Lane-keeping assistance control algorithm using differential braking to prevent unintended lane departures

This paper describes a hierarchical lane keeping assistance control algorithm for a vehicle. The proposed control strategy consists of a supervisor, an upper-level controller and a lower-level controller. The supervisor determines whether lane departure is intended or not, and whether the proposed algorithm is activated or not. To detect driver′s lane change intention, the steering behavior index has been developed incorporating vehicle speed and road curvature. To validate the detection performance on the lane change intention, full-scale simulator tests on a virtual test track (VTT) are conducted under various driving situations. The upper-level controller is designed to compute the desired yaw rate for the lane departure prevention, and for the guidance with ride comfort. The lower-level controller is designed to compute the desired yaw moment in order to track the desired yaw rate, and to distribute it into each tire′s braking force in order to track the desired yaw moment. The control allocation method is adopted to distribute braking forces under the actuator’s control input limitation. The proposed lane keeping assistance control algorithm is evaluated with human driver model-in-the-loop simulation and experiments on a real vehicle.     

Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration During Automated Driving

Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization. The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation, the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner. The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions.      

Adaptive rollover prevention controller for driver–vehicle systems

In the paper, we propose an adaptive rollover prevention controller for heavy vehicles. At first, a design method for an ideal vehicle model is proposed. The designed ideal vehicle model has the property that good rollover prevention performance can be assured even if the driver steering characteristics vary. If the behavior of the actual heavy vehicle tracks that of the designed ideal vehicle model, rollover prevention can be achieved. Therefore, next, to realize good rollover prevention, we propose an adaptive steering controller. In the heavy vehicle system using the controller, the actual heavy vehicle can track the ideal vehicle model. Then, rollover prevention can be achieved. Finally, to demonstrate the usefulness of the proposed controller, numerical simulations are carried out.     

驾驶员在环的SUV防侧翻控制器实时仿真设计

运用驾驶员在回路实时仿真系统设计SUV汽车防侧翻差动制动控制器并验证其有效性和可靠性。根据驾驶员的逻辑判断,得到理想的汽车行驶状态,当汽车行驶偏离理想值时,用控制系统来纠正SUV的横摆力矩。仿真实验在加拿大安省理工大学的汽车模拟器上进行,通过Fishhook和双移线工况对设计的控制器性能进行研究分析,对比控制前后对汽车侧向稳定性能的改善效果。仿真结果表明,所设计的控制器能有效提高汽车侧向稳定性和可操纵性。     

SUV侧翻预警系统硬件在环实时仿真设计

针对运动型多功能汽车（SUV）设计一种基于动态侧翻预警的控制系统。以横向载荷转移率作为侧翻指标,研究TTR侧翻预警算法及硬件实现,并应用差动制动方法对车辆进行侧倾控制。在汽车模拟器上进行硬件在环实时仿真实验,选取双移线和Fishhook工况对SUV动态侧翻预警控制性能进行分析。仿真结果显示,基于预警的防侧翻控制系统不仅可以有效地提高车辆的横摆稳定性和侧倾稳定性,且只有在出现侧翻危险时才起动制动装置,节省了制动能量。     

An investigation into vehicle rollover prevention by coordinated control of active anti-roll bar and electronic stability program

This paper presents a method for designing a controller that uses an active anti-roll bar (AARB) and an electronic stability program (ESP) for rollover prevention. ESP with longitudinal speed control (LSC) can carry out active braking to reduce vehicle speed and lateral acceleration to prevent a rollover. To enhance the rollover prevention capability of the ESP, an AARB is adopted. The controller for the AARB was designed based on linear quadratic (LQ) static output feedback (SOF) control methodology, which attenuates the effect of lateral acceleration on the roll angle and roll rate by control of the suspension stroke and the tire deflection of the vehicle. Although this AARB significantly increases ride comfort and rollover prevention, it has a drawback — the vehicle loses its maneuverability. Therefore, the ESP with LSC is used to overcome this drawback. Simulations showed that the proposed method was effective in preventing a rollover.     

