人机共驾环境下驾驶疲劳研究综述

为减少自动驾驶过程中驾驶疲劳对驾驶人状态的影响,综合分析人机共驾环境下驾驶人的疲劳研究发展现状,系统梳理人机共驾模式下驾驶疲劳的研究成果,探索未来发展方向。首先,通过文献检索与关联性分析,明确人机共驾过程中疲劳累积研究现状;然后,从手动驾驶和人机共驾下的驾驶疲劳致因分析、驾驶时长和非驾驶相关任务对疲劳的影响、人机共驾环境下驾驶疲劳对驾驶行为的影响3个维度,讨论分析研究成果;最后,提出人机共驾环境下驾驶人疲劳研究的不足与发展方向。研究结果表明：人机共驾模式导致驾驶人被动疲劳增加,接管绩效受损,弹性设置非驾驶相关任务与自动驾驶时间可有效缓解被动疲劳;人机共驾过程中驾驶疲劳的演化规律与检测模型尚不明确,结合人机共驾场景特征探索驾驶人疲劳调控策略是未来研究重点。     

员工不安全行为意向的影响因子研究

为探究员工不安全行为意向的主要前因变量,基于计划行为理论(TPB),结合矿山企业安全管理实际,编制了包含21个项目的不安全行为意向量表。通过对240名煤矿一线作业人员进行调查和探索性因子分析(EFA),形成不安全行为意向的正式量表和探索性因子结构模型;再对7个煤矿735名一线作业人员进行调查并进行验证性因子研究(CFA)。结果表明:编制修订的不安全行为意向量表信度、效度较高;员工不安全行为意向受不安全行为态度、班组安全氛围、行为风险认知偏差等3个因子的影响;企业应从行为态度改变、班组安全氛围构建、行为风险认知偏差校正等方面,干预员工不安全行为意向,控制不安全行为的发生。     

基于SEM的不安全行为与其意向关系的研究

为检验不安全行为与不安全行为意向的关系,基于计划行为理论(TPB),对7个煤矿的735名一线作业人员进行问卷调查,收集工人被记录的和未被记录的不安全行为数据。采用结构方程模型(SEM)对不安全行为意向与不安全行为之间的关系进行分析。结果表明:安全行为态度、班组安全氛围、不安全行为风险认知偏差与不安全行为意向显著相关(路径系数分别为-0.36,-0.23和-0.57);不安全行为意向与不安全行为显著相关(路径系数为0.85);行为风险认知偏差与不安全行为显著相关(路径系数为0.51);而安全行为态度、班组安全氛围与不安全行为的关系并不显著。     

基于计划行为理论的矿工故意违章行为意向研究

为进一步解释和预测矿工故意违章行为意向,寻求可能的干预对策,以计划行为理论(TPB)为基本的理论构架,加入过去行为和示范性规范2个变量,构建了矿工故意违章行为意向假设模型。采取分层随机抽样方法,对412名矿工进行问卷调查,并借助结构方程建模技术对提出的假设模型进行了验证。研究表明:违章态度、知觉行为控制、示范性规范均对故意违章行为意向有显著的正向影响;主观规范对违章行为意向没有显著的直接影响;主观规范和过去行为通过违章态度间接正向影响违章行为意向。违章态度和示范性规范对故意违章行为意向的整体影响系数比较高,转变违章态度以及发挥群体其他成员遵章行为的示范性是降低故意违章行为意向的重要途径。     

基于计划行为理论的自行车不安全行为模型研究

依托国家道路交通安全科技行动计划课题五"全民交通行为安全性提升综合技术及示范"专题,基于计划行为理论,从社会心理学的角度首次对自行车骑行者的不安全行为进行分析。在增加变量的基础上,通过调查问卷的方式,研究自行车骑行者对不安全行为的态度、主观规范、知觉行为控制、行为经验等心理因素,从而构建自行车不安全行为模型。从调查数据的结构方程模型分析和个人属性分析可知,在调查人群中存在对不安全行为没有正确认识、自觉守法能力较弱和普遍有不安全行为经验等问题,同时也确定了参与不安全行为的重点人群。最后,在揭示心理因素作用于行为的基础上提出家庭式安全教育、加强交警管理、提倡榜样学习、加强交通安全宣传等行为矫正手段。     

