心理特性--行车时间衰退曲线",结合目标公路附属设施设置实际情况情况,提出了更具有针对性的强制休息处运用体系.最后以阿拉尔-和田沙漠公路安全畅通工程建设为实例,详细阐述强制休息处运用体系研究情况.     

眼疾,驾车的大忌

驾驶员驾车在路上行驶,要通过视觉获得信息情报,处理各种情况,所以视觉机能的好坏及其变化直接影响到驾驶员发现和辨认障碍物的能力,对交通安全有着决定性的影响。 近视:汽车行驶时,驾驶员观察道路环境中的物体是相对运动的,这时驾驶员的视力叫作动视力,动视力与汽车的行驶速度、交通环境及驾驶员的年龄     

沙漠道路曲线对非专职驾驶员心率的影响

为合理确定道路曲线,确保沙漠公路行车安全,利用多导生理记录仪研究实驾试验中沙漠道路曲线对非专职驾驶员心率的影响。通过频域分析和灰色关联分析,确定非专职驾驶员的高频段功率的标化值(HFnorm)和低频与高频功率的比值(LF/HF)与道路曲线的关系。结果表明:在景观比较单一的沙漠地区道路曲线线形设计中,适当增加不同半径的曲线,能在一定程度上缓解驾驶员的行车疲劳。沙漠道路曲线变化对于驾龄较长的年轻驾驶员迷走神经活动的影响比年长驾驶员的要小。为保证司机的自主神经活动处于合理的范围,沙漠道路平竖曲线长度的设计应根据驾驶员心电的LF/HF指标确定,纵坡度的设计应根据驾驶员心电的HFnorm和LH/HF指标综合确定。     

新中老驾驶员交通安全违法随意性变化趋势及致因研究

为降低交通安全违法随意性,运用模糊信号检测理论,以动态模拟手段,进行了驾驶员交通安全违法随意性检测试验,并提取、分析驾驶员危险感知数据,研究了驾龄增长与驾驶员交通安全违法随意性之间的变化趋势和造成这种趋势的影响因素及作用机理。结果表明,随驾龄增长驾驶员交通安全违法随意性呈先增大而后降低、且老驾驶员交通安全违法随意性更大的总体趋势;在2项影响因素中,交通执法仅决定驾驶员交通安全违法随意性的整体水平。而新、中、老驾驶员对交通法规保障行车安全作用的认识不同,这造成了交通安全违法随意性的总体变化趋势。在交通管理中,对新、中驾驶员应侧重交通法规教育,并提高对中段驾驶员的交通执法力度;对老驾驶员应侧重交通执法。     

109国道宁夏石中段交通事故特性及成因分析

搜集了平原微丘区二级公路109国道宁夏石中段2001—2003年间的道路交通事故资料,分析其交通事故的时间分布、空间分布、肇事驾驶员等分布规律。研究表明:早晚交通高峰小时过后是交通事故高发时段,交通事故月分布规律受季节影响较大,路段交通事故形态中以尾随相撞类事故居多,发生于路段的交通事故数高于交叉口处的交通事故数,驾龄小于4年和年龄18～25岁的驾驶员最容易造成交通事故。进而提出加强交通管理,增设减速震动线等交通安全设施降低主线车速,加强易发交通事故的驾驶员人群的后期培训和教育等防控措施。以期有助于缓解我国二级公路严峻的交通安全形势,增强交通事故预防的科学性。     

驾驶员接管自动驾驶车辆的眼动特性和行为分析

为探究接管自动驾驶车辆期间驾驶员的视觉特性,分析眼动与接管反应操控行为的关系,开展驾驶模拟试验收集驾驶行为及眼动数据。运用统计学方法,分析驾驶员感知不同接管场景的视觉特性,探究接管请求(TOR)前后眼动指标的变化规律;并基于视觉分配和瞳孔变化特性分析驾驶行为,揭示眼动特性与接管反应及驾驶操纵策略的内在联系。结果表明:TOR前,相较于静态场景,驾驶员感知动态场景诱发元素扫视更频繁且平均注视时间更短;此时驾驶员的视觉分配特性与其接管反应行为存在显著相关性。TOR后,驾驶员的注视时间增加,眨眼频率降低,瞳孔直径扩张,眼跳幅度增大;不同场景下驾驶员的瞳孔差异表明其应对动态场景时具备更好的警戒水平和更平稳的操纵策略。     

Predictability of clinical assessments for driving performance

PROBLEM: As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. METHOD: Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors (<.05) to be included in a multivariate regression model. RESULTS: Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. DISCUSSION: The domains of vision, cognitive, and motor performance were represented in the predictive model. SUMMARY: Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. IMPACT ON INDUSTRY: By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers.     

Road characteristics and driver fatigue: a simulator study

Two experiments examined the influence of road characteristics on driver fatigue in a prolonged simulator drive. In experiment one, ten military truck drivers drove a mixed route, with straight, winding, and straight highway segments. In experiment two, 16 additional drivers drove either a straight, a winding, or a mixed route. Fatigue symptoms were assessed using performance, subjective, and psychophysiological measures (HRV). We hypothesized that drivers adopt different fatigue-coping strategies relative to the demands of the drive. Thus, on straight roads drivers are more likely to loosen their driving demands by either increasing their driving speed and/or not maintaining the lane position, as the road is tolerant to both strategies, whereas on winding roads, drivers are more likely to increase their speed but not their lane positioning. Our results confirm that decremental changes in driving performance varied among road types. In the straight road components, we found decrements in the quality of lane maintaining (experiment one) and steering quality (experiments one and two) and longitudinal speed (experiment two). In the winding road, we found that drivers increased their driving speed over time (experiments one and two).     

