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This paper presents a tire slip-angle based speed control race driver model. In developing a chassis control system for enhancement of high-speed driving performance, analysis of the vehicle-driver interaction at limit handling is one of the main research issues. Thus, a driver model which represents driving characteristics in a racing situation is required to develop a chassis control system. Since a race driver drives a vehicle as fast as possible on a given racing line without losing control, the proposed driver model is developed to ensure a lateral stability. In racing situation, one of the reasons which cause the lateral instabilities is an excessive corner-entry speed. The lateral instability in that moment is hard to handle with only a steering control. To guarantee the lateral stability of the vehicle while maximizing a cornering speed, a desired speed is determined to retain a tire slip-angle that maximizes lateral tire forces without front tire saturation.

The performance of an integrated Vehicle Stability Control (VSC) system depends on not only control logic itself, but also the performance of state estimator and control threshold. In conventional VSCs, a control threshold is designed by vehicle characteristics and is centered on average drivers. A VSC algorithm with variable control threshold has been investigated in this study. The control threshold can be determined by phase plane analysis of side slip angle and angular velocity. Vehicle side slip angle estimator has been evaluated using test data. Estimated side slip angle has been used in the determination of the control threshold. The performance of the proposed VSC algorithm has been investigated by human-in-the-loop simulation using a vehicle simulator. The simulation results show that the control threshold has to be determined with respect to the driver steering characteristics.

A throttle/brake control law for the intelligent cruise control (ICC) system has been proposed in this paper. The ICC system consists of a vehicle detection sensor, a controller and throttle/brake actuators. For the control of a throttle/brake system, we introduced a solenoid-valve-controlled electronic vacuum booster (EVB) and a step-motor-controlled throttle actuator. Nonlinear computer model for the electronic vacuum booster has been developed and the simulations were performed using a complete nonlinear vehicle model. The proposed control law in this paper consists of an algorithm that generates the desired acceleration/deceleration profile in an ICC situation, a throttle/brake switching logic and a throttle and brake control algorithm based on vehicle dynamics. The control performance has been investigated through computer simulations and experiments.

This paper describes an investigation into multi-core processing architecture for implementation of a Unified Chassis Control (UCC) algorithm. The multi-core architecture is suggested to reduce the operating load and maximization of the reliability to improve of the UCC system performance. For the purpose of this study, the proposed multi-core architecture supports distributed control with analytical and physical redundancy capabilities. In this paper, the UCC algorithm embedded in electronic control unit (ECU) is comprised of three parts; a supervisor, a main controller, and fault detection/ isolation/ tolerance control (FDI/FTC). An ECU is configured by three processors, and a control area network (CAN) is also implemented for hardware-in-the-loop (HILS) evaluation. Two types of multi-core architectures such as distributed processing, and triple voting are implemented to investigate the performance and reliability.

This paper presents a Unified Chassis Control (UCC) strategy to improve vehicle stability and maneuverability by integrating Electronic Stability Control (ESC) and Active Front Steering (AFS). The UCC architecture consists of two parts: an estimator and a controller. The estimator is designed to estimate longitudinal and lateral tire forces and the controller is designed in two stages, namely, an upper level controller and a lower level controller. The upper level controller, provides the desired yaw moment for vehicle lateral stability by adopting a sliding control method. The lower level controller, provides the integration method of the AFS and ESC strategies for the desired yaw moment and is designed by optimal tire force coordination.

This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) systems using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator which consists of a three-dimensional vehicle dynamic model, interface between human driver and vehicle simulator, three-dimensional animation program and a visual display has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

This paper presents a methodology of trajectory planning for the surrounding-aware lane change maneuver of autonomous vehicles based on a data-driven method. The lateral motion is planned by sampling candidate patterns which are defined based on quintic polynomial functions over time. Based on the cost evaluation among the sampled candidates, the optimal lateral motion pattern is selected as a reference and tracked by the controller. The longitudinal motion is planned and controlled using Model Predictive Control (MPC) which is an optimal control method designed considering the surrounding traffic information. To realize the lane change motion similar to the human driving behavior in the surrounding traffic situation, the human driving pattern is modeled in the form of motion parameters and considered in planning the lateral and longitudinal motion.