基于贝叶斯结构方程模型的疲劳驾驶行为意图研究

为了深入探究影响驾驶员疲劳驾驶行为意图的心理因素,提高道路安全性,在计划行为理论的基础上,新增行为经验解释变量,形成扩展计划行为理论(Ex-TPB),构建了基于Ex-TPB的疲劳驾驶行为意图心理影响因素贝叶斯结构方程模型(Bayesian-SEM),并对比了传统结构方程模型(Traditional-SEM)与Bayesian-SEM的参数估计结果。最后,为有效防范疲劳驾驶行为提出了建议。结果表明:Ex-TPB可以有效解释和预测疲劳驾驶行为意图;在小样本的条件下Bayesian-SEM与Traditional-SEM相比,能得到更好的结果;对疲劳驾驶行为意图影响最大的因素为知觉行为控制,最小的是行为经验,且4种因素都显著正向影响疲劳驾驶行为意图。     

基于拓展TPB理论的客舱不安全行为意向影响因素研究

为了探究客舱旅客产生不安全行为意向的影响因素,本文基于旅客个体行为不完全受意志控制的特点,提出了采用计划行为理论作为理论基础,并引入了过去行为、风险感知和情绪管理3个新变量,构建了拓展的计划行为理论模型。通过自制量表的方式,研究了客舱旅客不安全行为意向影响因素的12个假设。研究结果表明,行为态度是影响不安全行为意向的最大直接因素,风险感知是最大的间接因素。本文为干预和引导旅客的安全行为给出一定的理论依据。     

行为传播视角下群体压力对矿工不安全行为意向的影响*

为探究不安全行为在煤矿企业班组之间的传播机制,建立矿工的群体压力、道德推脱、道德氛围与矿工不安全行为意向之间的假设模型。以252名一线班组矿工为研究对象,基于结构方程模型分析道德推脱的中介效应和道德氛围的调节效应,对行为传播视角下的群体压力对矿工不安全行为意向的影响展开研究。研究结果表明:群体压力与矿工不安全行为意向正相关;群体压力与矿工道德推脱水平正相关;道德推脱在群体压力与不安全行为意向之间起中介作用;工具型道德氛围在群体压力与道德推脱之间起调节作用;规则型道德氛围在群体压力与矿工不安全行为意向之间起调节作用。研究结果可为煤矿企业降低矿工的不安全行为意向提供1种可借鉴的理论依据和管理方法。     

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。     

Personality,attitudes and risk perception as predictors of risky driving behaviour among young drivers

Within psychology, different research traditions have attempted to explain individual differences in risky driving behaviour and traffic accident involvement. The present study attempts to integrate two of these research traditions, the personality trait approach and the social cognition approach, in order to understand the mechanisms underlying young drivers' risk-taking behaviour in traffic. The study was based on a self-completion questionnaire survey carried out among 1932 adolescents in Norway. The questionnaire included measures of risk perception, attitudes towards traffic safety and self-reported risk-taking in traffic. Personality measures included aggression, altruism, anxiety and normlessness. The results of a structural equation model suggested that the relation between the personality traits and risky driving behaviour was mediated through attitudes. On this basis it was concluded that personality primarily influences risky driving behaviour indirectly through affecting the attitudinal determinants of the behaviour. Practical implications for traffic safety campaigns are also discussed.     

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.     

Test procedure for evaluating the human–machine interface of vehicles with automated driving systems

Abstract

Objective: The human–machine interface (HMI) is a crucial part of every automated driving system (ADS). In the near future, it is likely that—depending on the operational design domain (ODD)—different levels of automation will be available within the same vehicle. The capabilities of a given automation level as well as the operator’s responsibilities must be communicated in an appropriate way. To date, however, there are no agreed-upon evaluation methods that can be used by human factors practitioners as well as researchers to test this.

Methods: We developed an iterative test procedure that can be applied during the product development cycle of ADS. The test procedure is specifically designed to evaluate whether minimum requirements as proposed in NHTSA’s automated vehicle policy are met.

Results: The proposed evaluation protocol includes (a) a method to identify relevant use cases for testing on the basis of all theoretically possible steady states and mode transitions of a given ADS; (b) an expert-based heuristic assessment to evaluate whether the HMI complies with applicable norms, standards, and best practices; and (c) an empirical evaluation of ADS HMIs using a standardized design for user studies and performance metrics.

Conclusions: Each can be used as a stand-alone method or in combination to generate objective, reliable, and valid evaluations of HMIs, focusing on whether they meet minimum requirements. However, we also emphasize that other evaluation aspects such as controllability, misuse, and acceptance are not within the scope of the evaluation protocol.     

