Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control (MPC) schemes and robust $$H_{\infty }$$ H ∞ state feedback control (RSC) method for trajectory tracking is proposed in this paper. The main objective of this paper is to compare MPC and RSC controllers’ performance in tracking predefined trajectory under different scenarios. MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire, which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode. RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison. Then, three test cases are built in CarSim-Simulink joint platform. Specifically, the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions. Besides, the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability. Furthermore, an extreme curve test is built where the road adhesion changes suddenly, in order to test the performance of both controllers under extreme conditions. Finally, the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

Risk-Sensitive Rear-Wheel Steering Control Method Based on the Risk Potential Field

Various driving assistance systems have been developed to reduce the number of automobile accidents. However, the control laws of these assistance systems differ based on each situation, and the discontinuous control command value may be input instantaneously. Therefore, a seamless and unified control law for driving assistance systems that can be used in multiple situations is necessary to realize more versatile autonomous driving. Although studies have been conducted on four-wheel steering that steers the rear wheels, these studies considered the role of the rear wheels only to improve vehicle dynamics and not to contribute to autonomous driving. Therefore, in this study, we define the risk potential field as a uniform control law and propose a rear-wheel steering control system that actively steers the rear wheels to contribute to autonomous driving, depending on the level of the perceived risk in the driving situation. The effectiveness of the proposed method is verified by a double lane change test, which is performed assuming emergency avoidance in simulations, and subject experiments using a driving simulator. The results indicate that actively steering the rear wheels ensures a safer and smoother drive while simultaneously improving the emergency avoidance performance.

Carsickness-based design and development of a controller for autonomous vehicles to improve the comfort of occupants

It is anticipated that passengers in autonomous vehicles will be more occupied with in-vehicle activities. Loss of the authority on driving and engaging in non-driving tasks could cause lower predictability of car motions. This decrease in predictability is expected to increase the sensitivity to carsickness. It appears that it is crucial to develop controllers for autonomous driving with the capability of improving passenger comfort by reducing carsickness. In this regard, it can be asked how the motion variables can be used for the minimization of a carsickness-related measure, while the vehicle is required to follow a given path. In this study, an optimal control approach is being proposed to minimize a quantitative measure of carsickness. In order to address carsickness during autonomous maneuvers, the well-known motion sickness dose value formulation in ISO 2631-1 is augmented with horizontal direction motion components to define a performance measure. The performance measure includes the motion sensed in vestibular system rather than the motion occurring in the vehicle itself. Therefore, mathematical model of the vestibular system is included in the design of controller. Effects of acceleration and jerk are included in performance measure simultaneously. Control oriented linear parameter varying vehicle model is developed to design the path following controller. By means of simulation studies in which path following control is implemented, motion sickness dose values of the controlled vehicle are examined. It is shown by a regular lane change test at various speeds that the proposed controller, which seeks the minimization of the motion sickness dose value, achieves a reduction of the acceleration and jerk felt by a passenger, while the vehicle follows the given path.

Modeling and dynamic analysis of a 6 x 6 heavy military truck by adaptive model predictive control with application to NATO lane change test course

In this paper, the computer-aided vehicle dynamic analysis of a 6x6 heavy military truck is presented and examined. For the analysis, a MATLAB/Simulink® platform is used to design and model a truck. The vehicle configuration taken into account for the analysis is the powertrain (engine, gear box, transfer gear, differential), suspension, steering system and tire model according to the Pacekja 89’ formulation. In addition, the effect of the rolling resistance and drag is considered, in order to represent the vehicle behavior as real as possible. The longitudinal dynamic and lateral dynamic are formulated. First, the longitudinal dynamic model is established by means of implementation of the weight transfer function. The vehicles are considered as rigid bodies with 1 degree of freedom. Second, the vehicular planar model with three wheels, well known as bicycle model, is applied following the North Atlantic Treaty Organization double line change maneuver test reaching 3 degree of freedom. The driver behavior is represented by using an adaptive model predictive control varying the longitudinal velocity. The forces for braking, inertia of the rotating components, the energy lost in the powertrain, and the effect of dive squat and rollover. The numerical simulation results are shown and compared with a full-vehicle model formed by using Mechanical Simulation Corporation’s truckSIM®. There were chosen simulation scenarios applied to the model to observe the effects of different parameters concerning the dynamic behavior, and also prepared in truckSIM® environment. The main contributions of this article are the development of the vehicular model, through the use of block diagrams in a reliable and relatively simple programming code such as MATLAB/Simulink®, with innovative tools used in the control of autonomous vehicle driving and the flexibility to adapt said model to different environmental conditions and different vehicle parameters.

