Analyses of Vision-based Lateral Control for Automated Highway System

The stability and performance of a vision-based vehicle lateral control system are analyzed. Effects of look-ahead distance, vision delay, and vehicle speed on the performance of vision feedback control system are examined by using frequency domain and time domain methods. A measurement model of the vision system is derived from the point of view of multiple sensors. The quantization error of the vision system is analyzed and the way of extracting essential information for control is studied. Based on this analysis, some guidelines for the design of vision-based controllers are proposed. A design example is further illustrated for a vision system with a substantial time delay.     

Adaptive Throttle Control for Speed Tracking

SUMMARY

Electronic throttle control is an important part of every advanced vehicle control system. In this paper we design an adaptive control scheme for electronic throttle that achieves good tracking of arbitrary constant speed commands in the presence of unknown disturbances. The design is based on a simplified linear vehicle model which is derived from a validated nonlinear one. The designed control scheme is simulated using the validated full order nonlinear vehicle model and tested on an actual vehicle. The simulation and vehicle test results are included in this paper to show the performance of the controller. Due to the learning capability of the adaptive control scheme, changes in the vehicle dynamics do not affect the performance of the controller in any significant manner.     

Design and Evaluation of Robust Cooperative Adaptive Cruise Control Systems in Parameter Space

This paper is on the design of cooperative adaptive cruise control systems for automated driving of platoons of vehicles in the longitudinal direction. Longitudinal models of vehicles with simple dynamics, an uncertain first order time constant and vehicle to vehicle communication with a communication delay are used in the vehicle modeling. A robust parameter space approach is developed and applied to the design of the cooperative adaptive cruise control system. D-stability is chosen as the robust performance goal and the feedback PD controller is designed in controller parameter space to achieve this D-stability goal for a range of possible longitudinal dynamics time constants and different values of time gap. Preceding vehicle acceleration is sent to the ego vehicle using vehicle to vehicle communication and a feedforward controller is used in this inter-vehicle loop to improve performance. Simulation results of an eight vehicle platoon of heterogeneous vehicles are presented and evaluated to demonstrate the efficiency of the proposed design method. Also, the proposed method is compared with a benchmark controller and the feedback only controller. Time gap regulation and string stability are used to assess performance and the effect of the vehicle to vehicle communication frequency on control system performance is also investigated.     

Robust control and actuator dynamics compensation for railway vehicles

A robust controller is designed for active steering of a high speed train bogie with solid axle wheel sets to reduce track irregularity effects on the vehicle’s dynamics and improve stability and curving performance. A half-car railway vehicle model with seven degrees of freedom equipped with practical accelerometers and angular velocity sensors is considered for the H_∞ control design. The controller is robust against the wheel/rail contact parameter variations. Field measurement data are used as the track irregularities in simulations. The control force is applied to the vehicle model via ball-screw electromechanical actuators. To compensate the actuator dynamics, the time delay is identified online and is used in a second-order polynomial extrapolation carried out to predict and modify the control command to the actuator. The performance of the proposed controller and actuator dynamics compensation technique are examined on a one-car railway vehicle model with realistic structural parameters and nonlinear wheel and rail profiles. The results showed that for the case of nonlinear wheel and rail profiles significant improvements in the active control performance can be achieved using the proposed compensation technique.     

Application of Learning Automata to Controller Design in Slow-Active Automobile Suspensions

SUMMARY

This study considers a new design methodology in the context of active vehicle suspension control. The approach combines concepts from Stochastic Optimal Control with those of Learning Automata. A learning automaton effectively learns optimal control on-line in the vehicle, in an appropriate stochastic “test-track” environment. For practical application, the overwhelming advantage of this approach is that no explicit modelling is required, and considerable time savings may be expected in system development. This simulation study considers the on-line learning of optimal control in a low-bandwidth active suspension system, where control feedback is confined to a body-mounted accelerometer at each corner of the vehicle. It is shown that learning can successfully take place under a range of conditions, including the case when there is substantial transducer noise. The performance of the resulting control system is shown to depend heavily on the nature of the learning environment.     

Analysis of Automatic Steering Control for Highway Vehicles with Look-down Lateral Reference Systems

SUMMARY

In this paper, steering control for passenger cars on automated highways is analyzed, concentrating on look-down reference systems. Extension of earlier experimental results for low speed to highway speed is shown to be non-trivial. The limitations of pure output-feedback of lateral vehicle displacement from the road reference are examined under practical constraints and performance requirements like robustness, maximum lateral error and comfort. The in-depth system analysis directly leads to a new alternative design direction which allows to preserve look-ahead reference systems for highway speed automatic driving.     

Frequency Spectral Analysis of Bridge-Vehicle System due to Road Surface Roughness

SUMMARY

The paper presents a new method to study the dynamic properties of the bridge-vehicle system. The transfer function of the system is obtained by iteration in the frequency domain instead of the time domain. The relationship between vehicle speed and the lowest natural frequency of the system is investigated and a parametric study of the system stability is made. The varying parameters concerned are the vehicle speed, the ratio of vehicle mass to bridge mass, the ratio of vehicle eigenfrequency to bridge eigenfrequence, and the relative damping of the vehicle and bridge.     