轻型汽车实际行驶工况的排放研究

分别采用GPS和HEX CAN系统,记录了实际道路汽车行驶的瞬时速度和其他相关行驶参数,通过对两组数据进行工况解析,得到了城市汽车实际行驶工况.结果表明,我国的城市道路实际行驶工况与ECE EUDC标准工况相比,平均速度较低,怠速比例较高,加减速比例差别不大,但加减速较小,变化频繁,匀速比例较低.在整车排放试验台架上按得到的实际行驶工况进行排放试验,与ECE EUDC工况的排放试验结果进行对比.分析发现,冷启动时,实际行驶工况与ECE EUDC工况相比,CO排放高35.1%,HC高13.4%,NOx高23.1%; 热启动时,实际行驶工况与ECE EUDC工况相比,CO排放高21.4%,HC高26.3%,NOx高13.1%.研究表明,不论是在冷启动还是热启动状态,实际工况排放状况均与认证工况有一定的差别.因此,采用ECE EUDC工况不能代表不同城市实际车辆的污染排放状况.     

A challenge to the assumed generalizability of prediction and countermeasure for risky driving: different factors predict different risky driving behaviors

In road safety, it may be debated whether all risky behaviors are sufficiently similar to be explained by similar factors. The often assumed generalizability of the factors that influence risky driving behaviors has been inadequately tested. Study 1 (N=116) examined the role of demographic, personality and attitudinal factors in the prediction of a range of risky driving behaviors, for young drivers. Results illustrated that different driving behaviors were predicted by different factors (e.g., speeding was predicted by authority--rebellion, while drink driving was predicted by sensation seeking and optimism bias). Study 2 (N=127) examined the generalizability of these results to the general driving population. Study 1 results did not generalize. Predictive factors remained behavior-specific, but different predictor-behavior relationships were observed in the community sample. Overall, results suggest that future research and practice should focus on a multi-factor framework for specific risky driving behaviors, rather than assuming generalizability across behaviors and driving populations.     

Personality of young drivers in Oman: Relationship to risky driving behaviors and crash involvement among Sultan Qaboos University students

Objective: Drivers’ behaviors such as violations and errors have been demonstrated to predict crash involvement among young Omani drivers. However, there is a dearth of studies linking risky driving behaviors to the personality of young drivers. The aim of the present study was to assess such traits within a sample of young Omani drivers (as measured through the behavioral inhibition system [BIS] and the behavioral activation system [BAS]) and determine links with aberrant driving behaviors and self-reported crash involvement.

Methods: A cross-sectional study was conducted at the Sultan Qaboos University that targeted all licensed Omani's undergraduate students. A total of 529 randomly selected students completed the self-reported questionnaire that included an assessment of driving behaviors (e.g., Driver Behaviour Questionnaire, DBQ) as well as the BIS/BAS measures.

Results: A total of 237 participants (44.8%) reported involvement in at least one crash since being licensed. Young drivers with lower BIS–Anxiety scores and higher BAS–Fun Seeking tendencies as well as male drivers were more likely to report driving violations. Statistically significant gender differences were observed on all BIS and BAS subscales (except for BAS–Fun) and the DBQ subscales, because males reported higher trait scores. Though personality traits were related to aberrant driving behaviors at the bivariate level, the constructs were not predictive of engaging in violations or errors. Furthermore, consistent with previous research, a supplementary multivariate logistic regression analysis revealed that only driving experience was predictive of crash involvement.

Conclusions: The findings highlight that though personality traits influence self-reported driving styles (and differ between the genders), the relationship with crash involvement is not as clear. This article further outlines the key findings of the study in regards to understanding core psychological constructs that increase crash risk.     

The effects of personality and gender on risky driving behaviour and accident involvement

The present study investigates the effects of personality traits and gender on risky driving behaviour and accident involvement. A sample of Norwegian adolescents in two Norwegian counties participated (n = 1356). Anxiety was significantly correlated to excitement-seeking and risky driving behaviour, and excitement-seeking was significantly correlated to risky driving behaviour and collisions. Through a regression analysis, personality traits and gender were found to explain 37.3% of the variance in risky driving behaviour. However, the relations were not very strong, and the personality traits did only explain a moderate part of the variance. Possible explanations for this as well as methodological considerations are discussed. Directions for further research are suggested.     

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.