Active Steering Control System Research Articles

A Randomized Filtering Strategy Against Inference Attacks on Active Steering Control Systems

In this paper, we develop a framework against inference attacks aimed at inferring the values of the controller gains of an active steering control system (ASCS). We first show that an adversary with access to the shared information by a vehicle, via a vehicular ad hoc network (VANET), can reliably infer the values of the controller gains of an ASCS. This vulnerability may expose the driver as well as the manufacturer of the ASCS to severe financial and safety risks. To protect controller gains of an ASCS against inference attacks, we propose a randomized filtering framework wherein the lateral velocity and yaw rate states of a vehicle are processed by a filter consisting of two components: a nonlinear mapping and a randomizer. The randomizer randomly generates a pair of pseudo gains which are different from the true gains of the ASCS. The nonlinear mapping performs a nonlinear transformation on the lateral velocity and yaw rate states. The nonlinear transformation is in the form of a dynamical system with a feedforward-feedback structure which allows real-time and causal implementation of the proposed privacy filter. The output of the filter is then shared via the VANET. The optimal design of randomizer is studied under a privacy constraint that determines the protection level of controller gains against inference attacks, and is in terms of mutual information. It is shown that the optimal randomizer is the solution of a convex optimization problem. By characterizing the distribution of the output of the filter, it is shown that the statistical distribution of the filter’s output depends on the pseudo gains rather than the true gains. Using information-theoretic inequalities, we analyze the inference ability of an adversary in estimating the control gains based on the output of the filter. Our analysis shows that the performance of any estimator in recovering the controller gains of an ASCS based on the output of the filter is limited by the privacy constraint. The performance of the proposed privacy filter is compared with that of an additive noise privacy mechanism. Our numerical results show that the proposed privacy filter significantly outperforms the additive noise mechanism, especially in the low distortion regime.

Research on Stability Control Method of Vehicle Based on Steering Torque Superposition

At present, most stability control systems based on active steering are superposition control of steering Angle. For the steering system configuration commonly used in automatic driving vehicles, the active steering control system of steering angle superposition cannot be realized. In order to achieve man-machine collaborative driving, the co-driving intelligent vehicles usually realize automatic steering control based on the torque superposition, which solves the drawback that the driver of the Angle superposition cannot participate in the steering. In this paper, an active steering control method of superposition of steering torque based on Receding horizon control is proposed for man-machine collaborative driving of co-drive intelligent vehicles. This control method combines steering system with vehicle dynamics system, and takes steering motor torque as the sole control input, which ensures that the driver has the ultimate control right and makes the control of the system more stable. In order to solve the system uncertainties caused by model mismatch and external disturbances, the optimal control rate in predictive time domain can be calculated according to real-time vehicle state parameters by receding horizon control. In the design of the controller, the yaw rate deviation is the input of the controller, and then the calculated superposition torque is input into the vehicle model in real time, and the steering wheel angle is observed as a state variable. The control strategy can effectively compensate for the uncertainty of the system such as model mismatch and external disturbance, and enhance the robustness of the system.

A new robust combined control system for improving manoeuvrability, lateral stability and rollover prevention of a vehicle

This paper presents a new effective method in order to achieve an appropriate performance for a four-wheeled vehicle during different conditions. The main goal of the study is focused on the handling improvement and lateral stability increment of the vehicle using a robust combined control system. First, in order to increase the vehicle's manoeuvrability, an active steering control system is proposed based on the sliding mode control method and using the simplified dynamic model. The tracking of the desired values of the yaw rate and lateral velocity of the vehicle is the main purpose for using the controller. Also, in order for verifying the performance of the sliding mode controller, the linearization feedback control method is used to design the active steering control system. Moreover, to improve the directional stability of the vehicle, a new active roll control system is proposed. In this control system, the roll angle is considered as the state variable as well as the active anti-roll-bar is utilized as an actuator to generate the roll moment. Then, a 14-degrees-of-freedom nonlinear dynamic model of the vehicle validated using CarSim software is utilized. Afterward, the performance of the designed combined control system is investigated at various velocities. The simulation results confirm that the combined control system has an important effect on vehicle's manoeuvrability improvement and its lateral stability increment, especially during severe transient manoeuvre.

Active steering control system for an independent wheel drive electric vehicle

This research presents an active steering control system (ASCS) for an independent wheel drive electric vehicle (EV). The ASCS will manoeuvre the independently actuated (IA) all-wheel drive (AWD) EV via coordinating the angular velocities of the four wheels plus active front steering (AFS). Due to the physical and mechanical limitations of the steering input in conventional AFS, the differential speed between left and right wheels of an IA EV is used to generate the additional steering effects. The proposed ASCS is a combination of forward speed and yaw rate controllers, designed using the robust H∞ control methodology. The effectiveness of the proposed control system is analysed using a high-fidelity vehicle model by simulating different driving conditions and road disturbances cases. The simulation results indicate that the proposed system can significantly improve the vehicle performance by tracking the desired yaw rate and speed.

