三维模拟驾驶仿真系统的研究与实现

为了解决模拟驾驶仿真系统中开发成本昂贵、缺乏二次开发特性等问题,研究并实现了一种结合3DMAX建模软件、开放源代码的Newton物理引擎和OSG图像渲染引擎的三维模拟驾驶仿真系统.硬件系统采用多传感器融合技术来采集驾驶员模拟驾驶时的操作行为,软件系统根据所采集的操作数据实现对车辆的运动和碰撞反应的控制以及对场景视角的切换.实验结果表明,该方法具有软件开发成本低,场景逼真度高,动态效果好等特点,可以满足对驾驶员的驾驶行为进行记录并分析的需要.     

车载疲劳驾驶行为检测系统的研究与设计

针对汽车驾驶员的疲劳驾驶行为检测过程繁琐、算法复杂、检测装置部署易影响驾驶员等现状,为更加方便、快捷、有效的对疲劳驾驶做出监测和报警,提出基于ZigBee的车载疲劳驾驶检测方案.选取方向盘角度变化作为检测疲劳驾驶的突破点,使用TLE5012角度传感器,完成角度数据的采集,采用CC2530实现系统的无线通信.从采集到的方向盘角度数据中提取能反映疲劳状态的零速百分比和角度标准差两个特征,使用线性判别算法对驾驶人员的疲劳状态进行分类.仿真实验表明,该方法能够较准确的对疲劳状态进行判别.     

基于心理物理综合认知结构的微观交通仿真模型

针对驾驶行为的不确定性,在分析驾驶员心理-物理微观特性的基础上,构建了基于驾驶员任务集聚的心理-物理综合认知结构及其各行为运行模式下微观交通仿真的车辆跟驰模型.运用五轮仪试验系统所采获的实际数据和多元统计分析的数学方法对模型进行了标定,并使用与模型标定过程所用到的数据不同的另一部分数据验证了模型的有效性.结果表明,该文所提出的模型和算法能够很好地刻画驾驶员心理-物理行为特性的复杂性,再现人车单元的实际动态行为,为网络交通流一体化协同仿真和智能运输系统研究提供理论基础.     

驾驶员敏感行为对入匝道口车流量的影响

在交通流优化的研究中,为了解决驾驶员的敏感行为因素对入匝道口的车流量影响的问题,利用人匝道系统模型在开放边界条件下,采用元胞自动机方法得到驾驶员敏感行为因素引入与否的入匝道口处的车流量数据,得到了不同车辆运行方式条件下入匝道系统各路段的交通流图.结果表明,引入驾驶员敏感行为因素能够显著提高主干道上的车流量;当主干道上车辆较少而匝道上车辆较多时,引入驾驶员敏感行为因素能够显著提高匝道路段的车流量.当主干道和匝道上车辆均较多时,匝道上车辆的随机减速过程更为频繁,从而导致匝道路段流量降低,而驾驶员的敏感驾驶行为在一定程度上能够减少道路瓶颈处堵塞情况的发生.     

基于动态神经网络集成的驾驶员行为学习算法*

特定交通环境下的驾驶员行为的变化是一个非线性的复杂系统,传统的驾驶决策模型和车辆行驶模型难以体现驾驶员的感知、判断、决策、动作等一系列心理、生理活动的不确定性和不一致性,而人工神经网络特别适合于因果间不易建立明确联系的问题。提出了基于神经网络集成的驾驶员行为学习算法DNNIA,该算法的有效性通过标准数据集和仿真实验得到了验证,学习到的诸如驾驶员踩踏踏板的习惯行为的仿真结果与采集的样本数据总体趋势较为一致,且实现了系统泛化性能的提高。     

基于人类视觉皮层双通道模型的驾驶员眼动行为识别

驾驶员的危险行为会增加交通事故的发生率,目前对驾驶员行为的研究中大多通过面部识别等方法对异常行为如疲劳驾驶、接电话等进行识别.这种方法仅客观地对驾驶员行为进行分类,而忽略了他们在驾驶过程中的主观心理.眼动仪是记录和分析驾驶员眼动数据的有效工具,可以清晰地了解驾驶员的想法并总结其视觉认知模式.因为目前还没有针对驾驶员眼动...     

基于车载传感信息融合的电动汽车驾驶行为辨识

本文的主要目的是基于信息融合的方法设计出一套能准确辨识出驾驶行为的系统.本系统使用六轴加速度计采集加速度信息,通过多尺度多重分形(MMA)算法(首次将该算法用作特征提取的方法)从加速度信号中提取出可反映不同驾驶行为的波动特征.并采集电动汽车的OBD接口获取的包括速度、功率、电流等车载OBD信息并提取特征.分别通过随机森林(RF)算法对驾驶员的驾驶行为进行辨识.提出一种新的信息融合的方法,采用该方法对加速度信息和OBD信息进行融合,发现信息融合的方法可以更有效的辨识出电动汽车的驾驶行为.     

