现代汽车防撞系统

进入90年代以来,世界各国投入大量人力和物力从事汽车防撞系统的研究与试验。现已取得了明显的效果,并开发了若干新产品,为保障汽车行驶安全、降低肇事率作出了贡献。汽车防撞系统是一种可向司机预先发出视听警告信号的探测装置。它安装在汽车上,能探测企图接近车身的行人、车辆或周围障碍物;能向司机及乘员提前发出即将发生撞车危险的信号,促使司     

现代汽车防撞系统

从上个世纪90年代以来,世界各国投入大量人力、物力从事汽车防撞系统的研究,目前已取得了显著的成果,开发了若干新产品,使汽车的行驶安全性大大提高。     

汽车防撞系统与毫米波雷达

本文介绍了汽车防撞系统的构成,以及汽车防撞系统中的关键技术一汽车雷达的种类与特点。其中,重点介绍了毫米波汽车雷达的原理、特点、和现在发展的状况。     

激光测距在汽车防撞系统中的应用

本文通过对激光相位测距仪原理的分析,提出利用该仪器与报警器相结合,可避免汽车在气候恶劣的条件下发生追尾相撞事故。     

汽车防追尾碰撞数学模型研究

为了提高车辆在高速行驶状态下的主动安全性能,研究了处于追尾行驶状态的本车与前车的运动学特征;针对前车的不同运动状态分别推导出了跟车距离的计算模型并分析了模型中3个关键参数的随机性和动态性,对制动迟滞时间提出了基于模糊推理的确定方法,对本车制动减速度和前车的运动加速度提出了比较实用的动态测算公式;另外,研究了防追尾碰撞的控制与执行,建立了动态调整安全制动停车距离的神经网络模型,提出了基于危险裕度判别的安全控制方法。     

Emergency steering control of autonomous vehicle for collision avoidance and stabilisation

ABSTRACT

Collision avoidance and stabilisation are two of the most crucial concerns when an autonomous vehicle finds itself in emergency situations, which usually occur in a short time horizon and require large actuator inputs, together with highly nonlinear tyre cornering response. In order to avoid collision while stabilising autonomous vehicle under dynamic driving situations at handling limits, this paper proposes a novel emergency steering control strategy based on hierarchical control architecture consisting of decision-making layer and motion control layer. In decision-making layer, a dynamic threat assessment model continuously evaluates the risk associated with collision and destabilisation, and a path planner based on kinematics and dynamics of vehicle system determines a collision-free path when it suddenly encounters emergency scenarios. In motion control layer, a lateral motion controller considering nonlinearity of tyre cornering response and unknown external disturbance is designed using tyre lateral force estimation-based backstepping sliding-mode control to track a collision-free path, and to ensure the robustness and stability of the closed-loop system. Both simulation and experiment results show that the proposed control scheme can effectively perform an emergency collision avoidance manoeuvre while maintaining the stability of autonomous vehicle in different running conditions.     

Comparing and validating models of driver steering behaviour in collision avoidance and vehicle stabilisation

A number of driver models were fitted to a large data set of human truck driving, from a simulated near-crash, low-friction scenario, yielding two main insights: steering to avoid a collision was best described as an open-loop manoeuvre of predetermined duration, but with situation-adapted amplitude, and subsequent vehicle stabilisation could to a large extent be accounted for by a simple yaw rate nulling control law. These two phenomena, which could be hypothesised to generalise to passenger car driving, were found to determine the ability of four driver models adopted from the literature to fit the human data. Based on the obtained results, it is argued that the concept of internal vehicle models may be less valuable when modelling driver behaviour in non-routine situations such as near-crashes, where behaviour may be better described as direct responses to salient perceptual cues. Some methodological issues in comparing and validating driver models are also discussed.     

Unified decision-making and control for highway collision avoidance using active front steer and individual wheel torque control

ABSTRACT

Collision avoidance is a crucial function for all ground vehicles, and using integrated chassis systems to support the driver presents a growing opportunity in active safety. With actuators such as in-wheel electric motors, active front steer and individual wheel brake control, there is an opportunity to develop integrated chassis systems that fully support the driver in safety critical situations. Here we consider the scenario of an impending frontal collision with a stationary or slower moving vehicle in the same driving lane. Traditionally, researchers have approached the required collision avoidance manoeuver as a hierarchical scheme, which separates the decision-making, path planning and path tracking. In this context, a key decision is whether to perform straight-line braking, or steer to change lanes, or indeed perform combined braking and steering. This paper approaches the collision avoidance directly from the perspective of constrained dynamic optimisation, using a single optimisation procedure to cover these aspects within a single online optimisation scheme of model predictive control (MPC). While the new approach is demonstrated in the context of a fully autonomous safety system, it is expected that the same approach can incorporate driver inputs as additional constraints, yielding a flexible and coherent driver assistance system.     

