A passenger car driver model for higher lateral accelerations

Due to increasing demands for time and cost efficient vehicle and driver assistant systems development, numerical simulation of closed-loop manoeuvres becomes increasingly important. Thus, the driver has to be considered in the modelling. On the basis of a two-layer approach to model a driver's steering behaviour, the field of application is extended to higher lateral accelerations in this study. An analytical method to determine the driver parameters is presented, which is based on the two-wheel vehicle model. The simulation results are determined using a full vehicle model including all essential nonlinearities. Standard manoeuvres in the nonlinear range of vehicle handling behaviour are performed. A cornering manoeuvre is chosen to show the characteristics of the proposed driver model.     

Application of Elementary Neural Networks and Preview Sensors for Representing Driver Steering Control Behaviour

This paper demonstrates the use of elementary neural networks for modelling and representing driver steering behaviour in path regulation control tasks. Areas of application include uses by vehicle simulation experts who need to model and represent specific instances of driver steering control behaviour, potential on-board vehicle technologies aimed at representing and tracking driver steering control behaviour over time, and use by human factors specialists interested in representing or classifying specific families of driver steering behaviour. Example applications are shown for data obtained from a driver/vehicle numerical simulation, a basic driving simulator, and an experimental on-road test vehicle equipped with a camera and sensor processing system.     

Stability control of 4WS vehicles using robust IMC techniques

A robust nonparametric approach to vehicle stability control by means of a four-wheel steer by wire system is introduced. Both yaw rate and sideslip angle feedbacks are used in order to effectively take into account safety as well as handling performances. Reference courses for yaw rate and sideslip angle are computed on the basis of the vehicle speed and the handwheel angle imposed by the driver. An output multiplicative model set is used to describe the uncertainty arising from a wide range of vehicle operating situations. The effects of saturation of the control variables (i.e. front and rear steering angles) are taken into account by adopting enhanced internal model control methodologies in the design of the feedback controller. Actuator dynamics are considered in the controller design. Improvements on understeer characteristics, stability in demanding conditions such as turning on low friction surfaces, damping properties in impulsive manoeuvres, and improved handling in closed loop (i.e. with driver feedback) manoeuvres are shown through extensive simulation results performed on an accurate 14 degrees of freedom nonlinear model, which proved to give good modelling results as compared with collected experimental data.     

Dynamic stability of forklift trucks in cornering situations: parametrical analysis using a driving simulator

This paper describes the examination of the vehicle dynamics and stability of four-wheeled forklift trucks (FLTs) in cornering situations. Cornering at excessive speed is one major reason for fatal accidents with forklifts caused by lateral tipover. In order to increase the lateral stability of this kind of working machinery, the influence of certain important design properties has been studied using an appropriate vehicle simulation model and a driving simulator. The simulation model is based on a multi-body system approach and includes submodels for the propulsion system and the tyres. The driving behaviour of the operator has not been modelled. Instead, a driving simulator has been built up and a real human driver was employed for ensuring adequate and realistic model input. As there have not been any suitable standardised test manoeuvres available for FLTs, a new driving test has been developed to assess the lateral stability. This test resembles the well-known J turn/Fishhook turn, but includes a more dynamic counter-steering action. Furthermore, the dimensions of the test track are defined. Therefore, the test is better adapted to the driving dynamics of forklifts and reflects the real driver behaviour more closely. Finally, a parametrical study has been performed, examining the influence of certain important technical properties of the truck such as the maximum speed, the position of centre of gravity, rear axle design features and tyre properties. The results of this study may lead to a better understanding of the vehicle dynamics of forklifts and facilitate goal-oriented design improvements.     

Driver steering and muscle activity during a lane-change manoeuvre

The article reports an experimental study of driver steering control behaviour in a lane-change manoeuvre. Eight test subjects were instrumented with electromyography to measure muscle activation and co-contraction. Each subject completed 30 lane-change manoeuvres with one vehicle on a fixed-base driving simulator. For each driver, the steering torque feedback characteristic was changed after every ten manoeuvres; the response of the vehicle to steering angle inputs was not changed. Drivers' control strategies were found to be robust to changes in steering torque feedback. Path-following errors, muscle activity and muscle co-contraction all reduce with the number of lane-changes performed by the driver, suggesting the existence of a learning process. Comparing the test subjects, there was some evidence that high levels of co-contraction were used to allow high-frequency steering inputs to be generated. The results contribute to the understanding of vehicle–driver (and more generally, human–machine) dynamic interaction.     

