Human-Centered Design of an Acc-With-Braking and Forward-Crash-Warning System

This paper addresses the development of driver assistance systems whose functional purposes are to provide both adaptive cruise control (ACC) and forward collision warning (FCW). The purpose of the paper is to combine concepts from human factors psychology, vehicle-dynamics, and control theory, thereby contributing to the body of knowledge and understanding concerning human-centered approaches for designing and evaluating driver assistance systems. Conceptual and experimental results pertaining to driving manually and with the assistance of ACC and FCW are presented. The following human-centered aspects of driver-assistance systems are analyzed and presented: the looming effect; including rule-based and skill-based behavior in the design of ACC systems; using desired dynamics in controlling the driving process; braking rules that trade headway range for deceleration level; and collision-warning rules based on two different stress indicators. Field-test data are examined to justify and verify the parametric values selected for use in human-centered ACC systems. Measured data from on-road driving are used to evaluate the performance of proposed FCW systems in braking situations. The paper concludes with observations concerning the difficulty of developing a clear understanding of when and why drivers brake.     

Human-Centered Design of an Acc-With-Braking and Forward-Crash-Warning System

This paper addresses the development of driver assistance systems whose functional purposes are to provide both adaptive cruise control (ACC) and forward collision warning (FCW). The purpose of the paper is to combine concepts from human factors psychology, vehicle-dynamics, and control theory, thereby contributing to the body of knowledge and understanding concerning human-centered approaches for designing and evaluating driver assistance systems. Conceptual and experimental results pertaining to driving manually and with the assistance of ACC and FCW are presented. The following human-centered aspects of driver-assistance systems are analyzed and presented: the looming effect; including rule-based and skill-based behavior in the design of ACC systems; using desired dynamics in controlling the driving process; braking rules that trade headway range for deceleration level; and collision-warning rules based on two different stress indicators. Field-test data are examined to justify and verify the parametric values selected for use in human-centered ACC systems. Measured data from on-road driving are used to evaluate the performance of proposed FCW systems in braking situations. The paper concludes with observations concerning the difficulty of developing a clear understanding of when and why drivers brake.     

汽车ACC跟随控制策略研究

提出了ACC车辆与前车之间的速度一位移关系以及分别以车距控制和相对车速控制为目标的2种LQR模型，并根据两车的速度一位移关系的不同实现2种模型之间的转换，以生成符合驾驶员操作行为的ACC车辆控制目标，建立了实现控制目标的车速控制模型。仿真计算表明控制策略满足乘坐舒适性和保持安全车距的要求。     

基于预测恒定车头时距策略的自适应巡航控制研究

为了进一步提高车辆跟车过程中的跟踪性、安全性、舒适性和燃油经济性，针对已有间距策略表现过于保守或反应过于激烈等不足之处，提出了一种预测恒定车头时距策略。该策略考虑了相对加速度，建立了一种预测型期望车间距模型，进而应用于模型预测控制的多目标自适应巡航控制系统中，能进一步提高模型预测控制对多个控制目标的综合协调能力。搭建上层控制器、下层PID控制器、油门制动切换、逆纵向动力学模型。在多工况下仿真，通过建立性能评判指标对多目标进行量化分析。结果表明，所提出的间距策略在保证安全性的前提下，提升了自适应巡航控制系统的综合性能。在不同驾驶风格的车头时距下，跟踪性、舒适性和燃油经济性均有良好表现。     

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.     

自适应巡航及协同式巡航对交通流的影响分析

自适应巡航（ACC）和协同式自适应巡航（CACC）等自动驾驶技术正逐渐进入市场,未来一段时间内道路交通流将由人工驾驶车辆与不同等级、不同形式的自动驾驶车辆混合构成。为分析ACC和CACC对交通流的影响,利用实测交通数据NGSim建立人工驾驶车辆跟驰模型,并在综合已有ACC和CACC模型的基础上,提出基于安全间距的自动驾驶跟驰行为模型,进而得出不同ACC,CACC车辆渗透率下交通流的基本图模型。研究结果表明：自动驾驶可以提升交通容量;与ACC车辆比例r_a相比,CACC车辆比例r_c对交通容量的影响更为显著;当r_c>0.5时,饱和流量快速增加,当r_c=1时,饱和流量约为纯人工驾驶时的2倍。进一步,通过仿真考察车辆在车队中的跟驰响应和交通流在瓶颈处的运行情况。研究结果表明：自动驾驶改善了交通流的动态特性,对存在跟驰关系的连续车流来说,自动驾驶使得后车可以更加及时地响应前车的行为,车流会在更短的时间内进入稳态;在交通瓶颈处,自动驾驶降低了拥堵程度,提高了阻塞发生的临界流量。总体来看,自动驾驶对交通流静态和动态性能均有所提升,特别是在协同式自动驾驶场景下,车辆行为更加协调一致,交通流表现出良好的抗扰性,进一步验证了车路协同对自动驾驶的意义。     

