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紧急避障工况下的驾驶人操作具有响应快且动作幅值较大的特点,传统预瞄驾驶人模型已不能适应紧急避障工况的需求,故考虑实际避撞场景开发相应的驾驶人模型就显得尤为必要。针对此种状况,基于驾驶模拟器,结合紧急避撞工况实际驾驶人操纵数据,提出了一种融合预瞄与势场栅格法的紧急避撞驾驶人模型。首先针对紧急避撞工况下车辆运动特点,建立车辆横、纵向耦合非线性动力学模型,并给出其状态空间方程描述;其次,离线仿真分析紧急避撞系统特征,并结合线性二次型最优控制,建立最优曲率预瞄+跟踪误差反馈驾驶人模型;再者,基于紧急避撞工况下真实驾驶人经验转向行为数据,开发基于势场栅格法的驾驶人模型,为进一步提高驾驶人模型对避障行驶工况的适应性,将基于势场栅格法的驾驶人模型与最优曲率预瞄+跟踪误差反馈驾驶人模型进行融合,并基于Sigmoid函数实现两者输出的权重分配;最后,针对所提出的融合预瞄与势场栅格法的驾驶人模型,开展基于避撞台架的驾驶人在环仿真试验以及实车试验。研究结果表明:在紧急避撞工况下,对比最优曲率预瞄+跟踪误差反馈驾驶人模型,融合预瞄与势场栅格法的驾驶人模型输出的转向动作与实际驾驶人行为较为接近,可在保证避障安全性的前提下,兼顾避障路径跟踪精度与车辆行驶的稳定性。 相似文献
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行车紧急度主观判断与车辆行驶控制 总被引:1,自引:0,他引:1
在交通部试验场利用动态心电分析仪、Frecord数据采集系统及动态GPS,研究驾驶员特征对紧急状况主观评价和车辆行驶控制的影响。研究表明,具有不同驾驶经验、个性、年龄特征的驾驶员对同一紧急状况做出的紧急度主观评价和制动操纵存在差异,其中驾驶经验的影响最明显。经验丰富的驾驶员采用减速度相对较小,变化相对平缓;相对于谨慎型驾驶员而言、鲁莽型驾驶员制动减速度变化剧烈;年龄对驾驶员操纵也有一定影响,通常年轻驾驶员会进行快速制动,这与驾驶员的生理状况有很大关系。研究结果可为驾驶员安全管理提供理论依据。 相似文献
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Gü nther Prokop 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2001,35(1):19-53
A driver model is designed which relates the driver's action to his perception, driving experience, and preferences over a wide range of possible traffic situations. The basic idea behind the work is that the human uses his sensory perception and his expert knowledge to predict the vehicle's future behavior for the next few seconds (prediction model). At a certain sampling rate the vehicle's future motion is optimized using this prediction model, in order to meet certain objectives. The human tries to follow this optimal behavior using a compensatory controller. Based on this hypothesis, human vehicle driving is modeled by a hierarchical controller. A repetitive nonlinear optimization is employed to plan the vehicle's future motion (trajectory planning task), using an SQP algorithm. This is combined with a PID tracking control to minimize its deviations. The trajectory planning scheme is experimentally verified for undisturbed driving situations employing various objectives, namely ride comfort, lane keeping, and minimized speed variation. The driver model is then applied to study path planning during curve negotiation under various preferences. A highly dynamic avoidance maneuver (standardized ISO double lane change) is then simulated to investigate the overall stability of the closed loop vehicle/driver system. 相似文献
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A driver model is designed which relates the driver's action to his perception, driving experience, and preferences over a wide range of possible traffic situations. The basic idea behind the work is that the human uses his sensory perception and his expert knowledge to predict the vehicle's future behavior for the next few seconds (prediction model). At a certain sampling rate the vehicle's future motion is optimized using this prediction model, in order to meet certain objectives. The human tries to follow this optimal behavior using a compensatory controller. Based on this hypothesis, human vehicle driving is modeled by a hierarchical controller. A repetitive nonlinear optimization is employed to plan the vehicle's future motion (trajectory planning task), using an SQP algorithm. This is combined with a PID tracking control to minimize its deviations. The trajectory planning scheme is experimentally verified for undisturbed driving situations employing various objectives, namely ride comfort, lane keeping, and minimized speed variation. The driver model is then applied to study path planning during curve negotiation under various preferences. A highly dynamic avoidance maneuver (standardized ISO double lane change) is then simulated to investigate the overall stability of the closed loop vehicle/driver system. 相似文献
