驾驶人行为不确定性对车辆轨迹预测的影响分析

针对驾驶行为不确定性影响车辆轨迹预测精度的问题，采用预瞄控制方法和滑模控制方法，分析了不同行驶车速与工况下车辆轨迹预测误差。结果表明：预瞄控制方法和滑模控制方法能够有效处理驾驶人超车、避障和转向行为的外部干扰，将轨迹预测误差控制在0.5 m以内，但高速工况下的轨迹误差明显大于低速工况下的轨迹误差；在小曲率转向工况下，基于单点预瞄驾驶人视觉轨迹预测误差小于基于双点预瞄驾驶人视觉轨迹预测误；在大曲率转向工况下，基于单点预瞄驾驶人视觉轨迹预测误差大于基于双点预瞄驾驶人视觉轨迹预测误。研究结果为驾驶人视觉轨迹预测策略的制定及车辆不同行驶工况下驾驶人行为不确定性的处理提供了理论依据。     

电动转向系统助力性能研究

汽车电动转向系统的助力性能直接关系到汽车转向操作的安全 ,笔者以电动转向系统的跟踪性能和对扭矩传感器测量噪声及路面干扰的抑制为控制系统设计的目标 ,将H∞ 控制理论应用于控制系统的设计 ,采用LMI处理方法设计了控制器。计算机仿真结果证实 ,所设计的电动转向系统具有良好的跟踪性能 ,并有效地抑制了扭矩传感器测量噪声和路面激励干扰的影响 ,仿真结果为电动转向系统的设计提供了依据     

汽车EPS系统的行车工况补偿控制策略

针对汽车在常见转向工况时转向的操纵性和安全性不足问题,提出将常见工况补偿控制策略融合到汽车EPS助力控制中,将汽车速度、汽车质量、方向盘左右晃动考虑在内,设计了高速避让、低速满载、颠簸路面3种补偿控制策略;并理论分析加入高速避让、低速满载、颠簸路面3种补偿策略后,方向盘、齿条位移和汽车横摆角速度增减值的变化;最后,通过搭建汽车EPS系统模型和二自由度汽车模型进行仿真验证。仿真结果表明,采用补偿控制策略后,汽车在高速、低速大重量及于凹凸不平的路面行驶时,助力电机目标电流的获取与汽车行驶的内外环境紧密相连,且可随行车条件的改变而适时改变,使汽车EPS系统具有了更好的操纵性和安全性。     

高速公路行车“六忌”

一忌超高速行车。高速公路路面好,许多司机往往一上高速公路就爱开快车,这样既不经济,更不利于安全。因为车速越高,制动距离越大,汽车转向时的离心力就增大,汽车的操纵稳定性则变差。另外,车速越快,驾驶员视线距离越短,视野变得越窄,由此而产生的判断失误也就增加。因此,控制行驶速度是保证高速公路行车安全的首要条件。     

基于改进驾驶员模型的车道保持控制模型

为解决传统车道保持系统控制精度较差、驾驶员模型对大曲率道路适应性不足的问题,对传统预瞄加速度驾驶员模型非零频率点进行泰勒展开以改进模型;利用驾驶模拟器试验数据和快速傅里叶方法(FFT)研究双移线道路下的主要转向频率,并搭建Simulink/Car Sim联合仿真模型以验证改进前后驾驶员模型的双移线路径跟踪精度。仿真试验表明:改进后模型的横向位移误差比改进前明显减小,车速为60、70和80 km/h时的最大横向位移误差比改进前分别降低了0.2、0.15和0.11 m;与常规道路人工势场车道保持系统的对比,改进驾驶员模型能够更好地控制车辆跟随期望路径行驶,体现出良好的车道保持能力。     