Risk management algorithm for rear-side collision avoidance using a combined steering torque overlay and differential braking

This paper describes a risk management algorithm for rear-side collision avoidance. The proposed risk management algorithm consists of a supervisor and a coordinator. The supervisor is designed to monitor collision risks between the subject vehicle and approaching vehicle in the adjacent lane. An appropriate criterion of intervention, which satisfies high acceptance to drivers through the consideration of a realistic traffic, has been determined based on the analysis of the kinematics of the vehicles in longitudinal and lateral directions. In order to assist the driver actively and increase driver's safety, a coordinator is designed to combine lateral control using a steering torque overlay by motor-driven power steering and differential braking by vehicle stability control. In order to prevent the collision while limiting actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort, the Lyapunov theory and linear matrix inequalities based optimisation methods have been used. The proposed risk management algorithm has been evaluated via simulation using CarSim and MATLAB/Simulink.     

Model predictive control with constraints for a nonlinear adaptive cruise control vehicle model in transition manoeuvres

A vehicle following control law, based on the model predictive control method, to perform transition manoeuvres (TMs) for a nonlinear adaptive cruise control (ACC) vehicle is presented in this paper. The TM controller ultimately establishes a steady-state following distance behind a preceding vehicle to avoid collision, keeping account of acceleration limits, safe distance, and state constraints. The vehicle dynamics model is for continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. The ACC vehicle can execute the TM successfully and achieves a steady-state in the presence of complex dynamics within the constraint boundaries.     

混合动力汽车动力总成试验台研究

基于混合动力汽车有串联、并联和混联等多种结构形式的特点,提出以模块化设计思想来搭建混合动力汽车动力总成试验台的方法,从而达到了在比较短的时间内、以尽量小的改动适应不同混合动力汽车动力总成结构形式组合需要的目标。根据研究需要,首先完成了混合动力汽车动力总成试验台并联形式的建设,并利用该试验台对所研制的混合动力城市客车多能源动力总成控制器进行了初步调试,验证了该控制器的软硬件设计和并联电动助力型控制策略。同时,所完成的发动机台架试验和电机台架试验也充分证明了试验台模块化设计思想的可行性和有效性。     

智能车辆主动避撞与稳定性联合控制仿真

为改善车辆在主动避撞过程中的车辆动力学特性,在MATLAB/Simulink环境下结合驾驶员模型分别设计了基于模糊控制理论的主动避撞控制处理器、制动稳定性控制器和转向稳定性控制器,从而能够在车辆主动避撞过程中综合考虑避撞和稳定性两个目标.并在ADAMS中建立了整车模型,联合MATLAB进行了仿真研究,仿真结果证明,在相...     

汽车燃油空气加热器燃烧排放控制研究

针对燃油空气加热器开机、关机排放污染严重的问题,提出通过改进点火系统和供油系统来降低排放。通过对比发现:采用全陶瓷点火后,开机过程的CO、HC浓度基本不变,但烟度不透光系数(OPAC)峰值降低,排烟持续时间缩短;改进供油系统后,关机过程的HC排量降到原来的30%,CO排量降到原来的3%,烟度OPAC值降为原来的28%,各排放持续时间均缩短。试验结果表明:采用全陶瓷点火和改进供油系统有效地降低了加热器的开机、关机排放污染。     

基于双延迟深度确定性策略梯度的船舶自主避碰方法

为满足智能船舶自主航行的发展需求,解决基于强化学习的船舶避碰决策方法存在的学习效率低、泛化能力弱以及复杂会遇场景下鲁棒性差等问题,针对船舶避碰决策信息的高维性和动作的连续性等特点,考虑决策的合理性和实时性,研究了基于双延迟深度确定性策略梯度（TD3）的船舶自主避碰方法。根据船舶间相对运动信息与碰撞危险信息,从全局角度构建具有连续多时刻目标船信息的状态空间;依据船舶操纵性设计连续决策动作空间;综合考虑目标导向、航向保持、碰撞危险、《1972年国际海上避碰规则》（COLREGs）和良好船艺等因素,设计船舶运动的奖励函数;基于TD3算法,根据状态空间结构,结合长短期记忆（LSTM）网络和一维卷积网络,利用Actor-Critic结构设计船舶自主避碰网络模型,利用双价值网络学习、目标策略平滑以及策略网络延迟更新等方式稳定网络训练,利用跳帧以及批量大小和迭代更新次数动态增大等方式加速网络训练;为解决模型泛化能力弱的问题,提出基于TD3的船舶随机会遇场景训练流程,实现自主避碰模型应用的多场景迁移。运用训练得到的船舶自主避碰模型进行仿真验证,并与改进人工势场（APF）算法进行比较,结果表明：所提方法学习效率高,收敛快速平稳;训练得到的自主避碰模型在2船和多船会遇场景下均能使船舶在安全距离上驶过,并且在复杂会遇场景中比改进APF算法避碰成功率高,避让2~4艘目标船时成功率高达99.233%,5~7艘目标船时成功率97.600%,8~10艘目标船时成功率94.166%;所提方法能有效应对来船的不协调行动,避碰实时性高,决策安全合理,航向变化快速平稳、震荡少、避碰路径光滑,比改进APF方法性能更强。