汽车底盘测功机辅助驾驶装置的设计及其系统仿真

针对汽车底盘测功机进行试验时的人为误差因素,提出了辅助驾驶装置的设计方案及其模糊控制策略,并利用MATLAB/SIMULINK工具进行仿真。     

自动驾驶汽车的仿真

随着汽车自动化程度的提高，自动驾驶汽车已成为国内外的研究热点之一。本文设计了一种自动驾驶汽车的模型，它能根据道路的弯曲程度变化实时地计算出车辆的转向角度输入，控制车辆按照预设想道路行吮。     

Sustainability and automobility among the elderly: An international assessment

In the next three decades there will a huge increase in both the absolute number of older people and in their percentage of the populationin almost all Western European countries, North America, and Australia. Most older people will have active lifestyles in which mobility and access play a major role and almost all older men and a majority of older women will be car drivers, used to the convenience and flexibility which the car provides.Using data from the US, Australia, Germany, New Zealand, Norway, and the United Kingdom, the paper shows that, in spite of cultural and policy differences, older people around the world are more likely to have a license, to take more trips, and to do so more often as the driver of a car than older people just a decade ago; they are also less likely to use public transit. These trends have a number of sustainability implications – the most obvious one is increased environmental pollution. For example, even though older people may travel less than younger drivers they may be polluting proportionately more because a) they are less likely to make as great a proportion of trips in public transit as younger people and b) the trips they do make may create more pollutants. In addition, older drivers may incur more wasted miles due to wayfinding errors and trip-scouting behavior. And when older people curtail their driving, younger family members may have to increase (or lengthen) their trip-making to provide needed services or additional transportation.While this paper stresses the environmental problems posed by an aging population, effective strategies arise from a focus on a broader definition of sustainability. The most important approach is to accept the inevitable and work to make the private car "greener" and safer. New transit service concepts and strategic community and neighborhood design and service elements can complement the development of cleaner cars.Although many of the potential strategies are not new, or can be expensive to implement, the convergence of environmental concerns with other problems arising from the automobility of the elderly – including increasing crash rates and serious loss of mobility among those unable to drive – may make these policies more politically viable than in the past.     

基于大数据的乘用车油耗与续驶里程研究

基于全球乘用车整备质量、燃油箱容积和燃油消耗量数据的统计分析,推算出"NEDC工况"下的续驶里程;再通过众测油耗的统计分析,推算出乘用车满油箱燃料的实际续驶里程范围;对乘用车的供油系统设计及电动乘用车的续驶里程对标燃油车提供依据。     

Integrated solution for anomalous driving detection based on BeiDou/GPS/IMU measurements

There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, centimeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.     

电动汽车动力电池低温性能研究与应用

电动汽车锂离子动力电池在低温条件下工作时,电池的内阻明显升高、功率和能量急剧下降,导致整车低温下动力性能不足、续驶里程不足、充电受限等问题。通过试验进行了动力电池的低温特性研究,提出了适合整车低温工作的解决方案,通过实车验证,达到了很好的效果。     

靶场试验指挥控制中心系统及其应用

针对靶场试验指挥控制中心的应用需求，介绍靶场试验指挥控制中心系统的功能、特点以及体系结构和组成，分析系统研制的关键技术，说明该系统的应用范围。目前，该指控中心系统已成功地应用于某大型武器系统靶场试验中，取得了较好效果。     

汽车驾驶员不安全行为评价分析

为稳步增强汽车驾驶的安全性,减少安全事故的发生,驾驶人员除了需要具备足够的应急应变能力之外,还需要做好安全行为习惯养成工作,形成良好的驾驶习惯。文章以汽车驾驶员不安全行为作出研究对象,在明确不安全行为表现的基础上,深刻分析影响汽车驾驶人员不安全行为的因素,在此基础上,制定合理的应对策略,旨在引导驾驶人员形成安全行为,以不断提升驾驶员的驾驶能力。     

人机混驾环境下基于LSTM的无人驾驶车辆换道行为模型

道路系统中的人机混驾交通环境是指人工驾驶车辆与自动驾驶车辆混合运行的交通环境，其中换道行为建模是人机混驾环境下无人驾驶车辆行为研究的热点。基于深度学习理论，构建人机混驾环境下基于长短期记忆神经网络的无人驾驶车辆换道行为模型（Long-short-term-memory-based Autonomous Vehicles Lane Changing，LSTM-LC）。通过研究人工驾驶车辆在换道过程中与周边车辆的相互作用，对换道行为影响因素进行分析；同时，为了提升模型的迁移性，引入道路横向偏移量信息。结合LSTM神经网络的输入要求，使用美国公开交通数据集Next Generation SIMulation（NGSIM）构建换道行为样本库。针对LSTM-LC模型，以均方差MSE作为损失函数，使用RMSprop优化方法进行训练，对LSTM网络结构、历史序列长度N及训练样本量3个重要参数进行标定。最后，针对道路横向偏移量M对LSTM-LC模型性能的影响进行对比试验。研究结果表明：相比GRU-LC模型，LSTM-LC模型对换道行为的表征更准确，在模型的精度和迁移性上有着显著的提升；GRU-LC模型的均方差为4.64 m²，迁移性均方差为119.82 m²，而LSTM-LC模型的均方差为3.18 m²，迁移性均方差为79.58 m²，分别优化了31.5%和39.71%；通过引入道路横向偏移量M，可将LSTM-LC模型精度和迁移性提升约10%，且模型稳定性更强。     

卫星定位数据驱动的营运车辆驾驶人驾驶风险评估模型

为了提高营运车辆驾驶人安全管理的精细化水平，合理地评估驾驶人驾驶风险程度，有的放矢地降低高风险驾驶人的事故率，基于卫星定位数据特点及驾驶行为与驾驶风险的相关关系设计26个驾驶行为特征参数。考虑到高速和非高速行驶时相同驾驶行为对驾驶风险的影响区别较大，根据23名营运车辆驾驶人的实测数据有针对性地筛选高速和非高速路段驾驶人风险评估指标，构建营运车辆驾驶人驾驶风险评估指标体系。然后，基于熵权法、独立性权系数法和Spearman相关系数法建立集成赋权法，确定各评估指标的权重。最后，雇佣40名营运车辆驾驶人进行实车试验以验证模型的合理性。结果表明：车辆速度和加速度方面的驾驶行为特征可以用于评估驾驶人的驾驶风险且评估效果较好，驾驶风险评估得分与实际交通冲突次数呈正相关关系，所建立模型可以较为准确地评估营运车辆驾驶人驾驶风险的高低，准确率达到77.50%，该模型在不同地区使用时，准确率存在一定的差异，但在容许范围之内，方法具有较好的鲁棒性。