汽车生活情报

<正>"法拉利模拟学院20 1 0"横空出世9月9日,法拉利车队首款在线虚拟模拟系统"法拉利模拟学院"正式发布。此款虚拟模拟系统的开发工作得到了阿隆索、马萨和费斯切拉以及车队工程师的全力配合,将可以虚拟体验到驾驶法拉利F10的全部感觉。在首次发布的版本中,车迷可通过网络在著名的费奥拉诺赛道进行     

面向公路智能预警系统效用评价的驾驶模拟实验设计

随着智慧交通的发展，高速公路利用智能预警系统提升多因素影响高原山区高速公路互通立交区进出匝道的通行安全性与通畅性。为进一步评价预警系统的有效性，研究设计了驾驶模拟仿真实验，通过搭建典型低能见度天气下的虚拟场景的道路、交通、环境和交通流，通过驾驶模拟器、无线生理仪和眼动仪等设备采集驾驶员的驾驶行为和生理心理数据，通过不同场景的模拟仿真，对不同预警系统应用条件下的驾驶行为的变化进行分析。实验招募了50名驾驶人完成共12个互通立交进出口匝道场景的闭环虚拟仿真实验，利用实验设备采集了速度、加速度、皮电、心率以及注视扫视等数据，通过统计分析驾驶人在不同能见度、进出口匝道以及有/无预警系统的场景中的驾驶行为数据和生理心理数据，为预警系统的有效性分析提供定量化的评价。实验结果表明，预警系统能够有效提高驾驶人的驾驶安全性；此外，对比互通匝道预警系统对不同驾驶经验的驾驶人的影响，发现对驾龄>10年的驾驶人的警示效果更好。     

基于场景的自动驾驶汽车虚拟测试研究进展

随着自动驾驶等级的提高，面向传统汽车的测试工具与测试方法已不能满足自动驾驶汽车测试的需要。基于场景的虚拟测试方法在测试效率、测试成本等方面具有巨大的技术优势，是未来自动驾驶汽车测试验证的重要手段，已成为当前的研究热点。通过对大量相关文献的系统梳理，综述了基于场景的自动驾驶汽车虚拟测试研究进展。对比分析了自动驾驶测试场景的不同定义方式，明确了测试场景的内涵，归纳了测试场景的要素种类，概述了测试场景的数据来源，总结了场景数据的处理方法。在此基础上，对自动驾驶汽车虚拟测试方法进行了总结，分析了典型的测试方式、测试平台和虚拟测试的技术要点，梳理了软件在环、硬件在环和车辆在环测试方案及其关键技术。针对自动驾驶汽车测试效率问题，研究了基于场景的加速测试技术，概述了典型的测试场景随机生成方法和危险场景强化生成方法。最后，对基于场景的自动驾驶汽车虚拟测试所面临的问题及未来发展趋势进行了分析和展望。研究结果表明：基于场景的虚拟测试是推动自动驾驶技术发展和产业落地的必由之路，未来研究应着力突破基于解构与自动重构的测试场景数据库、人-车-环境系统一体化高置信度建模、自动驾驶汽车虚拟测试标准工具链、不同自动驾驶汽车渗透率下的混合交通模拟与测试、测试案例动态自适应随机生成机制等核心共性技术，建立自动驾驶汽车虚拟测试标准体系。     

基于虚拟驾驶轨迹的高速公路安全评价

汽车驾驶模拟器能准确记录在虚拟道路上行驶的驾驶轨迹。为了研究驾驶员对未建成高速公路的客观反应数据,本文提出通过研究超速状态下的汽车驾驶轨迹来评价高速公路安全性的方法。通过选取不同职业、性别和熟练程度的驾驶员进行实验,对他们在模拟器上的驾驶轨迹进行研究表明:驾驶轨迹分散、混乱、相互交叉频繁、波动幅度大的路段安全隐患较大,与高速公路实际事故数据相比结果基本一致。     

