汽车ACC毫米波雷达和视觉传感器目标级融合方法研究

自适应巡航控制系统是实现未来智能化汽车辅助驾驶的重要功能之一,以往该系统主要采用毫米波雷达感知周围环境,但是容易出现较多的误识别和漏识别情况。针对现存的问题,文章研究了自适应巡航感知系统,不同于以往单一雷达的方案,本设计采用毫米波雷达和视觉传感器融合的办法改善感知系统的性能。通过搭建电动车传感器数据采集系统,编写CAN通信报文解析程序,分析毫米波雷达和视觉传感器特性等,完成了对雷达和视觉信号的采集及处理,实现了感知系统目标级融合。并在巡航和跟车工况下进行离线仿真,验证了目标级融合方案能够有效地提高感知系统的准确性和合理性。     

A new shared control for lane keeping and road departure prevention

In recent years, the driver's active assistances have become important features in commercialised vehicles. In this paper, we present one of these features which consists of an advanced driver assistance system for lane keeping. A thorough analysis of its performance and stability with respect to variations in driver behaviour will be given. Firstly, the lateral control model based on visual preview is established and the kinematics model based on visual preview, including speed and other factors, is used to calculate the lateral error and direction error. Secondly, and according to the characteristics of the lateral control, an efficient strategy of intelligent electric vehicle lateral mode is proposed. The integration of the vehicle current lateral error and direction error is chosen as the parameter of the sliding mode switching function to design the sliding surface. The control variables are adjusted according to the fuzzy control rules to ensure that they meet the existence and reaching condition. A new fuzzy logic-based switching strategy with an efficient control law is also proposed to ensure a level of continuous and variable sharing according to the state of the driver and the vehicle positioning on the roadway. The proposed control law acts either at the centre of the lane, as a lane keeping assistance system to reduce the driver's workload for long trips, or as a lane departure avoidance system that intervenes for unintended lane departures. Simulation results are included in this paper to explain this concept.     

走-停巡航系统分层控制器设计

结合驾驶统计模型，设计了走一停自适应巡航系统的纵向车间距离控制器。上位控制器的设计与车辆模型无关。在建立目标性能函数的基础上得到控制律；而下位控制器则将油门和制动控制独立设计，依据一定的切换逻辑使它们分别作用于车辆。在制动控制的设计中引入了改进型史密斯预估器。在多种工况下的仿真试验中表明控制器性能良好。     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.     

Fault detection of vehicle suspension system using wavelet analysis

This paper presents a method based on continuous wavelet transform to detect the faults of vehicle suspension systems. The Morlet wavelet functions are employed to approach the natural frequencies of the system and the frequency components of the signal with relative maximum energy. To evaluate our method, we use a full vehicle dynamic model which has been simulated in ADAMS/CAR and validated by laboratory test results. The suspension faults have been considered due to the damage of shock absorbers (dampers) and upper damper bushings (UDBs) and assumed as the decrease in damping force and loose joints, respectively. In this paper, the incapability of the spectral analysis by using fast Fourier transform in analysis of the signals is revealed through applying the inputs that include transient characteristics and then wavelet transform employed to achieve more proper results. A swept frequency is applied as an input to the wheels that simulates the road irregularities. After detection of faulty sections of the system using signal energy distribution, the defects of damper and UDBs are distinguished from each other through observing the changes of natural frequencies and corresponding energy amplitudes.     

Road curvature estimation for vehicle lane departure detection using a robust Takagi–Sugeno fuzzy observer

In this paper, a lane departure detection method is studied and evaluated via a professional vehicle dynamics software. Based on a robust fuzzy observer designed with unmeasurable premise variables with unknown inputs, the road curvature is estimated and compared with the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed algorithm as the first driving risk indicator. To reduce false alarms and take into account the driver corrections, a second driving risk indicator is considered, which is based on the steering dynamics, and it gives the time to the lane keeping. The used nonlinear model deduced from the vehicle lateral dynamics and a vision system is represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is then proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using Lyapunov method. The proposed approach is evaluated under different driving scenarios using a software simulator. Simulation results show good efficiency of the proposed method.     

Integrated fault detection and diagnosis system for longitudinal control of an autonomous all-terrain vehicle (ATV)

This paper presents a fault detection and diagnosis (FDD) method to enhance the reliability and safety for longitudinal control of an autonomous all-terrain vehicle (ATV). An integrated approach using decentralized and centralized FDD is proposed to optimize the tradeoff between sensitivity and robustness. While the decentralized approach is suitable for detecting faults in actuators and sensors directly connected to a single processor, it is sensitive to noises and disturbances and thus may result in false alarms. On the other hand, the centralized approach is based on information communicated between multiple processors, and it detects and diagnoses faults through analyzing concurrent computations of multiple hardware modules. However, its performance is still limited to isolating faults specifically in terms of components in the single hardware. To incorporate the advantages of both FDD approaches, a two-layered structure integrating both decentralized and centralized FDD is proposed and allows us to perform more robust fault detection as well as more detailed fault isolation. Finally, the proposed method is validated experimentally via field tests of an ATV.     