海底隧道入口段驾驶员眼动特征分析*

为研究海底隧道入口段驾驶员眼动特征,以海底隧道收费站至入口为研究对象,运用Facelab5.0眼动仪和录像机等设备,采集真实状态下驾驶员眼动特征、行车速度和行车位置数据,并依据道路线形、车辆行车特征和路段标志标线设置,将收费站至入口划分为提速驶离段、换道减速段、缓和段和过渡段（入口段）,分析各区段驾驶员眼动特征及车速变化规律,并建立相应数学模型。研究结果表明:驾驶员驾车通过换道减速段和过渡段时,分别受交织车流与黑洞效应影响,行车速度减小、眼睑闭合度下降、眨眼频率增大;驾驶员行经入口段,车速呈上升-下降-上升-下降的趋势,眼睑闭合度呈增大-减小-增大-减小的趋势,眨眼频率呈减小-增大-减小-增大的趋势,且受交织车流与黑洞效应的影响显著。     

爆胎后如何驾驶?

汽车在行驶中如果轮胎突然“爆炸”,此时车辆往往会急速摇摆,驾驶员应掌握好方向盘,控制住车辆的行驶方向,同时迅速关闭油门,让汽车减速。当发动机的牵阻作用控制住车速后,可轻轻地使用后制     

汽车电动助力转向装置的安全性探讨

电动助力转向装置是汽车上一种新的助力转向系统装置 ,近年来在国内外发展迅速 ,由于它采用了可编程电子控制装置 ,在带来灵活性的同时也存在着安全隐患。在分析这种产品特殊性的基础上 ,笔者结合电子控制装置的特点 ,指出了事关安全性的因素 ,提出了处理安全性的措施 ,并讨论了几个事关安全性的具体问题。研究结果表明 :现有标准不能够满足电动助力转向装置安全性的需要 ;并提出了对电动助力转向装置进行安全性测评的思想。研究工作对电动助力转向装置的开发以及评价具有参考意义。     

车行万里,忍让为先

在汽车驾驶中,驾驶员能正确做到忍让,就能安全行车,幸福一生。 忍让车速 驾驶员在日常行车时,常常会遇到有的车辆在窄路     

村镇道路会车特性与驾驶员心生理变化关系研究

为提高村镇道路行车安全性,实地检测村镇道路会车过程中车速和驾驶员的心生理反应参数,融合交通工程学、心理学和人因工程学的基础理论,探究会车过程中车辆的运行特性与驾驶员心率变化间的关系。首先整体分析试验中所有会车过程的行车状态,然后分析直线段上单次会车过程中车速变化与心率增长率的关系,最后分析曲线段上车速、心率增长率与平曲线半径的关系。结果表明:在村镇道路上,驾驶员会车时存在明显的紧张行为;在会车时域内车速、驾驶员心率增长率呈U型变化,且两者变化趋势相反;会车时的车速随道路平曲线半径的增加而增大,心率增长率随平曲线半径的增加而减小。     

Changes in driving behavior and cognitive performance with different breath alcohol concentration levels

OBJECTIVE: This study examines the changes in driving behavior and cognitive performance of drivers with different breath alcohol concentration (BrAC) levels. METHODS: Eight licensed drivers, aged between 20 and 30 years, with BrAC levels of 0.00, 0.25, 0.4 and 0.5 mg/l performed simulated driving tests under high- and low-load conditions. Subjects were asked to assess their subjective psychological load at specified intervals and perform various tasks. The outcome was measured in terms of reaction times for task completion, accuracy rates, and driver's driving behavior. RESULTS: The effects of BrAC vary depending on the task. Performance of tasks involving attention shift, information processing, and short-term memory showed significant deterioration with increasing BrAC, while dangerous external vehicle driving behavior occurred only when the BrAC reached 0.4 mg/l and the deterioration was marked. CONCLUSION: We can conclude that the cognitive faculty is the first to be impaired by drinking resulting in deteriorated performance in tasks related to divided attention, short-term memory, logical reasoning, followed by visual perception. On the other hand, increasing alcohol dose may not pose an immediate impact on the external vehicle driving behavior but may negatively affect the driver's motor behavior even at low BrAC levels. Experience and will power could compensate for the negative influence of alcohol enabling the drivers to remain in full steering control. This lag between alcohol consumption and impaired driving performance may mislead the drivers in thinking that they are still capable of safe steering and cause them to ignore the potential dangers of drunk driving.     