河北省治超处罚联网系统的设计与实现

为了更好地提升治超效果,加强对违规超载运输车辆、驾驶员和企业的管理,设计了治超处罚联网系统,通过采集外部系统的处罚数据和车辆、驾驶员、运输企业等基础数据,并按照相应规则对数据进行清洗、规范化处理和存储,从而满足黑名单的生成.系统实现了治超处罚形势综合分析预测、处罚信息管理、黑名单管理和处罚备案等功能,为治超工作提供助力.     

基于ARM-Linux的驾驶员路面考试监控系统设计

针对驾驶员路面考试过程中存在的舞弊行为,提出基于ARM Linux的驾驶员路面考试监控系统.该系统以ARM9系列芯片S3C2440为核心,通过USB摄像头采集驾驶员图像信息,GPS模块采集车辆位置信息,CF卡存储图像及位置信息等方法可以有效地解决上述问题.该系统使用方便,可扩展性强,可靠性高.     

基于CAN数据的渣土车驾驶行为分析

摘要：针对渣土车辆管控的要求,着力于分析渣土车驾驶员的驾驶行为,以达到提高渣土车驾驶员的驾驶素质、规范其日常驾驶行为和行车安全意识,减少安全事故发生的目的;通过对渣土车辆的北斗定位数据和CAN数据进行采集与解析后,利用K-means聚类算法对渣土车驾驶员的驾驶倾向性进行识别;然后构建司机驾驶行为评分模型,使用熵权层次分析法来确定每个指标的权重,进而由权重来制定指标分值,最终对渣土车驾驶员进行综合评分,实现对渣土车驾驶员的驾驶行为分析。 关键词：CAN数据;驾驶行为;聚类;北斗定位;评分模型     

基于人类学的汽车驾驶员人机交互研究

文章在传统用户研究基础上,引入基于人类学的实地定性研究方法。获取驾驶员的驾驶行为与生活形态,驾驶性能和行为,驾驶情境和环境信息数据。并在此基础上,建立新的设计与研究框架。最后,利用研究成果和设计概念,开发了一个基于Web的设计知识系统-交通工具用户界面设计知识系统（TUI）。     

Situation awareness assessment in critical driving situations at intersections by task and human error analysis

The rapid development of sensor and tracking technology enables deployment of new Advanced Driver Assistance Systems (ADAS) that support the driver not just on highways but in urban areas as well. Intersections particularly present critical traffic scenarios where almost 35% of accidents occur, partially due to the present lack of in‐depth research about human errors and their determinants. The first step in ergonomic design of ADAS is to identify the specific situations in which drivers require support. To contribute to identification of such spots, situation awareness of 20 drivers in four critical intersection scenarios was explored. The study was conducted in the fixed‐base driving simulator. The applied approach consisted of assessing drivers' expectations and mental workload and of comparing theoretically correct cognitive behavior to experimentally collected data. Intersection scenarios were divided into five segments, and for each segment a task analysis was made. The study has shown that the driving simulator environment can be successfully deployed to provoke and explore various driver errors. The results have revealed that, in scenarios in which information is objectively missing, the majority of errors happened because the drivers had inaccurate mental models of particular scenarios. To the contrary, in the complex scenario the major cause of accidents was information overload. Furthermore, the task analysis disclosed applicable areas of intersection assistance. © 2010 Wiley Periodicals, Inc.     

Design,tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance

This paper describes the design, tuning, and evaluation of a full-range adaptive cruise control (ACC) system with collision avoidance (CA). The control scheme is designed to improve drivers’ comfort during normal, safe-driving situations and to completely avoid rear-end collision in vehicle-following situations. Driving situations are divided into safe, warning, and dangerous modes. Three different control strategies have been proposed, depending on the driving situation. The driving situations are determined using a non-dimensional warning index and the time-to-collision (TTC). The control parameters of the proposed ACC/CA system are tuned by a confusion-matrix method using manual-driving data in no-crashing driving situations. The vehicle-following characteristics of the subject vehicle were compared to real-world, manual-driving data. Finally, the ACC/CA system was also implemented in a real vehicle and tested in both safe-traffic and severe-braking situations. It is shown that the proposed control strategy can provide natural following performance that is similar to human manual-driving in both high-speed driving and low-speed stop-and-go situations. Furthermore, it can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

Development and application of an integrated traffic simulation and multi-driving simulators

