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。     

基于计划行为理论的侵犯驾驶行为研究

从社会心理学的角度,通过问卷调查的方式,对驾驶员侵犯驾驶行为的产生动机进行分析;基于计划行为理论,研究构建了能揭示驾驶态度与行为关系的理论模型,并得出驾驶员对侵犯驾驶行为的态度、主观标准、知觉行为可控性等心理因素,通过行为意向的中介作用,对驾驶员实施侵犯驾驶行为具有预测作用的结论。同时,提出了从态度改变、建立社会支持体系、提高驾驶员的自我能力评估等方面入手对驾驶员侵犯驾驶行为进行矫正的策略。     

驾驶行为理论模型研究概述

通过回顾驾驶行为的研究概况,重点介绍了4种理论模型:计划行为理论、威慑理论、事故原因模型、情境中介模型。在此基础上,分析了我国驾驶行为研究现状,并提出开展我国驾驶行为研究的初步建议和未来的研究方向:发展适用于我国的驾驶行为模型,并进一步研究在我国文化背景和道路环境下,不安全驾驶行为与示范性规范、文化因素以及情境变量等因素之间的关系,从心理学角度减少不安全驾驶行为和事故卷入,改善交通安全,提高交通效率。     

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。     

融合分心维度的驾驶行为可靠性研究

分心驾驶容易影响驾驶行为,进而导致交通事故的问题。用理论建模方法,研究分心对驾驶行为及其可靠性的影响。介绍分心驾驶的定义和维度。基于驾驶行为理论,建立融合分心维度的驾驶行为模型,分析不同分心维度对驾驶行为的影响机理。基于可靠性理论,建立融合分心维度的驾驶行为可靠性模型,分析不同分心维度对驾驶行为可靠性的影响。结果表明:不同维度分心对驾驶行为的影响具有各自特点和交互性;减少影响系数高的分心维度,有助于提高驾驶行为可靠性;多维度分心比单维度分心会更大程度地降低驾驶行为可靠度,应减少或避免复合分心。     

基于实车驾驶试验的螺旋匝道小客车纵向驾驶行为研究

为明确螺旋匝道(螺旋桥)驾驶操纵行为及车辆状态特征,选取2条桥头立交螺旋匝道和2座螺旋桥,开展小客车实车路试,通过连续采集行驶速度、加速度、踏板力等驾驶数据,分析螺旋匝道(桥)及前后衔接段的纵向驾驶行为特性.结果表明:行驶速度在螺旋匝道范围内基本恒定,并明显高于设计速度,螺旋匝道段的速度分布比主线段更集中,螺旋匝道对驾...     

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。     

自动挡车驾驶注意事项

和傻瓜相机一样,自动挡车经常被人们当成是不需要任何驾驶技术的傻瓜车。其实,自动挡汽车虽然省去了离合器踏板,使驾驶变得更加简单轻松,但若操作不当,也会增加自动变速器的故障发生几率,而正确使用自动变速器,不仅可以延长变速器的使用寿命,还可以降低油耗。技术顾问给我们指出了几个自动挡车的驾驶注意事项。     

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。     

驾驶行为模型的研究进展

驾驶员行为模型的研究对于预测和干预驾驶员的风险行为、设计相关的道路安全设施与车内设备,以及制定交通法律法规等具有重要的意义。为了解和掌握学术界关于驾驶行为模型的研究进展,搜集、筛选和归纳了1960—2010年被SCI数据库索引的相关文章,将驾驶行为模型分类为描述性模型、信息处理模型、动机模型、计划行为理论(TPB)和躯体标识假设,并对每种模型进行评述和总结,理清这些模型间的内在联系。研究发现,现有各模型只是从某个角度研究驾驶员行为的部分特征,而不能解释驾驶员的全部行为。今后应不断完善和整合各类模型,并借鉴心理学、生理学和行为科学等相关领域的理论、知识,使驾驶行为模型变得更为实用、有效。     

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.     

A framework for definition of logical scenarios for safety assurance of automated driving

Abstract

Objective: In order to introduce automated vehicles on public roads, it is necessary to ensure that these vehicles are safe to operate in traffic. One challenge is to prove that all physically possible variations of situations can be handled safely within the operational design domain of the vehicle. A promising approach to handling the set of possible situations is to identify a manageable number of logical scenarios, which provide an abstraction for object properties and behavior within the situations. These can then be transferred into concrete scenarios defining all parameters necessary to reproduce the situation in different test environments.

Methods: This article proposes a framework for defining safety-relevant scenarios based on the potential collision between the subject vehicle and a challenging object, which forces the subject vehicle to depart from its planned course of action to avoid a collision. This allows defining only safety-relevant scenarios, which can directly be related to accident classification. The first criterion for defining a scenario is the area of the subject vehicle with which the object would collide. As a second criterion, 8 different positions around the subject vehicle are considered. To account for other relevant objects in the scenario, factors that influence the challenge for the subject vehicle can be added to the scenario. These are grouped as action constraints, dynamic occlusions, and causal chains.