基于隶属函数的高速公路安全距离模型研究

为了改善高速公路防追尾安全距离模型,对模型中的驾驶员反应时间进行研究,分析不同车速时驾驶员反应时间对安全距离的影响。驾驶员反应时间受驾龄、应变能力、性别、心理生理状况、车速等多种因素的影响。基于模糊数学中隶属函数的有关理论,利用Matlab软件,在驾驶员反应时间大小允许的范围内,综合考虑各种主要因素,确定驾驶员反应时间。通过具体实例说明该方法的应用,结果证明,应用模糊数学,可以计算出不同的驾驶员,在不同的车速时的反应时间。     

Assessing drivers' response during automated driver support system failures with non-driving tasks

IntroductionWith the increase in automated driver support systems, drivers are shifting from operating their vehicles to supervising their automation. As a result, it is important to understand how drivers interact with these automated systems and evaluate their effect on driver responses to safety critical events. This study aimed to identify how drivers responded when experiencing a safety critical event in automated vehicles while also engaged in non-driving tasks.MethodIn total 48 participants were included in this driving simulator study with two levels of automated driving: (a) driving with no automation and (b) driving with adaptive cruise control (ACC) and lane keeping (LK) systems engaged; and also two levels of a non-driving task (a) watching a movie or (b) no non-driving task. In addition to driving performance measures, non-driving task performance and the mean glance duration for the non-driving task were compared between the two levels of automated driving.ResultsDrivers using the automated systems responded worse than those manually driving in terms of reaction time, lane departure duration, and maximum steering wheel angle to an induced lane departure event. These results also found that non-driving tasks further impaired driver responses to a safety critical event in the automated system condition.ConclusionIn the automated driving condition, driver responses to the safety critical events were slower, especially when engaged in a non-driving task.Practical applicationTraditional driver performance variables may not necessarily effectively and accurately evaluate driver responses to events when supervising autonomous vehicle systems. Thus, it is important to develop and use appropriate variables to quantify drivers' performance under these conditions.     

驾驶人疲劳监测预警技术研究与应用综述

基于各种物理传感器的疲劳驾驶监测预警技术(DFMP),是交通安全领域的研究重点。这类技术主要包括基于驾驶人生理特征、车辆运行状态以及驾驶人行为特征的疲劳监测。分析论述各种疲劳监测技术的研究现状与进展、优缺点以及应用状况,介绍目前世界上常用的疲劳监测系统。通过分析比较得出:车道偏离监测、车辆运动参数监测、基于人眼、头部运动以及面部状态的疲劳监测等是目前的热点研究方向;系统软硬件的提升、基于机器视觉的多传感器多参数信息融合等是疲劳监测技术重要的发展趋势;更强的实时性、准确性和鲁棒性是疲劳监测技术的发展目标。     

考虑驾驶员反应时间的车辆碰撞预警模型

为了保证车辆在行驶过程中的安全性,提出了一种考虑驾驶员反应时间的车辆碰撞预警模型,改进了传统模型中驾驶员反应时间定值化的缺点。首先,依据车辆的制动过程分析了驾驶员反应时间对制动距离的影响。其次,设计驾驶员反应时间的模糊推理算法,选取驾龄、疲劳强度和应变能力3个主要因素作为评价指标来计算反应时间。最后,采用分等级的预警策略建立考虑驾驶员反应时间的碰撞预警模型,并通过Carsim-Matlab/Simulink联合仿真与传统模型进行对比分析。结果表明,设计的预警模型可以对不同类型的驾驶员进行差异化碰撞预警,在30 km/h和80 km/h两种车速下实际停车距离与理论值的最大误差为8%。     