Sensitivity of Driver-Vehicle Performance to Vehicle Characteristics Revealed in Open-loop Tests

The advantages of being able to objectively specify desirable vehicle handling characteristics, which can be determined without recourse to closed-loop tests on a prototype vehicle, are widely recognised. This paper reviews the studies that have attempted to find a relationship between closed-loop task performance, and driver subjective opinion, and various steady-state and transient characteristics revealed in open-loop tests of the vehicle. It is found that the level of definition of these relationships is not sufficient to justify mandatory regulations for vehicle design. However, the basic requirements for steering control sensitivity, and the rapidity and stability of the fixed-control dynamic response of vehicles in normal manoeuvres, are beginning to emerge. Data are particularly lacking for the closed-loop effects of vehicle sideslipping characteristics, free-control responses and vehicle behaviour in limit manoeuvres.     

A Mathematical Model for Driver Steering Control,with Design,Tuning and Performance Results

A mathematical model for the steering control of an automobile is described. The structure of the model derives from linear optimal discrete time preview control theory but it is non-linear. Its parameter values are obtained by heuristic methods, using insight gained from the linear optimal control theory. The driver model is joined to a vehicle dynamics model and the path tracking performance is demonstrated, using moderate manoeuvring and racing speeds. The model is shown to be capable of excellent path following and to be robust against changes in the vehicle dynamics. Application to the simulation of manoeuvres specified by an ideal vehicle path and further development of the model to formalise the derivation of its parameter values and to put it to other uses are discussed.     

A Mathematical Model for Driver Steering Control, with Design, Tuning and Performance Results

A mathematical model for the steering control of an automobile is described. The structure of the model derives from linear optimal discrete time preview control theory but it is non-linear. Its parameter values are obtained by heuristic methods, using insight gained from the linear optimal control theory. The driver model is joined to a vehicle dynamics model and the path tracking performance is demonstrated, using moderate manoeuvring and racing speeds. The model is shown to be capable of excellent path following and to be robust against changes in the vehicle dynamics. Application to the simulation of manoeuvres specified by an ideal vehicle path and further development of the model to formalise the derivation of its parameter values and to put it to other uses are discussed.     

Driver steering and muscle activity during a lane-change manoeuvre

The article reports an experimental study of driver steering control behaviour in a lane-change manoeuvre. Eight test subjects were instrumented with electromyography to measure muscle activation and co-contraction. Each subject completed 30 lane-change manoeuvres with one vehicle on a fixed-base driving simulator. For each driver, the steering torque feedback characteristic was changed after every ten manoeuvres; the response of the vehicle to steering angle inputs was not changed. Drivers' control strategies were found to be robust to changes in steering torque feedback. Path-following errors, muscle activity and muscle co-contraction all reduce with the number of lane-changes performed by the driver, suggesting the existence of a learning process. Comparing the test subjects, there was some evidence that high levels of co-contraction were used to allow high-frequency steering inputs to be generated. The results contribute to the understanding of vehicle-driver (and more generally, human-machine) dynamic interaction.     

Time-optimal control of the race car: a numerical method to emulate the ideal driver

A numerical method for the time-optimal control of the race car is presented. The method is then used to perform the role of the driver in numerical simulations of manoeuvres at the limit of race car performance. The method does not attempt to model the driver but rather replaces the driver with methods normally associated with numerical optimal control. The method simultaneously finds the optimal driven line and the driver control inputs (steer, throttle and brake) to drive this line in minimum time. In principle, the method is capable of operation with arbitrarily complex vehicle models as it requires only limited access to the vehicle model state vector. It also requires solution of the differential equation representing the vehicle model in only the forward time direction and is hence capable of simulating the full vehicle transient response.     

A General Method for the Evaluation of Vehicle Manoeuvrability with Special Emphasis on Motorcycles

This paper presents a novel approach to the assessment of the manoeuvrability of vehicles which is not based on the simulation of open-loop manoeuvres, nor does it rely on the modelling of the driver as a control system. Instead, the essence of the method is the solution of a two-point optimal control boundary value problem, in which a vehicle, subject to physical constraints like tyre adherence and road borders, among others, is required to go between given initial and final positions as fast as possible. The control inputs - i.e., the driver's actions - that make the vehicle move between the two states in the most efficient way are found as a part of the solution procedure and represent the actions of a sort of ideal, perfect driver. The resulting motion is called the optimal manoeuvre and, besides being the most efficient way that the given vehicle has for travelling between the two points according to the chosen optimal criterion, may be taken as a reference for meaningful comparisons with other vehicles. The value of the penalty function, used to define the optimal condition occurring at the optimal manoeuvre, may be taken as a measure of manoeuvrability or handling. With this approach the manoeuvrability properties are established as intrinsic to the vehicle, being defined with respect to an ideal perfect driver. Some possible forms of the penalty function, which means slightly different concepts of manoeuvrability and handling, are discussed. In the end, the case of motorcycles and some examples of optimal manoeuvres are given.     