Results: By applying the proposed systematics, a catalog of base scenarios for a vehicle traveling on controlled-access highways has been generated, which can directly be linked to parameters in accident classification. The catalog serves as a basis for scenario classification within the PEGASUS project.

Conclusions: Defining a limited number of safety-relevant scenarios helps to realize a systematic safety assurance process for automated vehicles. Scenarios are defined based on the point of the potential collision of a challenging object with the subject vehicle and its initial position. This approach allows defining scenarios for different environments and different driving states of the subject vehicle using the same mechanisms. A next step is the generation of logical scenarios for other driving states of the subject vehicle and for other traffic environments.     

驾驶行为特性与人格特征关系研究

为了开展驾驶行为特性与人格特征关系的研究,选用26名被试人员,运用自主研 发的驾驶员综合能力测试系统,利用数理统计规律,研究被试者复杂反应、速度估计与 人格特征之间的关系。结果表明:在相同的试验环境下,所有被试者在伴有蜂鸣声时复 杂反应错误次数明显多于无蜂鸣声时;男女驾驶员在复杂反应时间方面表现出显著性差 异, 而在复杂反应错误次数方面未表现出明显差异;男女驾驶员在速度估计方面未表现 出显著性差异,但部分驾驶员表现出过高或过低估计速度的倾向;复杂反应指数和速度 估计指数与驾驶员的攻击性、独立性和敢为性之间存在着较强的正相关性,与社会向性 、稳定性之间存在着较强的负相关性;男性驾驶员表现出较强的攻击性、敢为性和独立 性,而女性驾驶员表现出较强的稳定性和社会向性。自主研发的系统能有效地分析了驾 驶行为特性与人格特征之间的内在关系,可以检测出潜在的事故倾向性大的驾驶员,有 利于减少交通事故的发生。     

基于HRV量化的高速公路出口匝道区域驾驶负荷特性研究

为提高高速公路主线出口匝道区域的行车安全性,基于HRV指标量化分析该区域的驾驶负荷特性和影响因素.分析了交通标志设计方案对主线出口匝道区域交通安全影响特性.采用HRV指标对驾驶负荷进行量化分析,同时采用不同信息量的交通标志对驾驶负荷进行定量加载,以汉十高速公路沿线匝道区为场景,设计并开展了主线出口匝道区域驾驶负荷的实车道路试验,采集不同试验场景下多个驾驶人的生理指标和驾驶特性.结果表明,交通标志信息量可以作为认知负荷加载的方式.从2 km到500m到出口位置的预告标志,表征驾驶负荷的HRV指标呈先下降后上升的趋势.驾驶人在通过主线出口匝道区域不同路段时的行驶车速的变化趋势与驾驶负荷强度的变化趋势具有较好的一致性.     

Impact of perceptual countermeasures on driving behavior at curves using driving simulator

Objective: The probability of crash occurrence on horizontal curves is 1.5 to 4 times higher than that on tangent sections. A majority of these crashes are associated with human errors. Therefore, human behavior in curves needs to be corrected.

Methodology: In this study, 2 different road marking treatments, optical circles and herringbone patterns, were used to influence driver behavior while entering a curve on a 2-lane rural road section. A driving simulator was used to perform the experiment. The simulated road sections are replicas of 2 real road sections in Flanders.

Results: Both treatments were found to reduce speed before entering the curve. However, speed reduction was more gradual when optical circles were used. A herringbone pattern had more influence on lateral position than optical circles by forcing drivers to maintain a safe distance from opposing traffic in the adjacent lane.

Conclusion: The study concluded that among other low-cost speed reduction methods, optical circles are effective tools to reduce speed and increase drivers’ attention. Moreover, a herringbone pattern can be used to reduce crashes on curves, mainly for head-on crashes where the main problem is inappropriate lateral position.     

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction

Objective: This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving.

Method: Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual–manual task) and distracted (poststarting of visual–manual task) driving periods. Average relative spectral power in a low frequency range (0–0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses.

Results: Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual–manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving.

Conclusions: This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.     

基于生理信号的驾驶疲劳综合指标试验研究

研究驾驶过程中随着疲劳的产生驾驶员生理信号的变化规律,提取反映驾驶疲劳程度的综合指标。采用驾驶模拟器对20名被试进行驾驶模拟试验,用MP150多导生理仪实时采集并记录驾驶员在60 min驾驶任务过程中的心电信号、脑电信号、肌肉电阻信号、皮肤温度信号和呼吸频率信号。运用R软件对数据进行线性回归分析,对比一般回归分析,逐步线性回归分析克服了一般回归分析许多变量不显著的缺点,得到了最优的驾驶综合指标方程,确定了与各项指标相关的驾驶疲劳评价综合指标,并通过3名被试模拟驾驶试验验证了综合指标作为评价驾驶疲劳的有效性。