This paper presents the design and evaluation of an emergency driving support (EDS) algorithm. The control objective is to assist driver's collision avoidance maneuver to overcome a hazardous situation. To support driver, electrically controllable chassis components such as motor driven power steering (MDPS) and differential braking and surrounding sensor systems such as radar and camera are used. The EDS algorithm is designed for 3 parts: monitoring, decision, and control. The proposed EDS algorithm recognizes a collision danger using minimum lateral acceleration to avoid collision and time-to-collision (TTC) and driver's intention using sensor systems. The control mode is determined using the indices from monitoring process and the collision avoidance trajectory is derived with trapezoidal acceleration profile (TAP).

A methodology to design a model free cruise control algorithm(MFCC) is presented in this paper. General cruise control algorithms require lots of vehicle parameters to control the power train and the brake system, that makes control system complicate. Moreover, when the target vehicle is changed, the vehicle parameters should be reinvestigated in order to apply the cruise control algorithm to the subject vehicle. To overcome these disadvantages of the conventional cruise control algorithm, MFCC algorithm has been developed. The algorithm directly determines the throttle, brake inputs based on the reference model parameters such as clearance, relative velocity, and subject vehicle acceleration. This simple structure facilitates human centered design of cruise controller and makes it easy to apply control algorithm to various vehicles without reinvestigation of vehicle parameters.

This paper describes a driving controller to improve vehicle lateral stability and maneuverability for a six wheel driving / six wheel steering (6WD/6WS) vehicle. The driving controller consists of upper and lower level controller. The upper level controller based on sliding control theory determines front, middle steering angle, additional net yaw moment and longitudinal net force according to reference velocity and steering of a manual driving, remote control and autonomous controller. The lower level controller takes desired longitudinal net force, yaw moment and tire force information as an input and determines additional front steering angle and distributed longitudinal tire force on each wheel. This controller is based on optimal distribution control and has considered the friction circle related to vertical tire force and friction coefficient acting on the road and tire.

This paper presents the integrated chassis control(ICC) of four-wheel drive(4WD), electronic stability control(ESC), electronic control suspension(ECS), and active roll stabilizer(ARS) for limit handling. The ICC consists of three layers: 1) a supervisor determines target vehicle states; 2) upper level controller calculates generalized forces; 3) lower level controller, which is contributed in this paper, optimally allocates the generalized force to chassis modules. The lower level controller consists of two integrated parts, 1) longitudinal force control part (4WD/ESC) and 2) vertical force control part (ECS/ARS). The principal concept of both algorithms is optimally utilizing the capability of the each tire by monitoring tire saturation, with tire combined slip. By monitoring tire saturation, 4WD/ESC integrated system minimizes the sum of the tire saturation, and ECS/ARS integrated system minimizes the variance of the tire saturation.

This paper presents a 3D dynamic simulation model of a wheel loader. The objective of development of the wheel loader dynamic simulation model is to investigate power flow under both working and driving conditions. The wheel loader dynamic simulation model consists of 3 parts: Vehicle mechanical powertrain module, Hydraulic modules for working and steering, and Vehicle dynamic module. Vehicle powertrain module consists of engine, torque converter and transmission. Hydraulic modules consist of pump, valve, cylinder and attachments. In this paper, hydraulic powertrain is managed only for steering system because this paper has been focused on dynamic analysis of mechanical powertrain and vehicle. Front and rear bodies are connected by pin in the center of steering system. Action/reaction forces and moments applied to the pin are calculated by solving front/rear dynamic simultaneous equations.

This paper describes a lane departure avoidance system to help the driver avoid the lane departure during drowsiness or inattention. The lane departure avoidance system proposed in this paper consists of unintended lane departure decision part, upper level controller part and lower level controller part. The index used in unintended lane departure decision part is proposed to monitor a driver's intention with steering behaviors. The desired dynamics is calculated in upper level controller part. When the desired dynamics is calculated, it is considered to guarantee a driver's safety and smooth ride feel simultaneously as possible. The lower level controller distributes the desired control input to actuators, motor driven power steering (MDPS) module and vehicle stability control (VSC) module. The proposed lane departure avoidance system has been evaluated via human driver model-in the loop simulation.

This paper describes development and performance verification of a driving control algorithm for a 6 wheel driving and 6 wheel steering (6WD/6WS) vehicle using a real-time simulator. This control algorithm is developed to improve vehicle stability and maneuverability under high speed driving conditions. The driving controller consists of stability decision, upper, lower level and wheel slip controller. The stability decision algorithm determines desired longitudinal acceleration and reference yaw rate in order to maintain lateral and roll stability using G-vectoring method. Upper level controller is designed to obtain reference longitudinal net force, yaw moment and front/middle steering angles. The longitudinal net force is calculated to satisfy the reference longitudinal acceleration by the PID control theory. The reference yaw moment is determined to satisfy the reference yaw rate using sliding control theory. Lower level controller determines distributed tractive/braking torques.