Real-time weighted multi-objective model predictive controller for adaptive cruise control systems

In this paper, a novel spacing control law is developed for vehicles with adaptive cruise control (ACC) systems to perform spacing control mode. Rather than establishing a steady-state following distance behind a newly encountered vehicle to avoid collision, the proposed spacing control law based on model predictive control (MPC) further considers fuel economy and ride comfort. Firstly, a hierarchical control architecture is utilized in which a lower controller compensates for nonlinear longitudinal vehicle dynamics and enables to track the desired acceleration. The upper controller based on the proposed spacing control law is designed to compute the desired acceleration to maintain the control objectives. Moreover, the control objectives are then formulated into the model predictive control problem using acceleration and jerk limits as constrains. Furthermore, due to the complex driving conditions during in the transitional state, the traditional model predictive control algorithm with constant weight matrix cannot meet the requirement of improvement in the fuel economy and ride comfort. Therefore, a real-time weight tuning strategy is proposed to solve time-varying multi-objective control problems, where the weight of each objective can be adjusted with respect to different operating conditions. In addition, simulation results demonstrate that the ACC system with the proposed real-time weighted MPC (RW-MPC) can provide better performance than that using constant weight MPC (CW-MPC) in terms of fuel economy and ride comfort.     

认知分心对车辆跟驰过程操控安全性的影响

为了研究车辆跟驰过程中驾驶人认知分心与驾驶安全的关系,采用驾驶模拟器构建城市道路车辆跟驰场景,并设计3种难度等级的认知分心次任务,采集35名被试驾驶人在试验过程中的方向盘转角、油门开度、制动踏板力等操作参数,以及车辆位置、速度、加速度等车辆运动参数。采用重复测量一般线性模型,分析不同等级认知分心对上述参数的影响。研究结果表明：在横向操控方面,随着认知分心程度增高,方向盘回转率增大,但车辆横向位置标准差减小,表明驾驶人处于认知分心时,采取频繁修正方向盘的补偿方式,降低车辆横向位置波动,过度补偿车辆横向安全性,且该补偿行为与认知分心程度正相关;在纵向操控方面,认知分心时,油门开度、制动踏板位置方差增大,且制动踏板位置均值增大,同时车头间距及时距未观察到显著性变化,表明认知分心时驾驶人采取频繁操作油门、制动踏板,增大制动幅度等方式进行补偿,使车头间距及车头时距等表征车辆纵向跟车安全性参数处于正常驾驶水平,但加速度标准差增大,表明跟车稳定性降低。研究结果为涉及分心的人车交互装置优化设计及考虑分心状态的驾驶人状态管理系统开发提供了一定的理论依据。     

考虑驾驶员行为特性的模糊推理跟驰模型改进研究

基于模糊推理的车辆跟驰模型实现了用数学方法描述驾驶员的主观判断、推理和执行的过程,但现有的这类模型通常未考虑驾驶员行为特性的差异。针对这一问题,在基于模糊推理的跟驰模型中引入期望车头时距,不同行为特性的驾驶员具有不同的期望车头时距,在此基础上建立了改进的车辆跟驰模型。仿真结果表明,改进的跟驰模型能准确描述不同类型驾驶员的跟驰行为及其差异。     

A Comparision of Spacing and Headway Control Laws for Automatically Controlled Vehicles1

SUMMARY

This paper investigates two different longitudinal control policies for automatically controlled vehicles. One is based on maintaining a constant spacing between the vehicles while the other is based upon maintaining a constant headway (or time) between successive vehicles. To avoid collisions in the platoon, controllers have to be designed to ensure string stability, i.e the spacing errors should not get amplified as they propagate upstream from vehicle to vehicle. A measure of string stability is introduced and a systematic method of designing constant spacing controllers which guarantee string stability is presented. The constant headway policy does not require inter-vehicle communication to assure string stablity. Also, since inter-vehicle communication is not required it can be used in systems with mixed automated-nonautomated vehicles, e.g for AICC (Autonomous Intelligent Cruise Control). It is shown in this paper that for all the autonomous headway control laws, the desired control torques are inversely proportional to the headway time.     