A General Method for the Evaluation of Vehicle Manoeuvrability with Special Emphasis on Motorcycles

This paper presents a novel approach to the assessment of the manoeuvrability of vehicles which is not based on the simulation of open-loop manoeuvres, nor does it rely on the modelling of the driver as a control system. Instead, the essence of the method is the solution of a two-point optimal control boundary value problem, in which a vehicle, subject to physical constraints like tyre adherence and road borders, among others, is required to go between given initial and final positions as fast as possible. The control inputs - i.e., the driver's actions - that make the vehicle move between the two states in the most efficient way are found as a part of the solution procedure and represent the actions of a sort of ideal, perfect driver . The resulting motion is called the optimal manoeuvre and, besides being the most efficient way that the given vehicle has for travelling between the two points according to the chosen optimal criterion, may be taken as a reference for meaningful comparisons with other vehicles. The value of the penalty function, used to define the optimal condition occurring at the optimal manoeuvre, may be taken as a measure of manoeuvrability or handling. With this approach the manoeuvrability properties are established as intrinsic to the vehicle, being defined with respect to an ideal perfect driver. Some possible forms of the penalty function, which means slightly different concepts of manoeuvrability and handling, are discussed. In the end, the case of motorcycles and some examples of optimal manoeuvres are given.     

A novel integrated chassis controller for full drive-by-wire vehicles

In this paper, a systematic design with multiple hierarchical layers is adopted in the integrated chassis controller for full drive-by-wire vehicles. A reference model and the optimal preview acceleration driver model are utilised in the driver control layer to describe and realise the driver's anticipation of the vehicle's handling characteristics, respectively. Both the sliding mode control and terminal sliding mode control techniques are employed in the vehicle motion control (MC) layer to determine the MC efforts such that better tracking performance can be attained. In the tyre force allocation layer, a polygonal simplification method is proposed to deal with the constraints of the tyre adhesive limits efficiently and effectively, whereby the load transfer due to both roll and pitch is also taken into account which directly affects the constraints. By calculating the motor torque and steering angle of each wheel in the executive layer, the total workload of four wheels is minimised during normal driving, whereas the MC efforts are maximised in extreme handling conditions. The proposed controller is validated through simulation to improve vehicle stability and handling performance in both open- and closed-loop manoeuvres.     

Models and methodology for optimal trajectory generation in safety-critical road–vehicle manoeuvres

There is currently a strongly growing interest in obtaining optimal control solutions for vehicle manoeuvres, both in order to understand optimal vehicle behaviour and, perhaps more importantly, to devise improved safety systems, either by direct deployment of the solutions or by including mimicked driving techniques of professional drivers. However, it is non-trivial to find the right combination of models, optimisation criteria, and optimisation tools to get useful results for the above purposes. Here, a platform for investigation of these aspects is developed based on a state-of-the-art optimisation tool together with adoption of existing vehicle chassis and tyre models. A minimum-time optimisation criterion is chosen for the purpose of gaining an insight into at-the-limit manoeuvres, with the overall aim of finding improved fundamental principles for future active safety systems. The proposed method to trajectory generation is evaluated in time-manoeuvres using vehicle models established in the literature. We determine the optimal control solutions for three manoeuvres using tyre and chassis models of different complexities. The results are extensively analysed and discussed. Our main conclusion is that the tyre model has a fundamental influence on the resulting control inputs. Also, for some combinations of chassis and tyre models, inherently different behaviour is obtained. However, certain variables important in vehicle safety-systems, such as the yaw moment and the body-slip angle, are similar for several of the considered model configurations in aggressive manoeuvring situations.     