基于整车在环仿真的自动驾驶汽车室内快速测试平台

整车在环仿真测试方法可以安全、高效地验证复杂环境和极端工况等场景下自动驾驶汽车性能的有效性，基于此研发一种基于整车在环仿真的自动驾驶汽车室内快速测试平台，该平台由前轴可旋转式转鼓试验台、试验台测控子系统、虚拟场景自动生成子系统、虚拟传感器模拟子系统、驾驶模拟器、自动驾驶汽车和测试结果自动分析评价子系统组成。通过在试验台滚筒上独立加载转矩模拟车辆行驶阻力，可动态模拟不同的路面附着系数，同时利用坡度、侧倾和转向随动机构可模拟车辆俯仰角、侧倾角和航向角3个自由度；采用虚拟现实技术柔性集成车辆动力学模型、传感器仿真、复杂道路交通环境及测试用例仿真，模拟多种道路交通场景，并通过传感器仿真及数据融合等技术快速测试自动驾驶汽车智能感知与行为决策等性能指标。将自动驾驶汽车、虚拟仿真场景和试验台耦合构建一个闭环系统，完成了多项关键技术研发，包括：多自由度高动态试验台结构设计、虚拟测试场景自动重构方法和传感器数据模拟及注入方法，可满足在各种场景下测试自动驾驶汽车整车性能的需求。此外，为验证快速测试平台的有效性，以U-turn轨迹跟踪控制为研究实例，基于简化的车辆运动学模型和模型预测控制算法，在平台上搭建U-turn场景并对自动驾驶汽车的轨迹跟踪控制算法性能进行大量测试。结果表明：自动驾驶汽车室内快速测试平台可以真实地模拟汽车在道路上的运行工况，自动驾驶汽车在虚拟场景中的轨迹跟踪效果良好，与参考轨迹的偏差小于8%，证明了该测试平台检测方法的有效性。     

基于Vissim的驾驶模拟系统交通流仿真

在道路交通驾驶模拟系统开发平台的基础上,加载动态车流,以实现交通流的真实性,利用Vissim的交通流仿真功能,通过编程语言VC对驾驶模拟系统与Vissim的接口进行了研究,实现了道路交通驾驶模拟系统的交通流仿真,并通过实例验证了这一方法的有效性和实用性.     

基于GT-SUITE的乘用车驾驶性仿真与应用

为了在整车性能开发早期对驾驶性进行评价,本文中使用GT-SUITE软件,考虑发动机瞬态响应和转矩控制策略,建立乘用车驾驶性仿真模型。利用仿真模型对部分典型的驾驶性工况进行仿真计算,并通过试验数据校正模型,确保仿真误差在10%以内。以某6速自动挡汽油车为例,针对3种驾驶模式的不同需求,分别对油门特性和换挡规律进行虚拟标定。最后对虚拟标定结果进行试验验证,仿真与试验误差在8%以内,充分验证了驾驶性虚拟标定的有效性和实用性。     

面向道路交通的汽车驾驶模拟器的研究及应用

研究开发了一套可在实验室控制条件下研究交通问题的汽车高级驾驶模拟器。该模拟器由驾驶舱系统、主计算机控制系统、驾驶员虚拟视景系统和声响模拟系统组成，既可用于模拟和分析某一真实路段的道路和交通情况，又可评价和检验设计中或已设计完的道路交通。     

微机实时控制与计算机成像技术在汽车驾驶模拟系统中的应用

对汽车驾驶模拟系统应用微机实时控制与计算机成像技术所涉及的建立控制模型及提高计算机成像产生道路视景的计算速度等方面的问题，从理论和实践上进行研究，并建立了适用于汽车驾驶员培训的模拟系统。试验结果表明，控制系统的模拟特性接近于实车特性。     

隧道烟雾环境对行车安全影响研究

通过UC-win/Road模拟驾驶软件和简易驾驶模拟器以及人体反应时间测试仪,对隧道内不同浓度的烟雾环境进行模拟,并在此环境内以不同的速度进行模拟驾驶。通过实验数据的回归分析,得出了驾驶员在烟雾环境下的反应时间可按规范中取值的结论。并得到了视认距离与车速和烟雾浓度的关系,指出了驾驶员在车速升高时注视点会前移,也给出了安全距离随车速和烟雾浓度的变化规律。     

基于SOM神经网络的多工况驾驶风格识别

不同的驾驶员对车辆的各项性能可能有个性化地要求,因此有必要对驾驶风格的分类与识别问题进行研究。首先在驾驶模拟器上采集不同驾驶员在多工况下的数据,利用主成分分析法选取驾驶员在各个工况下的特征参数,SOM神经网络分别对起步、加速及制动工况下的驾驶数据进行了聚类分析,然后以驾驶风格聚类分析结果为基础,建立了基于SOM神经网络的驾驶风格识别系统,该系统可根据驾驶员驾驶历史数据来判断其驾驶风格,最后以某一温和型驾驶风格识别结果为例验证了系统的合理性。     