An improvement in rollover detection of articulated vehicles using the grey system theory

A Rollover Index combined with the grey system theory, called a Grey Rollover Index (GRI), is proposed to assess the rollover threat for articulated vehicles with a tractor–semitrailer combination. This index can predict future trends of vehicle dynamics based on current vehicle motion; thus, it is suitable for vehicle-rollover detection. Two difficulties are encountered when applying the GRI for rollover detection. The first difficulty is effectively predicting the rollover threat of the vehicles, and the second difficulty is achieving a definite definition of the real rollover timing of a vehicle. The following methods are used to resolve these problems. First, a nonlinear mathematical model is constructed to accurately describe the vehicle dynamics of articulated vehicles. This model is combined with the GRI to predict rollover propensity. Finally, TruckSim^? software is used to determine the real rollover timing and facilitate the accurate supply of information to the rollover detection system through the GRI. This index is used to verify the simulation based on the common manoeuvres that cause rollover accidents to reduce the occurrence of false signals and effectively increase the efficiency of the rollover detection system.     

Vehicle dynamics and road curvature estimation for lane departure warning system using robust fuzzy observers: experimental validation

This paper describes a new approach to estimate vehicle dynamics and the road curvature in order to detect vehicle lane departures. This method has been evaluated through an experimental set-up using a real test vehicle equipped with the RT2500 inertial measurement unit. Based on a robust unknown input fuzzy observer, the road curvature is estimated and compared to the vehicle trajectory curvature. The difference between the two curvatures is used by the proposed lane departure detection algorithm as the first driving risk indicator. To reduce false alarms and take into account driver corrections, a second driving risk indicator based on the steering dynamics is considered. The vehicle nonlinear model is deduced from the vehicle lateral dynamics and road geometry and then represented by an uncertain Takagi–Sugeno fuzzy model. Taking into account the unmeasured variables, an unknown input fuzzy observer is proposed. Synthesis conditions of the proposed fuzzy observer are formulated in terms of linear matrix inequalities using the Lyapunov method.     

1+X证书制度对教师角色转变的新要求

1+X证书制度是由国务院牵头,联合多部委与地方政府贯彻"职教20条"提出的新制度。其主要核心内容为1个学历证书与若干个技能证书相融合,通过模块教学达到课证融通的效果。在1+X证书制度的实施过程中,不仅有企业行业参与,更多的是老师与学生的融入。由于企业行业提出了不同的新标准,指定了不同的实施方案,这就要求老师从传统的教学模式转变为课证融通的教学模式,实现模块化教学。因此,从整个1+X证书制度的顶层设计到最后的实施落地,教师都需参与其中,实现角色转变。重新修订学校的人才培养方案,课程标准的制定,教学环节的实施。     

Fault detection and isolation for a nonlinear railway vehicle suspension with a Hybrid Extended Kalman filter

Fault detection is considered to be one way to improve system reliability and dependability for railway vehicles. The secondary lateral and anti-yaw dampers are the most critical parts in railway suspension systems. So far, the dampers have been modelled as linear components in the fault detection and isolation observer design. In this work, a Hybrid Extended Kalman filter is used to capture the nonlinear characteristics of the dampers. In order to detect and isolate faults, a nonlinear residual generator is developed, which can distinguish clearly between different types of faults. A lateral half train model serves as an example for the proposed technique. The results show that failures in the nonlinear suspension system can be detected and isolated accurately.     

Fuzzy and adaptive fuzzy control for the automobiles' active suspension system

Two typical criteria for good vehicle suspension performance are their ability to provide good road handling and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. This paper describes fuzzy and adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road holding and riding comfort over a wide range of road profiles. The efficacy of the proposed control schemes is demonstrated via simulations. With respect to the optimal linear quadratic regulator (LQR), it is shown that superior results have been achieved by the AFC.     

Fuzzy and adaptive fuzzy control for the automobiles’ active suspension system

Two typical criteria for good vehicle suspension performance are their ability to provide good road handling and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. This paper describes fuzzy and adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road holding and riding comfort over a wide range of road profiles. The efficacy of the proposed control schemes is demonstrated via simulations. With respect to the optimal linear quadratic regulator (LQR), it is shown that superior results have been achieved by the AFC.