基于自然驾驶数据的跨江大桥小客车跟驰特性研究

为明确跨江大桥的跟驰行为特征以及驾驶模式,在重庆菜园坝大桥展开了30位被试的小客车实车驾驶试验,使用华测航姿测量系统和前视碰撞预警系统Mobileye 630采集自然驾驶状态下汽车的连续行驶速度、车头时距和车头间距等数据。通过筛选得到了725条有效跟驰轨迹数据,对比分析发现跨江大桥与城市一般道路的跟驰行为存在一定差异性,明确了菜园坝大桥车头时距和车头间距的分布特征,并且对强跟驰(小于1.6 s)、过渡区间(1.6~2.6 s之间)以及弱跟驰(大于2.6 s)3种跟驰状态和驾驶人性别差异下的跟驰数据进行了分析。结果表明:桥梁段车头时距分布集中在1.6 s处,车头间距分布集中在18 m处;超过1/3的跟驰轨迹处于强跟驰状态,此状态下前车驾驶行为对跟驰车辆具有较强制约性;当车辆处于弱跟驰状态时,前车对于后车的约束性会随车头时距的增大而快速降低;过渡区间的设立更好地揭示了强/弱跟驰状态之间的转变并不是只有一个临界值,而是存在一个转换过程,并且其间车辆跟驰特性的变化与驾驶人本身的操作行为存在较大关联;驾驶人的性别差异对跟驰距离几乎没有影响,但男性驾驶人往往会采取更加冒险的驾驶行为,平均车头时距、车头间距以及相对速度均高于女性驾驶人。     

高速公路作业区汇入提示标志设置研究

考虑驾驶员在作业区上游过渡车道上行驶的过程中,车辆可汇入相邻车道的临界间隙的变化情况,减少作业区警告区末端由于汇入产生的冲突,提出设置汇入提示标志。利用M3分布模型与间隙接受理论,通过微分方法得到次车道上车辆的汇入概率模型。利用该概率模型,得到了在不同交通流状态下的汇入提示标志设置距离,同时对影响汇入概率的交通流参数进行了分析。计算结果表明：当自由流比例及车速均相同时,设置距离随交通流量增大而增大;而当车速与交通流量均相同时,设置距离随自由流比例增大而减小;当自由流比例与交通流量均相同时,设置距离随车速增大而增大。因此应结合作业区的限速值进行汇入提示标志的设置。     

Development of a path planning system using mean shift algorithm for driver assistance

The longitudinal and lateral vehicle control techniques have been widely used in several active driver assistance systems. The adaptive cruise control, lane keeping assistant control, vehicle platooning and stop-and-go control are typical examples of the most important applications. In this study, a novel path planning method is proposed considering the driving environment such as road shape, ego vehicle and surrounding vehicles’ movement. The relative distance and velocity between the ego vehicle and surrounding vehicles are identified with respect to the predicted lane shape in front of the ego vehicle. Based on the identified information, the road shape and surrounding vehicles are mapped into the intensity image and the desired vector for the ego vehicle’s movement is determined by the maximum intensity density tracing method. The desired vehicle path is followed by the acceleration/deceleration control and the steering assist control, respectively. In order to evaluate the performance of the proposed system, simulations are conducted and compared with ACC systems.     

Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

城市道路应急车辆路段行程时间计算模型

针对应急车辆的路段行程时间计算问题,选择了具有代表性的单向2车道道路,在假设应急车辆不更换车道的条件下,根据应急车辆行驶规则,构建了城市道路应急车辆的2车道路段行程时间计算模型.得出行程时间和路段长度,自由流车速,常规车辆的平均车速,更换车道时间,车流的车头时距的关系.验证结果显示,该模型具有一定的适用性.     

面向瓶颈多簇运动波消除的拥堵吸收智能驾驶模型

高速公路瓶颈运动波是诱发通行延误与事故风险主要原因.智能网联下精细化感知与精准化控制为消除运动波影响提供了技术环境.在构建一种在线、主动消除广域运动波的拥堵吸收智能驾驶模型的基础上,解析车头间距与运动波传播关联机制,确定运动波完全消除设计实施条件,提出消除单个运动波最佳驾驶策略;面向多簇运动波形成时间[位置[规模等特性...     