关于区域环境保护政策的思考

本从通过分析我国环境保护政策存在的缺口和目前对这种理念的研究进展，并根据环境问题本身的特性以及环境问题产生的背景差异提出重新确立环境保护政策的调控范围的观点，并提出了这种观点对于对我国环境保护政策以及环境保护工作的重要意义。     

Improvement of driver active interventions during automated driving by displaying trajectory pointers—A driving simulator study

Abstract

Objective: The handover of vehicle control from automated to manual operation is a critical aspect of interaction between drivers and automated driving systems (ADS). In some cases, it is possible that the ADS may fail to detect an object. In this event, the driver must be aware of the situation and resume control of the vehicle without assistance from the system. Consequently, the driver must fulfill the following 2 main roles while driving: (1) monitor the vehicle trajectory and surrounding traffic environment and (2) actively take over vehicle control if the driver identifies a potential issue along the trajectory. An effective human–machine interface (HMI) is required that enables the driver to fulfill these roles. This article proposes an HMI that constantly indicates the future position of the vehicle.

Methods: This research used the Toyota Dynamic Driving Simulator to evaluate the effect of the proposed HMI and compares the proposed HMI with an HMI that notifies the driver when the vehicle trajectory changes. A total of 48 test subjects were divided into 2 groups of 24: One group used the HMI that constantly indicated the future position of the vehicle and the other group used the HMI that provided information when the vehicle trajectory changed.

The following instructions were given to the test subjects: (1) to not hold the steering wheel and to allow the vehicle to drive itself, (2) to constantly monitor the surrounding traffic environment because the functions of the ADS are limited, and (3) to take over driving if necessary.

The driving simulator experiments were composed of an initial 10-min acclimatization period and a 10-min evaluation period. Approximately 10?min after the start of the evaluation period, a scenario occurred in which the ADS failed to detect an object on the vehicle trajectory, potentially resulting in a collision if the driver did not actively take over control and manually avoid the object.

Results: The collision avoidance rate of the HMI that constantly indicated the future position of the vehicle was higher than that of the HMI that notified the driver of trajectory changes, χ² = 6.38, P < .05. The steering wheel hands-on and steering override timings were also faster with the proposed HMI (t test; P < .05).

Conclusions: This research confirmed that constantly indicating the position of the vehicle several seconds in the future facilitates active driver intervention when an ADS is in operation.     

驾驶员心理特征与驾驶安全的关系研究

随着人-车-环境系统复杂性的增加和交通事故数量的上升,新型交通工具对驾驶员的要求随之提高。从人的心理与控制的关系及汽车驾驶员的心理特征出发,具体分析心理各特征因素对驾驶员的影响,在此基础上建立汽车驾驶员安全评价模型,最后提出了在考虑心理因素的前提下提高道路行车安全的具体措施。     

考虑驾驶方式的车辆与航空器交叉冲突评估*

为量化不同驾驶方式下车辆与航空器行驶风险,提出车辆与航空器交叉运行冲突评估模型,该模型将特种车辆驾驶方式分为激进、稳定、保守3类,综合驾驶特性和管制规则定义车辆速度演化规律,结合运行场景、间隔配备等要素确定冲突条件,并基于航空器与车辆实时速度、位置变化构造冲突评估模型。研究结果表明:冲突评估模型能够计算车辆与航空器在十型交叉口的冲突概率;激进方式下车辆先于航空器通过交叉口,风险概率均值相对最大,为0.679;保守方式下航空器先于车辆通过交叉口,最大间隔是安全间隔的4.7倍;稳定驾驶方式可兼顾安全和效率。本文模型能再现十型道口车辆与航空器交叉运行冲突产生、发展及解脱过程,计算结果可用于场面实时冲突识别和预警,能够为机场危险源识别和风险管控提供依据。