Collaborater for a Car‐Like Vehicle Driven by a User with Visual Inattention

This paper proposes a control system applied to a car‐like vehicle driven by a user. The controller is designed to mitigate the negative effects produced by possible visual distractions of this user. In addition, the paper proposes to evaluate the user's visual distraction, defining a vector that has two components: one with respect to the path and the other with respect to the obstacles. These elements can be computed on‐line and are associated with two time delays that produce a similar effect of instability on the motion of the vehicle. The proposed scheme considers the distraction in the design through such delays. Finally, experiments using a car simulator are carried out     

Theoretical and Experimental Investigation of Driver Noncooperative-Game Steering Control Behavior

This paper investigates two noncooperative-game strategies which may be used to represent a human driver's steering control behavior in response to vehicle automated steering intervention.The first strategy,namely the Nash strategy is derived based on the assumption that a Nash equilibrium is reached in a noncooperative game of vehicle path-following control involving a driver and a vehicle automated steering controller.The second one,namely the Stackelberg strategy is derived based on the assumption that a Stackelberg equilibrium is reached in a similar context.A simulation study is performed to study the differences between the two proposed noncooperativegame strategies.An experiment using a fixed-base driving simulator is carried out to measure six test drivers'steering behavior in response to vehicle automated steering intervention.The Nash strategy is then fitted to measured driver steering wheel angles following a model identification procedure.Control weight parameters involved in the Nash strategy are identified.It is found that the proposed Nash strategy with the identified control weights is capable of representing the trend of measured driver steering behavior and vehicle lateral responses.It is also found that the proposed Nash strategy is superior to the classic driver steering control strategy which has widely been used for modeling driver steering control over the past.A discussion on improving automated steering control using the gained knowledge of driver noncooperative-game steering control behavior was made.     

Mixture of Automatically- and Manually-controlled Vehicles in Intelligent Transport Systems

This paper presents a technology which allows for the existence of mixed traffic, as a first step towards intelligent transport systems. We begin by designing an automatic driving controller called the intelligent vehicle driving system (IVDS). This is a two-layer system: the higher layer analyzes the current scenario and infers the control objective that associates with a certain index function; the lower layer optimizes the function provided by the upper layer. IVDS only uses the measurement of a vehicle's speed and distance relative to the vehicle in front, together with measurements of the vehicle's own state. Consequently, the vehicles equipped with the IVDS can operate together with manually-controlled vehicles. Next, a mathematical rule-based model for human drivers is developed. This model attempts to mimic human driver's behavior in vehicle following and lane-changing. Finally, we examine the control performance of the proposed controller and the potential benefits of mixed traffic by implementing the human driver model and IVDS on an automated highway simulator.     

基于车流信息的智能巡航控制器的设计分析

设计一个模拟人类驾驶行为的智能巡航控制器。在分析现有巡航控制的基础上,提出利用车流前后车辆的相对速度和间距信息的智能巡航控制算法来选择正确的控制行为,从而平顺跟车行为,使车辆能保持由驾驶员指定的理想跟车距离。仿真结果显示,在此智能巡航控制下能保证车辆和车队在前、后两个方向上的稳定性。     

A study on the factors that improve the velocity perception of a virtual reality‐based vehicle simulator

The Virtual Reality (VR) system of a real‐time VR‐linked vehicle simulator that was used in this study provides visual information and sound effects to participants. The VR system of a VR‐linked vehicle simulator should provide a perceived velocity similar with the perceived velocity in actual driving. To achieve these goals, modeling and rendering methods that offer an improved performance for complex VR applications, such as the 3D road model, were implemented and evaluated. We also evaluated the influences of graphic and engine sound effects on the driver and analyzed each result according to a driver's viewpoint, the dot densities of road texture provided, the lateral distance between a virtual driver and environmental objects, and the engine sound. Each factor was individually analyzed through an experiment that evaluated the influence of visual images or sound effects in the vehicle simulator. Through the experimental evaluation, the research results could be used for improving the effectiveness of VR‐based vehicle simulators.     

The validity of driving simulation for assessing differences between in-vehicle informational interfaces: A comparison with field testing

Data from on-road and simulation studies were compared to assess the validity of measures generated in the simulator. In the on-road study, driver interaction with three manual address entry methods (keypad, touch screen and rotational controller) was assessed in an instrumented vehicle to evaluate relative usability and safety implications. A separate group of participants drove a similar protocol in a medium fidelity, fixed-base driving simulator to assess the extent to which simulator measures mirrored those obtained in the field. Visual attention and task measures mapped very closely between the two environments. In general, however, driving performance measures did not differentiate among devices at the level of demand employed in this study. The findings obtained for visual attention and task engagement suggest that medium fidelity simulation provides a safe and effective means to evaluate the effects of in-vehicle information systems (IVIS) designs on these categories of driver behaviour.