Vehicle detection system design based on stereo vision sensors

Vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, a vehicle detection system using stereo vision sensors is developed. This system utilizes feature extraction, epipoplar constraint and feature matching in order to robustly detect the initial corresponding pairs. The proposed system can detect a leading vehicle in front and can estimate its position parameters such as the distance and heading angle. After the initial detection, the system executes the tracking algorithm for the vehicles in the lane. The proposed vehicle detection system is implemented on a passenger car and its performances are verified experimentally.     

An Active Suspension with Optimal Linear State Feedback

SUMMARY

In this paper modern optimal control theory is applied to the design of an active suspension system for a motor vehicle. The road profile is assumed to be continuous and random with a power spectral density (P.S.D.) which varies inversely with the square of the frequency. The quadratic integral type performance index employed is a weighted sum of the integral squares of body acceleration, dynamic tyre deflection and relative body-to-axle displacement. A solution is obtained for the infinite time case which is both computationally and physically realizable as an active suspension in which the only continuous measurements required are the body absolute velocity and the body displacement relative to the road. The performance is compared with that of a conventional type passive suspension and found to be significantly better in practically all respects.     

Application of Sensitivity Methods to Analysis and Synthesis of Vehicle Dynamic Systems

SUMMARY

The development and application of sensitivity methods for determining the effects of parameter changes on the response of vehicle dynamic systems is presented. The procedures shown can be used to enhance the analysis and synthesis processes of virtually any road or rail vehicle system regardless of its complexity. The parametric sensitivity of vehicle models in time domain, steady state models and vehicle models in frequency domain can be investigated using different types of sensitivity functions, both dimensional and dimensionless including first order standard, percentage, logarithmic, second order standard, and logarithmic and percentage sensitivity measures. These sensitivity functions and measures are determined as functions of partial derivatives of system variables taken with respect to system parameters. In the case of sensitivity functions in the frequency domain the variable values are computed as either the magnitude or phase angle of a complex element of the transfer function matrix. The methods presented enable to determine the influence of all system primary (constant) and secondary (non-constant) parameters on system primary and secondary variables. The primary variables are state variables or elements of the transfer function matrix and the secondary variables may be any functions of primary variables and system parameters. Typical secondary system parameters which can be examined include initial conditions, time variant coefficients, natural frequencies, loads, and typical secondary variables are forces, weight transfers, stability factors and energy components. The analysis of sensitivity results obtained for three vehicle handling models in both linear and nonlinear regimes of vehicle performance and utilizing various types of sensitivity functions is also presented.     

On the Stability of a Flexible Vehicle Controlled by a Human Pilot

SUMMARY

This paper presents a stability analysis of a vehicle flexible in the plane of yawing and being controlled by a human pilot. The vehicle is represented by a two degrees-of-freedom model and the pilot is assumed to respond to the lateral displacement and to the lateral velocity with a time delay. It is shown that in order for the pilot model to exhibit a realistic human operator behavior, driver's gain must be linearly proportional to vehicle velocity and also inversely related to frontal visibility. Moreover, application of the Hurwitz criterion indicated that flexibility of the vehicle frame has a destabilising effect on the lateral stability and reduces the stable domain of operation.     

Optimal Preview Control of Rear Suspension Using Nonlinear Neural Networks

SUMMARY

The performance of neural networks to be used for identification and optimal control of nonlinear vehicle suspensions is analyzed. It is shown that neuro-vehicle models can be efficiently trained to identify the dynamical characteristics of actual vehicle suspensions. After trained, this neuro-vehicle is used to train both front and rear suspension neuro-controllers under a nonlinear rear preview control scheme. To do that, a neuro-observer is trained to identify the inverse dynamics of the front suspension so that front road disturbances can be identified and used to improve the response of the rear suspension. The performance of the vehicle with neuro-control and with LQ control are compared.     

Effects of field of view on lateral control performance in a vision-based autonomous vehicle

This paper addresses the effects of field of view on lateral control performance in a vision-based autonomous vehicle with simulation studies. When a vehicle drives around a circle with the lateral control algorithm proposed here, the performance is evaluated for a tracking error and ride quality for locations and sizes of the field of view. The results show that a field of view covering from 10 to 30 m in front of a vehicle is the optimal with respect to both the error and the ride quality, and it is independent of the vehicle speed.     