This paper describes a driving motor torque distribution strategy of six-wheel-driven electric vehicles for optimized energy consumption. In this research, this strategy minimizes motoring power consumption and maximizes regenerative braking power under given required power condition. The torque distribution controller consists of total required motor torque calculation part, upper and optimal torque calculation part, lower level controller. The upper level controller determines total required torque of vehicle. And the torque is determined by acceleration pedal input of driver and vehicle velocity. The lower level controller calculates energy consumption in given condition and distributes motor torque to driving motor minimizing energy consumption. In distributing optimal motor torque, it is important to get accurate characteristics of driving motor and performance constraint.

This paper presents an Interacting Multiple Model (IMM) based side slip angle estimation method to estimate side slip angle under various road conditions for vehicle stability control. Knowledge of the side slip angle is essential enhancing vehicle handling and stability. For the estimation of the side slip angles in previous researches, prior knowledge of tire parameters and road conditions have been employed, and sometimes additional sensors have been needed. These prior knowledge and additional sensors, however, necessitates many efforts and make an application of the estimation algorithm difficult. In this paper, side slip angle has been estimated using on-board vehicle sensors such as yaw rate and lateral acceleration sensors. The proposed estimation algorithm integrates the estimates from multiple Kalman filters based on the multiple models with different parameter set.

This paper describes an Integrated Chassis Control (ICC) strategy for improving high speed cornering performance by integration of Electronics Stability Control (ESC), Four Wheel Drive (4WD), and Active Roll Control System (ARS). In this study, an analysis of various chassis modules was conducted to prove the control strategies at the limits of handling. The analysis is focused to maximize the longitudinal velocity for minimum lap time and ensure the vehicle lateral stability in cornering. The proposed Integrated Chassis Control algorithm consists of a supervisor, vehicle motion control algorithms, and a coordinator. The supervisor monitors the vehicle status and determines desired vehicle motions such as a desired yaw rate, longitudinal acceleration and desired roll motion. The target longitudinal acceleration is determined based on the driver's intention and vehicle current state to ensure the vehicle lateral stability in high speed maneuvering.

This paper presents an integrated chassis control method for vehicle stability under various road friction conditions without information on tire-road friction. For vehicle stability, vehicle with an integrated chassis control needs to cope with the various road friction conditions. One of the chassis control method under various road conditions is to determine and/or limit control inputs based on tire-road friction coefficient. The tire-road friction coefficient, however, is difficult to estimate and still a challenging task. The key idea for the proposed method without the estimation of the tire-road friction coefficient is to analyze and control vehicle states based on a tire slip angle - tire force phase plane, i.e. based on these vehicle responses: tire forces and tire slip angles of front/rear wheels.

This paper presents an integrated control of in-wheel motor (IWM) and electronic limited slip differential (eLSD) to enhance the vehicle lateral stability and maneuverability. The two actuators are utilized in the proposed controller to achieve separate purposes. The IWM controller is designed to modify the understeer gradient for enhanced handling characteristic and maneuverability. The eLSD controller is devised to improve the lateral stability to prevent oversteer in a severe maneuver. The proposed controller consists of a supervisor, upper-level controller and lower-level controller. The supervisor determines a target motion based on a target understeer gradient for IWM control and a yaw rate reference for eLSD control. The upper-level controller generates a desired yaw moment for the target motion. In the lower-level controller, the desired yaw moment is converted to the control inputs for IWMs in the two front wheels and eLSD at the rear axle.

This paper proposes a rear-wheel steering control method that can modify and improve the vehicle lateral response without tire model and parameter. The proposed control algorithm is a combination of steady-state and transient control. The steady state control input is designed to modify steady-state yaw rate response of the vehicle, i.e. understeer gradient of the vehicle. The transient control input is a feedback control to improve the transient response when the vehicle lateral behavior builds up. The control algorithm has been investigated via computer simulations. Compared to classical control methods, the proposed algorithm shows good vehicle lateral response such as small overshoot and fast response. Specifically, the proposed algorithm can alleviate stair-shaped response of the lateral acceleration.