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车辆转向操纵过程中驾驶员的生理/心理分析与测试 总被引:1,自引:0,他引:1
本文指出驾驶员在行车过程中的生理/心理状态对其操纵行为有着重要影响,着重探讨了驾驶员转向操纵过程中生理/心理问题,首先对驾驶员行车时的心理进行了分析及描述,提出了一种合格驾驶员的心理模型;然后提出了驾驶员身心反应测试的几项指标,并进行了有关的测试,得到了不同驾驶员在不同车速,不同路线下的生理/心理变化规律,本文为建立一个包括驾驶员心理特性,行为规律的综合模型提供了新的依据。 相似文献
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As driving error is a main contributory factor of road accidents, its causes and consequences are of great interest in the road safety decision making process. This paper investigates several factors (including driver distraction, driver characteristics and road environment) that affect overall driving error behaviour and estimates a new unobserved variable which underlines driving errors. This estimation is performed with data obtained from a driving simulation experiment in which 95 participants covering all ages were asked to drive under different types of distraction (no distraction, conversation with passenger, cell phone use) in rural and urban road environment, as well as in both low and high traffic conditions. Driving error was then modeled as a latent variable based on several individual driving simulator parameters. Subsequently, the impact of several risk factors such as distraction, driver characteristics as well as road environment on driving error were estimated directly. The results of this complex model reveal that the impact of driver characteristics and area type are the only statistically significant factors affecting the probability of driving errors. Interestingly, neither conversing with a passenger nor talking on the cell phone have a statistically significant impact on driving error behaviour which highlights the importance of the present analysis and more specifically the development of a measure that represents overall driving error behaviour instead of individual driving errors variables. 相似文献
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司机是一个比较特殊的工作,通常在驾驶汽车时,司机要确保整个驾驶过程的安全,这就要求司机要具备较高的驾驶素质。如果驾驶员自身的安全意识不高,对车辆驾驶工作没有太深的安全意识,就会给行车工作带来很大的安全隐患。如果司机对驾驶工作安全性意识较高,则行车就会更加安全,司机也会提高自己的综合素质和驾驶技术来保证车辆行驶的安全,避免在行驶中出现一系列安全隐患。因此,在驾驶汽车时,要重点突出安全隐患的预防,并制定一系列的对策,才可能减少车辆的安全事故产生。 相似文献
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为了深入分析驾驶模式决策影响因子,通过实车试验采集了人-车-路多源特征信息。用驾驶人主观经验将驾驶模式划分为人工驾驶、警示辅助、自动驾驶3种状态,并利用采集的驾驶人血流量脉冲(BVP)和皮肤电导(SC)值进行K均值聚类,将驾驶人当前合适的驾驶模式自动聚类为3级。通过融合驾驶人自汇报结果和聚类结果对驾驶模式进行准确标定。采用以信息增益为依据的Ranker算法对多特征进行排序,并在此基础上,根据多分类器分级结果确定最优特征属性集合。研究结果表明:当选取车速、车头时距、车道中心距离、前轮转角标准差、驾驶经验5个指标为特征子集时,支持向量机、朴素贝叶斯及K近邻这3种分类器的识别准确率都超过90%;除警示辅助模式与自动驾驶模式下的车速值和车道中心距之外,其余所有不同模式决策属性值均呈显著性差异;研究结果可为人机共驾智能车驾驶模式决策提供依据。 相似文献
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驾驶风格是用来体现驾驶员在车辆运行状态下对车辆操作的行为特征,对用户驾驶风格进行识别与分析,有利于推进智能驾驶的发展。根据基于116 辆纯电动汽车的车辆运行数据,通过主成分分析方法与K-means 聚类算法,对用户驾驶行为进行分类分析,对驾驶风格进行了分类识别。利用XGBoost 算法构建纯电动汽车驾驶行为与能耗输入模型,利用SHAP 对模型进行解释。结果表明,将驾驶风格聚为3 类具有较好的分类效果,可分别对应冷静型、普通型与激进型;当驾驶员的驾驶风格趋向于激进型时时,车辆的驾驶能耗越高,驾驶风格激进一个层级,车辆百公里电耗增加3~4倍。当驾驶员行车时,其车速越高,油门踏板踩得越深,车辆加速度的绝对值越大,车辆的驾驶能耗越高。驾驶员的驾驶风格越激进,车辆的驾驶能耗越高。 相似文献
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驾驶员车道变换视点转移模型及其参数标定 总被引:1,自引:0,他引:1
为了获取驾驶员车道变换行程中的视点转移特性,构建视点转移模型,解决驾驶员行为监控设备布设缺乏依据的难题,采用眼动仪和人工记录的方式,分别以轿车和公交车驾驶员为研究样本,获取了车道变换行为过程中驾驶员视点停留时间和视点位置转移特性数据,给出驾驶员的眼动停留时间均值和分布规律,基于外界的交通运行环境,根据驾驶员对外界信息的获取程度,考虑驾驶员、车辆、道路、环境等影响因素,设定其符合泊松分布,将驾驶行为分为决策阶段和执行阶段,给出了基于6个模块的流程结构,构建基于信息满意度的视点位置转移模型并标定了模型参数。 相似文献
