A Comparison of Alternative Obstacle Avoidance Strategies for Vehicle Control

In Alleyne (1996) several vehicle control options were considered for Unintended Roadway Departure (URD) prevention and conclusions were drawn as to the efficacy of each method. This companion paper investigates the use of several different inputs for the control of a vehicle, in the context of Obstacle Avoidance for autonomous vehicles. In this investigation, the goal of the controller is to provide an intervention in the event of the vehicle detecting an obstacle in its path. The five types of inputs that will be considered are (i) Four Wheel Steering; (ii) Front Wheel Steering; (iii) Four Wheel Brake Steering; (iv) Front Wheel Brake Steering; and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a more complete, nonlinear vehicle model. A key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, an important metric of performance is the ratio of peak tire force used versus available tire force. The conclusions reached in this paper shed additional light on appropriate input actuator methods for vehicle guidance and control.     

A Comparison of Alternative Intervention Strategies for Unintended Roadway Departure (URD) Control

This paper investigates the use of several different inputs for the control of a vehicle, in the context of URD. In this investigation, the goal of the URD controller is to provide an intervention in the event of the vehicle leaving the road. The types of inputs that will be considered are (i) Four Wheel Steering, (ii) Front Wheel Steering, (iii) Four Wheel Brake Steering, (iv) Front Wheel Brake Steering, and (v) Rear Wheel Brake Steering. The controller design is an LQ controller based on the simplified dynamics of a 2 degree of freedom bicycle model. However, the analysis of the different strategies are performed on a 7 degree-of-freedom nonlinear vehicle model. The key contribution of this paper is the quantitative evaluation of the relative efficiencies of each of these input strategies being examined. Unlike most control schemes, the performance measure to be used will not be the output tracking error of the system. Instead, the metric of performance is the ratio of peak tire force used versus available tire force or, in other words, the actuator response relative to the maximum available actuator capability.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Drive control system design for stability and maneuverability of a 6WD/6WS vehicle

This paper describes a drive controller designed to improve the lateral vehicle stability and maneuverability of a 6-wheel drive / 6-wheel steering (6WD/6WS) vehicle. The drive controller consists of upper and lower level controllers. The upper level controller is based on sliding control theory and determines both front and middle steering angle, additional net yaw moment, and longitudinal net force according to the reference velocity and steering angle of a manual drive, remotely controlled, autonomous controller. The lower level controller takes the desired longitudinal net force, yaw moment, and tire force information as inputs and determines the additional front steering angle and distributed longitudinal tire force on each wheel. This controller is based on optimal distribution control and takes into consideration the friction circle related to the vertical tire force and friction coefficient acting on the road and tire. Distributed longitudinal/lateral tire forces are determined as proportion to the size of the friction circle according to changes in driving conditions. The response of the 6WD/6WS vehicle implemented with this drive controller has been evaluated via computer simulations conducted using the Matlab/Simulink dynamic model. Computer simulations of an open loop under turning conditions and a closed-loop driver model subjected to double lane change have been conducted to demonstrate the improved performance of the proposed drive controller over that of a conventional DYC.     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Controller Development and Evaluation

SUMMARY

Due to increased traffic congestion and travel times, research in Advanced Vehicle Control Systems (AVCS) has focused on automated lateral and headway control. Automated vehicles are seen as a way to increase freeway capacity and vehicle speeds while reducing accidents due to human error. Recent research in automated lateral control has focused on vehicle control during low-g maneuvers. To increase safety, automated lateral controllers will need to recognize and react to emergency situations.

This paper investigates the effects of vehicle and tire model order on the response of automated vehicles to an emergency step lane change using a controller based on linear vehicle and tire models. From these studies it is concluded that control strategies based solely on linear vehicle and tire models are inadequate for emergency vehicle maneuvers.

A strategy is then proposed to automatically control vehicles through emergency maneuvers. Here the response of a nonlinear vehicle model is used with a linear state model to optimize controller gains for nonlinear maneuvers. An emergency step lane change is used as a preliminary test of the method.     

Multi-axle vehicle dynamics stability control algorithm with all independent drive wheel

The stability driving characteristic and the tire wear of 8-axle vehicle with 16-independent driving wheels are discussed in this paper. The lateral stability of 8-axle vehicle can be improved by the direct yaw moment which is generated by the 16 independent driving wheels. The hierarchical controller is designed to determine the required yaw torque and driving force of each wheel. The upper level controller uses feed-forward and feed-backward control theory to obtain the required yaw torque. The fuzzification weight ratio of two control objective is built in the upper level controller to regulate the vehicle yaw and lateral motions. The rule-based yaw moment distribution strategy and the driving force adjustment based on the safety of vehicle are proposed in the lower level controller. The influence of rear steering angle is considered in the distribution of driving force of the wheel. Simulation results of a vehicle double lane change show the stability of 8-axle vehicle under the proposed control algorithm. The wear rate of tire is calculated by the interaction force between the tire and ground. The wear of tire is different from each other for the vehicle with the stability controller or not.     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Model Development,Validation and Comparison