Mental flexibility impairment in drivers with early Alzheimer's disease: A simulator-based study

After memory impairment, one of the most common troubles of early Alzheimer's disease (AD) is the impairment of executive functioning. However, it can have major consequences on daily life, notably on the driving activity. The present study focused on one important executive function involved in driving: mental flexibility; and considered how this impairment can affect driving. Ten patients with early AD were matched with 29 healthy older drivers. All participants were given an evaluation of mental flexibility through neuropsychological tests and an experimental test developed on a static driving simulator. The experiment was divided in two conditions; one without mental flexibility and another condition with a mental flexibility demand. AD patients showed impairments in the neuropsychological tests evaluating mental flexibility. These deficits are linked to the deficits they showed in the driving simulator flexibility tests. This study contributes to the understanding of mental flexibility mechanisms and on their role in driving activity. It also confirms that the driving simulator is a suitable tool to explore cognitive disorders and driving ability.     

山区公路爬坡车道的交通特性及驾驶安全性模拟评价

以山区公路上设置的某一爬坡车道为试验对象,利用驾驶模拟试验对其交通特性及驾驶安全性进行仿真。根据设计图和现场环境构建了三维虚拟试验场景,通过VISSIM生成试验路段交通流;32名受试者在4种交通条件下进行了驾驶模拟试验;模拟过程中记录车辆的速度、轨迹、加速度、制动力等数据;通过VISSIM仿真试验确定了该爬坡车道的交通量阈值。分析结果表明,在常规交通流情况下,该爬坡车道可提高主路上的车速及其平稳性,同时可减少来自对向车道的冲突;但随着交通流量趋于饱和,其有效性逐渐减弱甚至产生负面影响。     

Vehicle sensor data-based analysis on the driving style differences between operating indoor simulator and on-road instrumented vehicle

Abstract

Indoor simulator and on-road instrumented vehicle are the most popular ways to analyze driving behaviors by using collected Vehicle Sensor Data (VSD). However, for a same driver, the driving performance could be different in the real world and in the simulated world. Even though many studies have been conducted to discover the differences of driving behaviors in these two circumstances, little research has focused on analyzing the differences in driving style, which can provide more integrated knowledge of a driver from the natural structure, stimulus–response mechanism, of driving behaviors. Therefore, in this paper, the driving styles in both the real world and the simulated world are extracted by implementing the nonnegative matrix factorization method on the collected VSD data. Through this analysis, the driving style differences can be quantitatively described and discussed in detail. It is found that the drivers tend to be more unstable and sometimes aggressive when driving the simulator and the deviation in the perception of temporal gap in two circumstances is also discovered. The research findings are particularly valuable to calibrate the driving simulator and construct more reliable driving behavior models.     

Effect of the front and rear weight distribution ratio of a Formula car during maximum-speed cornering on a circuit

Because Formula cars are lighter than ordinary cars, the optimal settings for this type of car are thought to be different from those of a ordinary car. The front and rear weight distribution ratio of a vehicle is an important parameter that exerts a significant influence on critical cornering. The tendency of a ordinary car to under-steer during critical cornering is determined by the front and rear weight distribution ratio of the vehicle. Specifically, when the front of an ordinary FR (front-engine, rear wheel drive) vehicle is slightly heavier than the rear, the car tends to understeer during critical cornering. However, the optimal weight distribution ratio for critical cornering is not obvious for a formula car because of its lightness. This observation was investigated using a driving course similar to a real driving course to perform a maximum speed cornering simulations. It was found that a front to rear weight distribution ratio of 40:60 resulted in the fastest lap time. This ratio also gave the best results in the maximum-speed driving experiment performed using a driving simulator. Moreover, the maximum lateral acceleration during turning, the driving force, and the load movement of the inside and outside wheels was calculated using experimental driving force data and the concept of a tire friction circle. As a result, driving mechanics have been determined for a vehicle having a front/rear weight distribution ratio of 40:60 while traveling at maximum speed.     