Statement of Relevance: Realistic evaluation of the user interface of IVIS has significant implications for both user acceptance and safety. This study addresses the validity of driving simulation for accurately modelling differences between interface methodologies by comparing results from the field with those from a medium fidelity, fixed-base simulator.     

Automation-driver cooperative driving in presence of undetected obstacles

The work presented in this paper describes and discusses the principles of a haptic shared control between a human driver and an Electronic copilot (E-copilot) for a vehicle. The aim of the sharing control is to allow the driver to momentarily take control over the E-copilot without deactivating it nor being constrained, in order to deal with a specific situation such as avoiding an obstacle that has not been detected by the E-copilot. As the E-copilot acts simultaneously on the steering system with the driver, both have to be aware of one another's actions, which means bi-directional communication is essential. In this work, to achieve this goal, we consider the haptical interactions through the steering wheel. The torque applied by the driver on the steering system is used by the E-copilot to take into account the driver's actions while the E-copilot assistance torque is felt by the driver and used by him to understand the system's behavior. This low communication level strongly improves the cooperation between the driver and the E-copilot.The system takes into account the drivers actions thanks to a driver lane keeping model that is added to the road vehicle one in the controller synthesis step. This allows to introduce driver's interaction control variables in such a way that the E-copilot can consider conflicting objectives between the driver and the lane keeping task, and thus handle them.In order to highlight the assets of the approach, a comparison of the behaviors of a simple lane keeping E-copilot to that of a cooperative proposed here is given at the end of this paper. This comparison is achieved through computer simulations and experimental tests with a human driver carried out in the SHERPA-LAMIH interactive dynamic driving simulator. The results of these tests confirm the improvement of the level of cooperation between the human driver and the E-copilot and show that the cooperative E-copilot gives more authority to the human driver especially in hazardous situations.     

Optical information for car following: the driving by visual angle (DVA) model

OBJECTIVE: The present study developed and tested a model of car following by human drivers. BACKGROUND: Previous models of car following are based on 3-D parameters such as lead vehicle speed and distance information, which are not directly available to a driver. In the present paper we present the driving by visual angle (DVA) model, which is based on the visual information (visual angle and rate of change of visual angle) available to the driver. METHOD: Two experiments in a driving simulator examined car-following performance in response to speed variations of a lead vehicle defined by a sum of sine wave oscillations and ramp acceleration functions. In addition, the model was applied to six driving events using real world-driving data. RESULTS: The model provided a good fit to car-following performance in the driving simulation studies as well as in real-world driving performance. A comparison with the advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN) model, which is based on 3-D parameters, suggests that the DVA was more predictive of driver behavior in matching lead vehicle speed and distance headway. CONCLUSION: Car-following behavior can be modeled using only visual information to the driver and can produce performance more predictive of driver performance than models based on 3-D (speed or distance) information. APPLICATION: The DVA model has applications to several traffic safety issues, including automated driving systems and traffic flow models.     

Using Queuing Network and Logistic Regression to Model Driving with a Visual Distraction Task

Computational dual-task models of driving with a secondary task can help compute, simulate, and predict driving behavior in dual task situations. These models can thus help improve the process of developing in-vehicle devices by reducing or eliminating the need for conducting driver experiments in the early stage of the development. Further, these models can help improve traffic flow simulation. This article develops a dual-task model of driving with a visual distraction task using the Queuing Network model of driver lateral control and a logistic regression model. The comparison between the model simulation data and the human data from drivers in a driving simulator shows that this computational model can perform driving with a secondary visual task well and its performance is consistent with the driver data.     