Active steering control system for an independent wheel drive electric vehicle

This research presents an active steering control system (ASCS) for an independent wheel drive electric vehicle (EV). The ASCS will manoeuvre the independently actuated (IA) all-wheel drive (AWD) EV via coordinating the angular velocities of the four wheels plus active front steering (AFS). Due to the physical and mechanical limitations of the steering input in conventional AFS, the differential speed between left and right wheels of an IA EV is used to generate the additional steering effects. The proposed ASCS is a combination of forward speed and yaw rate controllers, designed using the robust H∞ control methodology. The effectiveness of the proposed control system is analysed using a high-fidelity vehicle model by simulating different driving conditions and road disturbances cases. The simulation results indicate that the proposed system can significantly improve the vehicle performance by tracking the desired yaw rate and speed.

A new robust controller to improve the lateral dynamic of an articulated vehicle carrying liquid

In this paper to improve manoeuvrability and jackknifing prevention, as well as increasing rollover stability of an articulated vehicle carrying liquid, a new control system coupled with an active roll control system and an active steering control system is presented. First, a 16-degrees-of-freedom nonlinear dynamic model of an articulated vehicle is developed. Next, the dynamic interaction of the liquid cargo with the vehicle is investigated by integrating a quasi-static liquid sloshing model with a tractor semi-trailer model. Initially, to improve the roll stability of the vehicle, an active roll control system is presented. The active anti-roll bar is employed as an actuator to generate the roll moment. Furthermore, the manoeuvrability increment and jackknifing prevention are targeted using the active steering control system. The main purpose of using the active steering controller is to track the desired values of tractor yaw rate, articulation angle and tractor lateral velocity in different roads, various filled volumes and different speeds. The active steering control system is designed based on a three-degrees-of-freedom dynamic model of the articulated vehicle carrying liquid and on the basis of sliding mode control. Simulation results confirmed robust performance of the control system for different filled volumes, especially during the critical manoeuvre. Further studies show that the tracking of the desired articulation angle has not only eliminated the off-tracking path, but also has made the semi-trailer rear end follow the fifth wheel path.

Improvement in the rollover stability of a liquid-carrying articulated vehicle via a new robust controller

In this paper, in order to improve the roll stability of an articulated vehicle carrying a liquid, an active roll control system is utilized by employing two different control methods. First, a 16-degree-of-freedom non-linear dynamic model of an articulated vehicle is developed. Next, the dynamic interaction of the liquid cargo with the vehicle is investigated by integrating a quasi-dynamic liquid sloshing model with a tractor–semitrailer model. Initially, to improve the lateral dynamic stability of the vehicle, an active roll control system is developed using classical integral sliding-mode control. The active anti-roll bar is employed as an actuator to generate the roll moment. Next, in order to verify the classical sliding-mode control performance and to eliminate its chattering, the backstepping method and the sliding-mode control method are combined. Subsequently, backstepping sliding-mode control as a new robust control is implemented. Moreover, in order to prevent both yaw instability and jackknifing, an active steering control system is designed on the basis of a simplified three-degree-of-freedom dynamic model of an articulated vehicle carrying a liquid. In the introduced system, the yaw rate of the tractor, the lateral velocity of the tractor and the articulation angle are considered as the three state variables which are targeted in order to track their desired values. The simulation results show that the combined proposed roll control system is more successful in achieving target control and reducing the lateral load transfer ratio than is classical sliding-mode control. A more detailed investigation confirms that the designed active steering system improves both the lateral stability of the vehicle and its handling, in particular during a severe lane-change manoeuvre in which considerable instability occurs.

Development of active front wheel steering control system keeping stable region in driving phase diagram

This paper presents a new active steering control system based on driving phase diagram (β fr −δ f diagram). In order to make state variables to follow those of nominal vehicle model that was developed under no consideration of disturbance, Quadratic Programming Problem (QPP) is formulated, where time varying objective function minimizes the differences between nominal and actual parameters. The steering characteristic in active steering control system changes when the vehicle faces disturbance such as crosswind and flat tire, and driver tries to counteract it after recognizing the change. The proposed method defines a stability region on β fr −δ f diagram. In order to make β fr and δ f remain in the stability region, a new model predictive controller is proposed. While conventional controllers are restrictive to satisfy the β fr −δ f diagram based stability condition, the proposed controller ensures solution space and also plays a direct role to minimize the evaluation function in the constrained optimal control problem.

A Study on Shared Control between the Driver and an Active Steering Control System in Emergency Obstacle Avoidance Situations

Recently, automatic steering systems for emergency obstacle avoidance have been studied extensively. The control input of such active steering control systems can be classified into the steering angle and the steering torque input. The steering torque based control provides some degree of freedom for drivers to control the vehicle motion, thus it has potential for development as steering assistance system. This paper describes the evaluation of shared control characteristics between human drivers and the active steering system for obstacle avoidance assistance system based on steering torque input. The shared control characteristics between the driver and the active steering system are investigated by using the driving simulator reconstructing a dangerous scenario.

비젼 기반 자율주행을 위한 다중비율 예측기 설계와 모델예측 기반 능동조향 제어

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].