Professional virtual reality experiment tools, including driving simulators and traffic simulators, have their strengths and weaknesses. The integration of the two simulators will enhance the ability of both traffic modeling and driving simulation and present a new area of applications. This paper develops, implements, and validates an experimental platform that integrated a traffic simulator with multiple driving simulators (TSMDS). As a connected multi-user framework that allows multiple drivers who are simultaneously handling many driving simulators, it not only allows driver behavior experiments to be more accurate, controlled, and versatile but also simulates special driving behavior or multi-vehicle interactions under more realistic traffic flow environments. To validate the performance of TSMDS, 27 drivers were recruited to attend the lane changing experiments at a recurring on-ramp bottleneck and left-turn experiments at a two-phase signalized intersection in Shanghai. Both experiments required several drivers to drive the TSMDS and fulfill several complicated lane changing/crossing behaviors through their interaction. The results show that both the participants’ response and lane changing/crossing data that were obtained from the experiment are consistent with the field observation, which confirms the validity of the integrated platform.     

The influence of alarm timing on driver response to collision warning systems following system failure

This driving simulator study focuses on false and missing alarms produced by a forward collision warning system and estimates the effect of alarm timing on driver response to alarm malfunction from the perspective of driver trust in alarms. The results show that drivers who experience late alarms are reluctant to respond to a false alarm and are not influenced by a missed alarm; however, drivers who experience early alarms tend to respond to a false alarm and suffer a delayed response to critical situations when a missing alarm happens. Furthermore, drivers whose judgement of trust is relatively high, tend to exhibit delayed braking, compared with drivers that have lower levels of trust. Driver behaviour towards false and missed alarms may vary according to alarm timing and its influence on trust in alarms; moreover, impaired system effectiveness caused by alarm malfunction may be mitigated by manipulating alarm timing.     

The influence of alarm timing on driver response to collision warning systems following system failure

This driving simulator study focuses on false and missing alarms produced by a forward collision warning system and estimates the effect of alarm timing on driver response to alarm malfunction from the perspective of driver trust in alarms. The results show that drivers who experience late alarms are reluctant to respond to a false alarm and are not influenced by a missed alarm; however, drivers who experience early alarms tend to respond to a false alarm and suffer a delayed response to critical situations when a missing alarm happens. Furthermore, drivers whose judgement of trust is relatively high, tend to exhibit delayed braking, compared with drivers that have lower levels of trust. Driver behaviour towards false and missed alarms may vary according to alarm timing and its influence on trust in alarms; moreover, impaired system effectiveness caused by alarm malfunction may be mitigated by manipulating alarm timing.     

基于车辆行驶数据的驾驶人行为谱分析方法

针对我国驾驶人行为谱的研究尚不完善，专业领域内没有相应的行为谱分析工具的问题，提出了一套针对营运客车的完整的驾驶人驾驶行为谱体系并设计了一套分析工具。首先，设计并定义了驾驶人行为谱的特征指标和评价指标；其次，给出了驾驶人行为谱的特征指标分析、计算方法，采用基于马尔可夫链蒙特卡洛采样和离群点剔除的K-means算法对驾驶人的驾驶风格进行分析，采用回归学习对驾驶人的驾驶技能进行分析；然后，设计了基于车联网、大数据的驾驶人行为谱的基础数据采集和预处理方法；最后，采用Java语言、Spring MVC架构开发出驾驶人行为谱分析工具。将机器学习中的数据挖掘、数据分析算法与交通安全领域相结合，对完善我国驾驶人行为谱框架体系具有理论意义，为我国驾驶人行为谱的研究提供了一个科学、定量化分析的工具，对交管部门规范驾驶人驾驶行为、提高道路安全指数、制定合理的交通安全管理策略具有指导意义。     

Drivers’ willingness to drive in old age: a case study on young and mid-aged drivers in China

Previous studies on driving have found connections among age, gender, perceived driving ability, self-regulatory behavior and driving intentions. However, young and mid-aged drivers’ willingness to drive in old age has not been examined in prior studies. The aim of the present study was to gain a better understanding of Chinese drivers’ willingness to drive in old age as well as the influence of predictors of this willingness. A sample of 334 participants (aged 20–62 years) completed the perceived driving abilities scale, the driving willingness scale and scales of driving behavior and general information. A multivariate logistic model was used to explore the factors that changed individuals’ willingness to drive in old age. The results indicated that drivers’ willingness to drive in old age was significantly correlated with age, current driving experience and perceived driving ability in the future. With respect to drivers’ perceived driving abilities, visual acuity and executive skills were important predictors of drivers’ willingness to drive in old age. In addition, both subjective attitudes and objective attitudes significantly impaired drivers’ willingness. Conversely, we found that drivers’ willingness to drive increased with restrictive measures. These findings extend our understanding of how attitudes and awareness can influence drivers’ willingness to drive in old age. Although drivers’ current willingness may subsequently change, the findings are valuable for the study of the driving behavior of older drivers in China.