An adaptive fuzzy-sliding lateral control strategy of automated vehicles based on vision navigation

Lateral control is considered to be one of the toughest challenges in the development of automated vehicles due to their features of nonlinearities, parametric uncertainties and external disturbances. In order to overcome these difficulties, an adaptive fuzzy-sliding mode control strategy used for lateral control of vision-based automated vehicles is proposed in this paper. First, a vision algorithm is designed to provide accurate location information of vehicle relative to reference path. Then, an adaptive fuzzy-sliding mode lateral controller is proposed to counteract parametric uncertainties and strong nonlinearities, and the asymptotic stability of the closed-loop lateral control system is proven by the Lyapunov theory. Finally, experimental results indicate that the proposed algorithm can achieve favourable tracking performance, and it has strong robustness.     

Improvement of Vehicle Dynamics by Rear Braking Force Control

SUMMARY

A study on effective use of rear braking force to improve a brake performance and vehicle dynamics are carried out. On a ordinary condition, the rear braking force could be more increased to a conventional braking force distribution. Based on this thought, the brake performances are estimated. The results show the effects not only improve the brake performance but also reduce a pitching at braking and moderate a vehicle OS behavior in a turn during braking. These are verified by experimental test vehicle equipped with a rear braking force control system.     

Robust design of a passive linear quarter car suspension system using a multi-objective evolutionary algorithm and analytical robustness indexes

This paper deals with the robust design of a passive vehicle suspension system. A robust design methodology based on a multi-objective evolutionary algorithm (MOEA) is used to handle the trade-off between the considered conflicting performance requirements under uncertainty and feasibility constraints. A constrained multi-objective optimisation problem is formulated and the notion of Pareto-optimality is used to increase the quality of the candidate design solutions obtained at each generation by the MOEA. To save computation time, a simplified physical model (quarter car) is considered and the optimisation is performed in the frequency domain, using relevant transmissibilities of the system. The robustness is directly investigated by means of analytical robustness indexes. Time-consuming a posteriori methods, like designs of experiments or Monte Carlo analysis, are therefore avoided. A set of non-dominated solutions is obtained. Thus the designer not only selects a special design, in accordance with the wanted vehicle configuration, but also includes the robustness of each performance requirement in his final decision.     

Modelling of Driver/Vehicle Directional Control System

Abstract

Different driver models and driver/vehicle/road closed-loop directional control systems are reviewed and compared. Evaluation methods of vehicle handling quality based on closed-loop system dynamics, stability of the closed-loop system, and optimization of vehicle design are discussed.     

Adaptive Control of Vehicle Suspension

SUMMARY

An adaptive control scheme for a two-degree-of-freedom vehicle model with active suspension is proposed. The performance goal is to minimize the variance of vehicle body acceleration under inequality constraints imposed on the variance of either tire or suspension deflection. An active suspension is adapted to the changes in vehicle velocity and the type of road (or terrain) surface which is assumed to be reconstructable from the accelerometer measurements. The control gain factors are obtained by the iterative method taking advantage of stochastic linear control theory. The performance of the system is evaluated and compared to that of an active system with constant gain factors and a passive system with adjustable parameters.     

Heavy-duty vehicle modelling and longitudinal control

This paper addresses modelling, longitudinal control design and implementation for heavy-duty vehicles (HDVs). The challenging problems here are: (a) an HDV is mass dominant with low power to mass ratio; (b) They possess large actuator delay and actuator saturation. To reduce model mismatch, it is necessary to obtain a nonlinear model which is as simple as the control design method can handle and as complicated as necessary to capture the intrinsic vehicle dynamics. A second order nonlinear vehicle body dynamical model is adopted, which is feedback linearizable. Beside the vehicle dynamics, other main dynamical components along the power-train and drive-train are also modelled, which include turbocharged diesel engine, torque converter, transmission, transmission retarder, pneumatic brake and tyre. The braking system is the most challenging part for control design, which contains three parts: Jake (engine compression) brake, air brake and transmission retarder. The modelling for each is provided. The use of engine braking effect is new complementary to Jake (compression) brake for longitudinal control, which is united with Jake brake in modelling. The control structure can be divided into upper level and lower level. Upper level control uses sliding mode control to generate the desired torque from the desired vehicle acceleration. Lower level control is divided into two branches: (a) engine control: from positive desired torque to desired fuel rate (engine control) using a static engine mapping which basically captures the intrinsic dynamic performance of the turbo-charged diesel engine; (b) brake control: from desired negative torque to generate Jake brake cylinder number to be activated and ON/OFF time periods, applied pneumatic brake pressure and applied voltage of transmission retarder. Test results are also reported.     

Integrated Control of Active Rear Wheel Steering and Direct Yaw Moment Control

SUMMARY

An integrated control system of active rear wheel steering (4WS) and direct yaw moment control (DYC) is presented in this paper. Because of the tire nonlinearity that is mainly due to the saturation of cornering forces, vehicle handling performance is improved but limited to a certain extent only by steering control. Direct yaw moment control using braking and/or driving forces is effective not only in linear but also nonlinear ranges of tire friction circle. The proposed control system is a model matching controller which makes the vehicle follow the desired dynamic model by the state feedback of both yaw rate and side slip angle. Various computer simulations are carried out and show that vehicle handling performance is much improved by the integrated control system.