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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 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 represents a parking lot occupancy detection and parking control algorithm for the autonomous valet parking system. The parking lot occupancy detection algorithm determine the occupancy of the parking space, using LiDAR sensors mounted at each side of front bumper. Euclidean minimum spanning tree (EMST) method is used to cluster that information. After that, a global parking map, which includes all parking lots and access road, is constructed offline to figure out which cluster is located in a parking space. By doing this, searching for available parking lots has been finished. The proposed parking control algorithm consists of a reference path generation, a path tracking controller, and a parking process controller. At first, route points of the reference path are determined under the consideration of the minimum turning radius and minimum safety margin with near parking.

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 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 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 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 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.

This paper describes a driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consists of four parts; speed controller for tracking of the desired speeds, yaw rate controller which computes a yaw moment input to track desired yaw rates, longitudinal tire force distribution which determines an optimal desired longitudinal tire force and wheel torque controller which determines a wheel torque command at each wheel to keep slip ratio at each wheel below a limit value as well as track the desired tire force. Longitudinal and vertical tire force estimators are designed for optimal tire force distribution and wheel slip control. The dynamic model of RVAS for simulation study is validated using vehicle test data.

This paper presents a stability monitoring algorithm with a combined slip tire model for maximized cornering speed of high-speed autonomous driving. It is crucial to utilize the maximum tire force with maintaining a grip driving condition in cornering situations. The model-free cruise controller has been designed to track the desired acceleration. The lateral motion has been regulated by the sliding mode controller formulated with the center of percussion. The controllers are suitable for minimizing the behavior errors. However, the high-level algorithm is necessary to check whether the intended motion is inside of the limit boundaries. In extreme diving conditions, the maximum tire force is limited by physical constraints. A combined slip tire model has been applied to monitor vehicle stability. In previous studies, vehicle stability was evaluated only by vehicle acceleration.

This paper is concerned with the torque distribution problem including slip limitation and actuator fault tolerance to improve vehicle lateral stability and maneuverability of six-wheeled skid-steered vehicles. The torque distribution algorithm to distribute wheel torque to each wheel of a skid-steered vehicle consists of an upper level control layer, a lower level control layer and an estimation layer. The upper level control layer is designed to obtain longitudinal net force and desired yaw moment, while the lower level control layer determines distributed driving and braking torques to six wheels. The algorithm takes vehicle speed, slip ratio and tire load information from the estimation layer, as well as actuator fault information from each in-wheel motor controller unit.