Shared control for lane departure prevention based on the safe envelope of steering wheel angle

The ability to prevent lane departure has become an important feature for commercialized vehicles. This paper proposes a shared steering assistance strategy based on a safe envelope of steering wheel angle (SWA). This solves the human-machine conflict issue in lane departure prevention (LDP) system which uses steering control to help the driver keep the vehicle within the correct lane. The system combines a driver steering control model, current vehicle states and vehicle-road deviation. The desired SWAs are calculated when the driver intends to drive along the left or right side of the lane, and then the two angles are used to generate the safe envelope. Next, a driver intention estimator is designed to predict driver’s intended SWA and the assistance control is activated by judging whether the driver intended SWA is go beyond the safe envelope. Finally, a H∞ controller and a disturbance observer are developed to determine the assistance torque. In this way, the SWA is limited to safe values to mitigate lane departure and the controller intervention is minimized. The effectiveness of the proposed method is evaluated via numerical simulation with different driving scenarios and human-in-the-loop experiment on a driving simulator. The obtained results show that this method not only can avoid lane departures effectively, but also ensures a good human-machine cooperative performance.     

智能车载感知与侧翻预警系统的设计

为了防止汽车在行驶过程中发生侧翻,使汽车始终处在安全工况下行驶,减少交通事故,设计了一种基于ARM9的智能车载感知和侧翻预警系统,对汽车在途行驶时的侧倾角和侧倾角速度进行监测,并采用多阶递推模型对汽车侧倾姿态进行预测,当预测到侧倾达到极限工况时发出报警信息,提醒驾驶人员注意并采取相应减少侧向加速度的措施,从而达到预防汽车侧翻事故的发生,并基于VB2005,Matlab和NIMeasurement Studio开发了车载感知与侧翻预警系统软件,进行了系统仿真。实车道路试验与系统仿真实验进行了比较,结果表明:车载感知和预警系统能够及时准确预测汽车侧翻,提高汽车主动安全。     

Detection of Impending Vehicle Rollover with Road Bank Angle Consideration Using a Robust Fuzzy Observer

 This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate rollover detection, a new method is proposed to compute the time to rollover (TTR) using the load transfer ratio (LTR). The nonlinear model, deduced from the vehicle lateral and roll dynamics, is represented by a Takagi-Sugeno (T-S) fuzzy model. This representation is used to account for the nonlinearities of lateral cornering forces. The proposed T-S observer is designed with unmeasurable premise variables to cater for non-availability of the slip angles measurement. The proposed approach is evaluated using CarSim simulator under different driving scenarios. Simulation results show good efficiency of the proposed T-S observer and the rollover detection method.     

非线性系统的直接自适应输出反馈监督模糊控制

针对一类单输入单输出非线性不确定系统，提出一种稳定的直接自适应模糊输出反馈监督控制算法，该算法不需要系统的状态完全可测的假设条件，监督控制不仅迫使系统的状态在指定的集合内，而且当模糊自适应控制处于良好的工作状态时，监督控制可以关闭，证明了整个模糊自适应输出反馈控制算法可以保证闭环系统稳定。     

Guidance and nonlinear control system for autonomous flight of minirotorcraft unmanned aerial vehicles

Small unmanned aerial vehicles (UAVs) are becoming popular among researchers and vital platforms for several autonomous mission systems. In this paper, we present the design and development of a miniature autonomous rotorcraft weighing less than 700 g and capable of waypoint navigation, trajectory tracking, visual navigation, precise hovering, and automatic takeoff and landing. In an effort to make advanced autonomous behaviors available to mini‐ and microrotorcraft, an embedded and inexpensive autopilot was developed. To compensate for the weaknesses of the low‐cost equipment, we put our efforts into designing a reliable model‐based nonlinear controller that uses an inner‐loop outer‐loop control scheme. The developed flight controller considers the system's nonlinearities, guarantees the stability of the closed‐loop system, and results in a practical controller that is easy to implement and to tune. In addition to controller design and stability analysis, the paper provides information about the overall control architecture and the UAV system integration, including guidance laws, navigation algorithms, control system implementation, and autopilot hardware. The guidance, navigation, and control (GN&C) algorithms were implemented on a miniature quadrotor UAV that has undergone an extensive program of flight tests, resulting in various flight behaviors under autonomous control from takeoff to landing. Experimental results that demonstrate the operation of the GN&C algorithms and the capabilities of our autonomous micro air vehicle are presented. © 2009 Wiley Periodicals, Inc.