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汽车驾驶员模型是汽车交通安全、智能交通系统、汽车自动驾驶和车辆巡航等技术的基础研究内容和关键环节之一。按照汽车驾驶员模型的研究方向及应用,将驾驶员模型分为基于人—车—环境闭环系统汽车操纵稳定性的驾驶员模型、基于智能交通系统的驾驶员行为模型和基于交通安全的驾驶员疲劳模型等类型,综述了上述各类汽车驾驶员模型的研究现状,对各类驾驶员模型存在的不足进行了分析论述,并展望了汽车驾驶员模型的发展方向及趋势。 相似文献
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为研究驾驶人的跟车特性及探究可适用于不同风格驾驶人的跟车预警规则,为自动驾驶车辆开发可满足不同用户驾驶需求和驾乘体验的主动安全预警系统,选取50名被试驾驶人开展实车试验,采集驾驶人跟车行为表征参数并基于雷达数据确定跟车事件提取规则。选取平均跟车时距和平均制动时距为二维向量,使用基于K-means聚类结果的高斯混合模型将驾驶人聚类为3种风格类型(冒进型、平稳型、保守型)。通过分析3组驾驶人的跟车及制动数据,将不同类型驾驶人的制动时距分位数作为跟车预警阈值,结合实际预警数据及不同制动时距分位数对应的预警正确率,对现有跟车预警规则进行调整,以适应不同类型驾驶人的驾驶需求。研究结果表明:3组驾驶人的平均跟车时距和平均制动时距差异显著,冒进型驾驶人倾向于选择较小的跟车时距和制动时距,保守型驾驶人的跟车时距和制动时距则普遍较大;3组驾驶人的实际跟车预警次数为215次,驾驶人采取制动操作而系统未予以预警的次数为329次,系统整体预警正确率为21.9%,漏警率为87.5%,通过分析信息熵等判定当前预警规则并不合理;将每类驾驶人制动时距的10%分位数作为阈值时的预警效果较好,调整后的跟车预警规则能在一定程度上适应不同的驾驶人类型。 相似文献
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In this paper, evolving Takagi-Sugeno (eTS) fuzzy driver model is proposed for simultaneous lateral and longitudinal control of a vehicle in a test track closed to traffic. The developed eTS fuzzy driver model can capture human operator’s driving expertise for generating desired steering angle, throttle angle and brake pedal command values by processing only information which can be supplied by the vehicle’s on-board control systems in real time. Apart from other fuzzy rule based (FRB) models requiring human expert knowledge or off-line clustering, the developed eTS driver model can adapt itself automatically, even ‘from scratch’, by an on-line learning process using eTS algorithm while human driver is supervising the vehicle. Proposed eTS fuzzy driver model’s on-line human driver identification capability and autonomous vehicle driving performance were evaluated on real road profiles created by digitizing two different intercity express ways of Turkey in IPG© CarMaker® software. The training and validation simulation results demonstrated that eTS fuzzy driver model can be used in product development phase to speed up different tests via realistic simulations. Furthermore eTS fuzzy driver model has an application potential in the field of autonomous driving. 相似文献
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Sang Hyeop Lee Suk Lee Man Ho Kim 《International Journal of Automotive Technology》2018,19(5):837-844
An advanced driver assistance system (ADAS) uses radar, visual information, and laser sensors to calculate variables representing driving conditions, such as time-to-collision (TTC) and time headway (THW), and to determine collision risk using empirically set thresholds. However, the empirically set threshold can generate differences in performance that are detected by the driver. It is appropriate to quickly relay collision risk to drivers whose response speed to dangerous situations is relatively slow and who drive defensively. However, for drivers whose response speed is relatively fast and who drive actively, it may be better not to provide a warning if they are aware of the collision risk in advance, because giving collision warnings too frequently can lower the reliability of the warnings and cause dissatisfaction in the driver, or promote disregard. To solve this problem, this study proposes a collision warning system (CWS) based on an individual driver’s driving behavior. In particular, a driver behavior model was created using an artificial neural network learning algorithm so that the collision risk could be determined according to the driving characteristics of the driver. Finally, the driver behavior model was learned using actual vehicle driving data and the applicability of the proposed CWS was verified through simulation. 相似文献