小街区密路网交通标志缩尺研究

应用驾驶模拟器、眼动仪和调查问卷对小街区密路网条件下的交通标志设计方案和缩尺方案进行了分析探讨。驾驶模拟器采集的速度和加速度数据显示设计方案和缩尺方案具有差异显著性，眼动仪数据显示缩尺方案需要更多的注意力。调查问卷显示，大多数人主观上无法准确感受到两个方案之间的差异，缩尺方案的可行性还需要进行深入研究。     

Application of a driving simulator to the development of in-vehicle human-machine-interfaces

The use of a driving simulator in the development of human-machine-interfaces (HMI) such as a navigation, information or entertainment system is discussed. Such use addresses the need to study and evaluate the characteristics of a candidate HMI early in the R&D and design stage to ensure that it is likely to meet various objectives and requirements, and to revise the HMI as may be necessary. Those HMI requirements include such things as usability, driver comfort, and an acceptable level of attentional demand in dual task conditions (driving while using an HMI). Typically, such an HMI involves an information display to the driver, and a means for driver input to the HMI. Corresponding simulator requirements are discussed, along with typical simulator features and components. The latter include a cab, control feel systems, visual image generator, real time scenario control (task definitions), a motion system (if provided), and data acquisition. Both fixed and moving base systems are described, together with associated benefits and tradeoffs. Considerations in the design of the evaluation experiment are discussed, including definition of primary and secondary tasks, and number of driver subjects (experimental participants). Possible response and performance measures for the primary and secondary tasks are noted, together with subjective measures such as task difficulty and ease of using the HMI. The advantages of using a driving simulator to support R&D are summarized. Some typical and example simulator uses are noted.     

汽车驾驶模拟器在交通安全中的应用综述

汽车驾驶模拟器是1种研究“人‐车‐路‐环境”交通特性的重要工具,由于具有重现性好、安全性高、成本低等优势,被广泛应用于交通研究方面,尤其因其能够在危险场景中采集多种车辆数据,近年来汽车驾驶模拟器在交通安全方面的研究进展飞速。文中简要介绍了汽车驾驶模拟器的国内外发展历史,从驾驶分心、道路设计、交通设计、交通事故和驾驶疲劳5个方面梳理出汽车驾驶模拟器在交通安全领域的应用研究,并分析了这5个方面研究领域中驾驶模拟器实验的其中利弊,探讨了汽车驾驶模拟器在中国交通安全研究中的应用前景及存在的问题。      

In-vehicle display HMI safety evaluation using a driving simulator

Recently, telematics services and in-vehicle display devices such as the CNS (Car Navigation System) have become new causes of traffic accidents. These accidents are caused by ‘Inattention’ from the increase of the driver’s mental workload while he/she is driving. The driver of a vehicle (except for emergency or police vehicles) must not use a hand-held mobile phone while the vehicle is moving. To address this problem, Australia, England, Italy, Brazil and some states in the US have banned the use of hand-held mobile devices during driving. However, there are no restrictions on the use of in-vehicle displays or on the display’s positions. The position of a navigation system in a vehicle should be assessed objectively, and the effect of the position on the driver’s attention should be studied. Some existing research reports that in-vehicle distraction not only leads to reduced speeds and more frequent lane switching, but also more gazing by the driver to the centre of the road. In this study, to develop an assessment method and to propose the proper position of a CNS, an experiment is carried out in a driving simulator environment. Different methods to track the gaze and physical parameters of the driver are used for HMI (Human-Machine Interface) assessment. The experiment is carried out in a driving simulator to observe the glancing distribution during driving according to the position of the navigation system. Fourteen subjects participated in this experiment. Changes in subjects’ physiological signals and glancing distribution rates were collected.     

Measuring the safety impact of road infrastructure systems on driver behavior: Vehicle instrumentation and real world driving experiment

Featured in this pilot experimental study is the construction and design of an instrumented vehicle that is able to capture vehicle trajectory data with an extremely high level of accuracy and time resolution. Once constructed and properly instrumented, the various data collection systems were integrated with one another and a driving experiment was conducted on northern Virginia roadways with 18 participants taking part in the study. Trajectory data were collected for each of the drivers as they traversed a predefined loop of four roadway segments with varying numbers of lanes and varying shoulder widths. Data collected from the experiment were then used to calibrate the parameters of the prospect theory car-following model through a genetic algorithm calibration procedure. Once all model parameters were successfully calibrated, significance testing was carried out to determine the impacts that the varying roadway infrastructure had on driving behavior. Results indicated that there were significant changes in behavior when comparing one lane roadways to their two lane counterparts—specifically in cases where the roadway featured a wide shoulder. Additional testing was conducted to ensure that there was no variation based on gender, as nine study participants were female and nine were male. The successfulness of this first study conducted with the newly constructed instrumented vehicle creates the opportunity for a variety of additional studies to be conducted in the future.