La surestimation de la distance intervéhiculaire dans le brouillard

The difficulties of driving in fog are usually perceived in terms of lower sight distances and reduced ability to anticipate. However, the fall in the quality of visual information can also lead to errors in judgement by affecting the way drivers perceive their environment and their movement within it. We have conducted a series of experiments in a fog chamber and on a driving simulator, with the main aim of investigating the influence of fog on vehicle headway perception. Our results have revealed that distances are seriously overestimated in fog, and that this is likely to contribute to lower headways under such conditions, In fog an overestimation of headway between 20 and 55% was observed when vehicles were visible only as a result of their rear lights, which is the case in night-time or thick daytime fog. Under these conditions, the characteristics of vehicle lights become extremely important. Overestimation of distance becomes greater when vehicles have only one rear light instead of two, and when their two reac lights are close together. Perception of vehicle distance is therefore improved by two rear lights, placed as far apart as possible to indicate the dimensions of the vehicle. No significant overestimation of headways was found during thin or moderate daytime fog, when the vehicle outline remained visible. The results have shown the importance of the familiar size of vehicles as an indicator of distance in the situations we have investigated. They confirm the hypothesis that basic mechanisms of space perception are modified in fog.     

基于不同风格行驶模型的自动驾驶仿真测试自演绎场景研究

为了验证自动驾驶汽车决策结果的安全性,提出一种具有自主决策和交互能力的行驶模型生成方法,该行驶模型作为背景车被用于构建自演绎仿真场景来测试自动驾驶汽车的连续决策能力。首先,以强化学习为基础、结合遗传与进化思想,创新地设计并生成了具有自主决策和交互能力的不同风格行驶模型;然后,在模型构建阶段分别训练生成了保守、普通和激进3种风格的行驶模型,其中普通风格行驶模型的训练参数来源于自然驾驶数据集highD的车辆参数分布,保证了该行驶模型的真实性;最后,在普通风格行驶模型的基础上设计并训练出了具有显著激进特征的激进风格行驶模型,以增强自演绎场景的复杂性和测试效果。结果表明：在模型真实性方面,以highD数据集中的跟车速度、车头间距、换道时刻下碰撞时间等参数的分布为真值,研究所生成的普通风格行驶模型的参数分布与真值的平均相似程度为88%,相较于基于规则的智能驾驶人模型（IDM）提升了20.3%;在场景测试性方面,以被测系统为主要责任方的碰撞次数为评估指标,研究生成的不同风格行驶模型所构成的自演绎场景的测试性约是由IDM构成的基线场景的7倍。因此,设计和生成的行驶模型所构成的自演绎场景可以有效支撑面向自动驾驶决策系统的仿真测试。     

基于拉格朗日松弛算法的自动驾驶公交调度优化研究

为了解决公交实际运营出现的调度方式单一、车辆配合度较差、串车等问题，降低公交运行中人为因素的影响，提高公交系统的运营效率，提出一种考虑乘客动态需求的调度模型，采用自动驾驶环境下的公交运营方式，结合站点实际乘客需求调配车辆，实现了公交车辆利用程度最大和乘客总体等待时间最小的多目标优化。提出的自动驾驶公交调度方法，获取了乘客个体的实时出行需求，同时实现了对车头时距的调控。在模型求解方面，选取拉格朗日松弛算法，最终获得了多目标优化问题的精确解。以北京公交300路快车作为实际案例进行分析，从公交实际运营数据中提取多项参数作为模型的输入，通过拉格朗日松弛算法的求解，得到自动驾驶条件下公交运行时刻表、乘客等待时间、公交承载量、站点上车乘客人数等多项运营指标。通过与公交实际运营状态的对比，论证了采用自动驾驶公交对于改善公交运营现状的可行性。最后将优化结果与公交实际数据进行了对比分析。结果表明：自动驾驶车辆投入公交运营，能够缓解串车问题，同一线路上公交车的载客量分布更为均衡，在同一断面的客流与车头时距的不均衡程度均有所降低；同时高峰时段发车数量减少了20%，公交车的平均承载量提高了21.7%，车辆平均间隔缩短了29.9%。