SUMMARY

Recent research on autonomous highway vehicles has begun to focus on lateral control strategies. The initial work has focused on vehicle control during low-g maneuvers at constant vehicle speed, typical of lane merging and normal highway driving. In this paper, and its companion paper, to follow, the lateral control of vehicles during high-g emergency maneuvers is addressed. Models of the vehicle dynamics are developed, showing the accuracy of the different models under low and high-g conditions. Specifically, body roll, tire and drive-train dynamics, tire force saturation, and tire side force lag are shown to be important effects to include in models for emergency maneuvers. Current controllers, designed for low-g maneuvers only, neglect these effects. The follow on paper demonstrates the performance of lateral controllers during high-g lateral emergency maneuvers using these vehicle models.     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

Enhancing grey prediction fuzzy controller for active suspension systems

A grey prediction fuzzy controller (GPFC) was proposed to control an active suspension system and evaluate its control performance. The GPFC employed the grey prediction algorithm to predict the position output error of the sprung mass and the error change as input variables of the traditional fuzzy controller (TFC) in controlling the suspension system to suppress the vibration and the acceleration amplitudes of the sprung mass for improving the ride comfort of the TFC used; however, the TFC or GPFC was employed to control the suspension system, resulting in a large tire deflection so that the road-holding ability in the vehicle becomes worse than with the original passive control strategy. To overcome the problem, this work developed an enhancing grey prediction fuzzy controller (EGPFC) that not only had the original GPFC property but also introduced the tire dynamic effect into the controller design, also using the grey prediction algorithm to predict the next tire deflection error and the error change as input variables of another TFC, to control the suspension system for enhancing the road-holding capability of the vehicle. The EGPFC has better control performances in suppressing the vibration and the acceleration amplitudes of the sprung mass to improve the ride quality and in reducing the tire deflection to enhance the road-holding ability of the vehicle, than both TFC and GPFC, as confirmed by experimental results.     

Direct tire force generation algorithm based on non-iterative nonlinear inverse tire model

The function of vehicle dynamics control system is adjusting the yaw moment, the longitudinal force and lateral force of a vehicle body through several chassis systems, such as brakes, steering and suspension. Individual systems such as ESC, AFS and 4WD can be used to achieve desired performance by controlling actuator variables. However, integrated chassis control systems that have multiple objectives may not simply achieve the desired performance by controlling the actuators directly. Usually those systems determine the required tire forces in an upper level controller and a lower level controller regulates the tire forces through the actuators. The tire force is controlled in a recursive way based on vehicle state measurement, which may not be sufficient for fast response. For immediate force tracking, we introduce a direct tire force generation method that uses a nonlinear inverse tire model, a pseudo-inverse model of vehicle dynamics and the relationship between longitudinal force and brake pressure.     

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.     

Optimal Performance of Variable Component Suspensions

SUMMARY

Most vehicle suspension systems use fixed passive components that offer a compromise in performance between sprung mass isolation, suspension travel, and tireroad contact force. Recently, systems with discretely adjustable dampers and air springs been added to production vehicles. Active and semi-active damping concepts for vehicle suspensions have also been studied theoretically and with physical prototypes. This paper examines the optimal performance comparisons of variable component suspensions, including active damping and full-state feedback, for “quartercar” heave models. Two and three dimensional optimizations are computed using performance indicators to find the component parameters (control gains) that provide “optimal” performance for statistically described roadway inputs. The effects of performance weighting and feedback configuration are examined. Active damping is shown to be mainly important for vehicle isolation. A passive vehicle suspension can control suspension travel and tire contact force nearly as well as a full state feedback control strategy.     

Selection of Actuator Combination in Integrated Chassis Control Using Taguchi Method

This paper presents a method to select the actuator combination in integrated chassis control using Taguchi method. Electronic stability control (ESC), active front and rear steering (AFS/ARS) are used as an actuator, which is needed to generate a control tire force. After computing the control yaw moment in the upper-level controller, it is distributed into the control tire forces, generated by ESC, AFS and ARS in the lower-level controller. In this paper, the weighted pseudo-inverse control allocation (WPCA) with variable weights is used to determine the control tire forces of each actuator. Taguchi method is adopted for sensitivity analysis on variable weights of WPCA in terms of the control performances such as the maneuverability and the lateral stability. For sensitivity analysis, simulation is performed on a vehicle simulation package, CarSim. From sensitivity analysis, the most effective actuator combination is selected.     