Process Save Reduction by Macro Joint Approach: The Key to Real Time and Efficient Vehicle Simulation

Applying a non-linear model reduction method to the tire suspension system of road vehicles enables an automatic transfer of complex offline simulation vehicle models to a mathematical model, which fits the real time simulation requirements. The basic assumption, that high frequent inner suspension dynamics are not relevant to handling manoeuvres, converts the differential algebraic equation system (DAE) of suspensions with kinematical closed loops into pure elasto-kinematical linkage equations. The equations of motions can be represented as an ordinary differential equation system (ODE) and considerable simulation time reductions are obtained for the off-line simulation and real time simulation is enabled. This so-called macro joint approach is an alternative modelling method to the well-known look-up table representation of suspension kinematics but it keeps the parameterisation of the original suspension model and is suitable to parameterised real time MBS models. With a second step the dynamics, caused by compliance in the suspension bushings, are reduced to their quasi-static behaviour. The consideration of these quasi-elasticity has nearly no influence on the necessary simulation time. This contribution shows the theoretical background and demonstrates the advantage of the macro joint model reduction approach on a typical vehicle example.     

Process Save Reduction by Macro Joint Approach: The Key to Real Time and Efficient Vehicle Simulation

Applying a non-linear model reduction method to the tire suspension system of road vehicles enables an automatic transfer of complex offline simulation vehicle models to a mathematical model, which fits the real time simulation requirements. The basic assumption, that high frequent inner suspension dynamics are not relevant to handling manoeuvres, converts the differential algebraic equation system (DAE) of suspensions with kinematical closed loops into pure elasto-kinematical linkage equations. The equations of motions can be represented as an ordinary differential equation system (ODE) and considerable simulation time reductions are obtained for the off-line simulation and real time simulation is enabled. This so-called macro joint approach is an alternative modelling method to the well-known look-up table representation of suspension kinematics but it keeps the parameterisation of the original suspension model and is suitable to parameterised real time MBS models. With a second step the dynamics, caused by compliance in the suspension bushings, are reduced to their quasi-static behaviour. The consideration of these quasi-elasticity has nearly no influence on the necessary simulation time. This contribution shows the theoretical background and demonstrates the advantage of the macro joint model reduction approach on a typical vehicle example.     

An adaptive lateral preview driver model

Successful modelling and simulation of driver behaviour is important for the current industrial thrust of computer-based vehicle development. The main contribution of this paper is the development of an adaptive lateral preview human driver model. This driver model template has a few parameters that can be adjusted to simulate steering actions of human drivers with different driving styles. In other words, this model template can be used in the design process of vehicles and active safety systems to assess their performance under average drivers as well as atypical drivers. We assume that the drivers, regardless of their style, have driven the vehicle long enough to establish an accurate internal model of the vehicle. The proposed driver model is developed using the adaptive predictive control (APC) framework. Three key features are included in the APC framework: use of preview information, internal model identification and weight adjustment to simulate different driving styles. The driver uses predicted vehicle information in a future window to determine the optimal steering action. A tunable parameter is defined to assign relative importance of lateral displacement and yaw error in the cost function to be optimized. The model is tuned to fit three representative drivers obtained from driving simulator data taken from 22 human drivers.     

Brain limbic system-based intelligent controller application to lane change manoeuvre

This paper presents the application of a novel neuromorphic control strategy for lane change manoeuvres in the highway environment. The lateral dynamics of a vehicle with and without wind disturbance are derived and utilised to implement a control strategy based on the brain limbic system. To show the robustness of the proposed controller, several disturbance conditions including wind, uncertainty in the cornering stiffness, and changes in the vehicle mass are investigated. To demonstrate the performance of the suggested strategy, simulation results of the proposed method are compared with the human driver model-based control scheme, which has been discussed in the literature. The simulation results demonstrate the superiority of the proposed controller in energy efficiency, driving comfort, and robustness.     

Driver models for personalised driving assistance

We propose a learning-based driver modelling approach which can identify manoeuvres performed by drivers on the highway and predict the future driver inputs. We show how this approach can be applied to provide personalised driving assistance. In a first example, the driver model is used to predict unintentional lane departures and a model predictive controller is used to keep the car in the lane. In a second example, the driver model estimates the preferred acceleration of the driver during lane keeping, and a model predictive controller is implemented to provide a personalised adaptive cruise control. For both applications, we use a combination of real data and simulation to evaluate the proposed approaches.     

Modelling of a driver's behaviour considering roll motion

This paper presents an anlysis of the control behaviour of a driver during curves and lane changes. We model the driver's behaviour taking the roll motion of the vehicle into consideration. Using this model with constraints on the roll angle, it is possible to model lane change maneuvers without specifying a path. The validity of the model is investigated through a comparison between computer simulation and experimentation using a driving simulator system.