Effects of environment, vehicle and driver characteristics on risky driving behavior at work zones

This study aims to analyze the effects of environment, vehicle and driver characteristics on the risky driving behavior at work zones. A decision tree is developed using the classification and regression tree (CART) algorithm to graphically display the relationship between the risky driving behavior and its influencing factors. This approach could avoid the inherent problems occurred in the conventional logistic regression models and further improve the model prediction accuracy. Based on the Michigan M-94/I-94/I-94BL/I-94BR highway work zone driving behavior data, the decision tree comprising 33 leaf nodes is built. Bad weather, poor road and light conditions, partial/no access control, no traffic control devices, turning left/right and driving in an old vehicle are found to be associated with the risky driving behavior at work zones. The middle-aged drivers, who are going straight ahead in their vehicles with medium service time and equipped with an airbag system, are more likely to take risky behavior at lower work zone speed limits. Further, the middle-aged male drivers engage in risky driving behavior more frequently than the middle-aged female drivers. The number of lanes exhibits opposing effects on risky behavior under different traveling conditions. More specifically, the risky driving behavior is associated with the single-lane road under bad light or weather conditions while drivers are more likely to engage in risky behavior on the multi-lane road under good light conditions.     

The relationship of beer consumption and state alcohol and motor vehicle policies to fatal accidents

Fatal accident data from 50 states and the District of Columbia were examined in order to determine the relationship between alcohol availability and fatal motor vehicle accidents. This relationship was analyzed for both fatal accidents and motor vehicle fatalities (potentially more than one per accident) using multiple regression. The independent variables were: (1) driving age (percent of drivers under 21); (2) beverage purchase age; (3) average beer consumption; (4) number of outlets per million population selling alcohol for on-premise consumption; (5) percentage of metropolitan residents; (6) percentage of male drivers; and (7) mileage per driver per year. It was found that the regression analyses for fatal accidents and for fatalities were highly similar. Driving age was the strongest predictor of highway mortality. On-premise availability of alcohol was significantly and inversely associated with motor vehicle fatalities. This suggests that when on-premise outlets are fewer and more geographically spread out, the chances of drinking and driving are greater. Finally, average beer consumption was significantly and positively associated with highway fatalities perhaps because many drivers consider it a “soft” alcoholic beverage that will not impair their ability to drive.     

Classification of driving workload affected by highway alignment conditions based on classification and regression tree algorithm

Objective: Guaranteeing a safe and comfortable driving workload can contribute to reducing traffic injuries. In order to provide safe and comfortable threshold values, this study attempted to classify driving workload from the aspects of human factors mainly affected by highway geometric conditions and to determine the thresholds of different workload classifications. This article stated a hypothesis that the values of driver workload change within a certain range.

Methods: Driving workload scales were stated based on a comprehensive literature review. Through comparative analysis of different psychophysiological measures, heart rate variability (HRV) was chosen as the representative measure for quantifying driving workload by field experiments. Seventy-two participants (36 car drivers and 36 large truck drivers) and 6 highways with different geometric designs were selected to conduct field experiments. A wearable wireless dynamic multiparameter physiological detector (KF-2) was employed to detect physiological data that were simultaneously correlated to the speed changes recorded by a Global Positioning System (GPS) (testing time, driving speeds, running track, and distance). Through performing statistical analyses, including the distribution of HRV during the flat, straight segments and P-P plots of modified HRV, a driving workload calculation model was proposed. Integrating driving workload scales with values, the threshold of each scale of driving workload was determined by classification and regression tree (CART) algorithms.

Results: The driving workload calculation model was suitable for driving speeds in the range of 40 to 120 km/h. The experimental data of 72 participants revealed that driving workload had a significant effect on modified HRV, revealing a change in driving speed. When the driving speed was between 100 and 120 km/h, drivers showed an apparent increase in the corresponding modified HRV. The threshold value of the normal driving workload K was between ?0.0011 and 0.056 for a car driver and between ?0.00086 and 0.067 for a truck driver.

Conclusion: Heart rate variability was a direct and effective index for measuring driving workload despite being affected by multiple highway alignment elements. The driving workload model and the thresholds of driving workload classifications can be used to evaluate the quality of highway geometric design. A higher quality of highway geometric design could keep driving workload within a safer and more comfortable range. This study provided insight into reducing traffic injuries from the perspective of disciplinary integration of highway engineering and human factor engineering.     

塔克拉玛干沙漠公路交通事故趋势预测分析

应用塔克拉玛干沙漠干线公路建成通车以来的交通事故统计数据,在分析交通事故主要指标发展变化特征和分布特征的基础上,建立了适用于沙漠公路交通事故特点的GM(1,1)预测模型,对未来几年内交通事故发展趋势进行了预测。预测结果表明,未来几年沙漠公路交通事故次数、死亡人数、受伤人数以及直接经济损失等4项指数将分别以15.9%,10%,4.5%和5%的年平均增长率快速增长。同时针对预测结果提出了相应的对策。