Controller design for soft-disability remedy of the electric power steering system

The electric power steering (EPS) system is designed to reduce the effort exerted by driver on the steering wheel. One of the most common and critical failures of EPS is the soft-disability of the torque sensor or the loss of its signal, which leads to the instant shutdown of the EPS system while turning and causes serious traffic accidents. In this paper, a novel controller based on the self-alignment torque (SAT) estimation was designed to remedy the soft-disability of EPS system. After the SAT estimation method was verified by the empirical Magic Formula (MF) tire model, the remedy control strategy based on the SAT estimation was developed and evaluated by simulations under step and sinusoidal inputs. To further evaluate the performance of the controller on a real vehicle, experiments on a real EPS system were implemented under step and sinusoidal inputs. The results of simulation and experiment using the controller based on estimated SAT showed this controller to be feasible and capable of eliminating the abrupt reaction torque increment caused by shutdown of EPS and of remedying the soft-disability of EPS system under common input signals.     

Integrated fuzzy/optimal vehicle dynamic control

There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers.     

Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Model Development, Validation and Comparison

Recent research on autonomous highway vehicles has begun to focus on lateral control strategies. The initial work has focused on vehicle control during low-g maneuvers at constant vehicle speed, typical of lane merging and normal highway driving. In this paper, and its companion paper, to follow, the lateral control of vehicles during high-g emergency maneuvers is addressed. Models of the vehicle dynamics are developed, showing the accuracy of the different models under low and high-g conditions. Specifically, body roll, tire and drive-train dynamics, tire force saturation, and tire side force lag are shown to be important effects to include in models for emergency maneuvers. Current controllers, designed for low-g maneuvers only, neglect these effects. The follow on paper demonstrates the performance of lateral controllers during high-g lateral emergency maneuvers using these vehicle models.     

Modelling and control of a new differential steering concept

This paper presents a new steer-by-wire concept using an all-wheel drive vehicle layout with in-wheel motors while completely omitting the application of any dedicated steering device. Steering is based on the so-called differential steering principle which generates the necessary steering moment about the kingpins by a traction force difference between left and right sides of the vehicle. In order to investigate the behaviour of the vehicle and to design the underlying control algorithms, a planar vehicle model is presented, where the vehicle is described as constrained non-holonomic system requiring a special treatment. A state feedback linear controller for controlling of the lateral dynamics of the vehicle at higher speeds and a simple PI angle controller for low-speed manoeuvring are developed. The resulting behaviour of the system is investigated by various simulation experiments demonstrating a comparable steering performance of the new steering concept as that of conventional passenger cars.     

Automated Emergency Four-Wheel-Steered Vehicle Using Continuous Gain Equations

Advanced Vehicle Control Systems (AVCS), when realized, should substantially increase the convenience and safety of highway travel. Automated lateral control is an important step in the realization of AVCS. Much research has been concerned with lateral control during low-g maneuvers. However, before passengers' lives are in the hands of any automated laterally-controlled vehicle, the vehicle controller must be designed to respond to emergency situations where high-g maneuvers may be necessary.

This paper presents the development of a nonlinear-gain-optimized (NGO) controller for emergency automated lateral control of four wheel steered automobiles. Continuous gain equations (GE) are used to account for changes in the vehicle speed. The NGO controller uses a linear vehicle/tire model to define the state model. The response of a nonlinear vehicle/tire model is used to choose the performance index that optimizes the feedback gains for high-g emergency maneuvers at discrete speeds. Continuous gain equations are then derived as least-square approximations to each set of gains.

The performance of the four-wheel-steer continuous gain equations (4WS-GE) controller is compared to that of a two-wheel-steer continuous gain equations (2WS-GE) controller. Significant improvements in vehicle response are realized by using the 4WS-GE controller. The robustness of the controller's performance is examined with respect to changes in tire parameters and changes in vehicle mass.     

Performance of Low-bandwidth,Semi-active Damping Concepts for Suspension Control

Abstract

Active damping has been shown to offer increased suspension performance in terms of vehicle isolation, suspension packaging, and road-tire contact force. It can even approximate the performance of full state feedback control without requiring the difficult measurement of tire deflection. Many semi-active damping strategies have been introduced to approximate the response of active damping with the modulation of passive damping parameters. These strategies have typically required a relatively high bandwidth for actuator response. This paper investigates the simulation performance and “frequency response” of two concepts in low-bandwidth semi-active suspension control, one that sets a damping force directly and another that sets the damping resistance. The electronically controlled bandwidth of these actuators is approximately an order of magnitude less than other semi-active devices; high frequency control is handled mechanically. A quarter-car model is studied with the controlled damping replacing both passive and active damping of typical control schemes. Both low-bandwidth damping strategies perform remarkably well compared to both active and high-bandwidth, semi-active damping. In certain dynamic performances, the new semi-active strategies outperform active damping and what the author calls “nominal” semi-active damping.