A novel evaluation method for vehicle and traffic performance of different decision control of automatic lane change based on miniature model

Research on automatic lane-change decision is mainly limited to simulation validation and lacks real vehicle validation methods because it is limited by experimental site and automatic driving technology on real vehicles. This paper puts forward a miniature traffic model to simulate the actual traffic scene and achieves to verify the decision control of automatic lane-change scene. The miniature intelligent traffic scene contains miniature vehicles, simplified miniature road traffic environment, and wireless network communication. After testing the basic functions of the miniature traffic scene model, such as automatic lane change, lane keeping, and automatic following, a semi-physical simulation test of the traffic flow composed of the model vehicle and the virtual vehicle is carried out. The semi-physical simulation test includes vehicle-following test of hybrid-condition intelligent driver model, lane-change test of lane-change decision two-vehicle gaming model, and minimizing overall braking induced by lane changes. The results show that the feasibility of the method and of the lane-change decision two-vehicle gaming model of automatic lane change is better in terms of traffic safety, traffic efficiency, and homogeneity. Compared to the minimizing overall braking induced by lane-change model test, the test of lane-change decision two-vehicle gaming model improves 2.26% and 1.5% in the average speed and total driving distance, respectively. The standard deviation of the traffic speed of the lane-change decision two-vehicle gaming model was 28.57% lower than the minimizing overall braking induced by lane changes. Compared to pure simulation verification, the method considers the effects of actual sensor signals and actuator control, which is closer to the actual application.

Asymmetric Energy Harvesting and Hydraulically Interconnected Suspension: Modeling and Validations

This paper introduces a new form of energy-harvesting suspension that is integrated in a hydraulically interconnected suspension (HIS) system. The combined energy-harvesting and hydraulic interconnection features provide improved energy efficiency and vehicle dynamics performance. A half car model and a full car model are developed to validate the effectiveness of this design. Different dynamic input scenarios are used for model simulation, which includes single-wheel sinusoidal input, two-wheel sinusoidal input and double lane change test. The system performs better than a conventional suspension system in rolling dynamics in the cases of the single-wheel road input and double lane change test. The heaving dynamics is dependent on the frequency of the road input. The energy harvesting can generate up to 421 w at 4 Hz and 40 mm (peak to peak) road input.

Investigation on adaptive preview distance path tracking control with directional error compensation

Path tracking control cannot effectively satisfy the stability requirements of intelligent vehicles under large curvature conditions. To solve this problem, an adaptive preview distance path tracking controller with a hierarchical structure is proposed in this study. The vehicle centroid lateral acceleration and lateral error of the preview point are taken as the inputs of the upper controller, and the optimal preview distance is obtained based on fuzzy inference. To eliminate the subjective influence of the membership function and fuzzy rule selection in the fuzzy controller design, a genetic algorithm is used for optimization. The lower controller is a sliding mode controller that aims to achieve intelligent vehicle self-tracking. Moreover, a radial basis function neural network is adopted to combine with the sliding mode controller to eliminate output chattering. However, adaptive adjustment of the preview distance deteriorates the vehicle directional tracking error, which makes controlling the vehicle at the road curvature switching point difficult. Thus, a directional error compensation controller is designed based on the iterative learning theory to compensate the front wheel steering angle. Simulations under two standard conditions are carried out to verify the control effect. The results show that, in a double lane change test, the peak centroid acceleration and coaxial load transfer rates decreased by 26.91% and 19.83% at low velocity, respectively, and the improvements at high velocity were 42.71% and 39.22%, respectively. In the pylon course slalom test, all three performance indicators decreased by more than 30%, which indicates the modified adaptive preview distance path tracking controller with a hierarchical structure can effectively improve the vehicle handling performance and roll stability and can ensure the tracking accuracy.

Variable steering ratio control of steer-by-wire vehicle to improve handling performance

To improve vehicle handling performance, a variable steering ratio characteristic for steer-by-wire system is designed. The steering ratio is adjusted by a compensating coefficient according to vehicle longitudinal speed and steering wheel angle. To evaluate the performance of vehicle with variable steering ratio, simulations are conducted based on an objective evaluation index, which consists of quadratic cost functions of vehicle lateral deviation, steering angular speed, vehicle lateral acceleration and roll angle. By using the optimized data from the simulation results, a Takagi-Sugeno fuzzy neural network is designed for the steering ratio control. In order to test and validate the proposed controller, a series of comparison experiments are conducted on a closed-loop driver-vehicle system, including lemniscate curve test and double lane-change test. The results demonstrate that compared with a conventional steering system with fixed steering ratio, the proposed system can not only improve steering agility at low speed and steering stability at high speed, but also reduce driver’s workload in critical driving conditions.

Preliminary investigation of sleep-related driving fatigue experiment in Indonesia

Sleep-related driving fatigue has been recognised as one main cause of traffic accidents. In Indonesia, experiment-based driving fatigue study is still very limited, therefore it is necessary to develop laboratory-based experiment procedure for sleep-related fatigue study. In this preliminary study, we performed a literature review to find references for the procedure and three pilot experiments to test the instruments and procedure to be used in measuring driving fatigue. Three subjects participated, both from experienced and inexperienced drivers. Our pilot experiments were performed on a driving simulator using OpenDS software with brake and lane change test reaction time measurement. We measured sleepiness by using Karolinska Sleepiness Scale (KSS) Questionnaire. The conditions of the experiment were based on illumination intensity as well as pre- and post-lunch session. We found that lane change reaction time is more potential than brake reaction time to measure driving performance as shown by the more fluctuating data. Post-lunch seems to induce drowsiness greater than illumination intensity. KSS questionnaire seems non-linear with driving performance data. We need to test further these speculations in the future studies involving a sufficient number of subjects. We also need to compare the effect of circadian rhythm and sleep deprivation on driving fatigue. The use of eye closure and physiological measurement in further study will enable us to measure driving fatigue more objectively. Considering the limitations, more preliminary experiments are required to be performed before conducting the main experiment of driving fatigue.