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This paper describes an automatic steering controller based on a target and control driver steering model. With the road information provided by the image sensor, the structure revealed that drivers apply a PID-type controller whose look-ahead distances and feedback gains are dependent on the vehicle speed. With these simple gains, the vehicle can perform very well in vehicle lateral dynamics control. Instead of planning and following a desired path according to the traditional trajectory planning concept, drivers use the next lane center as the target points to generate vehicle angle error for steering control. This novel target and control driver model captures driver’s key steering mechanisms. The automatic steering controller was first simulated under the Model-in-the-Loop (MIL) test using the CarSim simulation. The simulation results indicate that lateral offsets are smaller than those from typical driver models.

A model-based sensor fault detection algorithm is proposed in this paper to detect and isolate the faulty sensor. Wheel speeds are validated using the wheel speed deviations before being employed to check the sensor measurements of the vehicle dynamics. Kinematic models are employed to estimate yaw rate, lateral acceleration, and steering wheel angle. A Kalman filter based on a point mass model is employed to estimate longitudinal speed and acceleration. The estimated vehicle dynamics and sensor measurements are used to calculate the residuals. Adaptive threshold values are employed to identify the abnormal increments of residuals. Recursive least square method is used to design the coefficients of the expressions for adaptive threshold values, such that the false alarms caused by model uncertainties can be prevented. Different combinations of estimations are employed to obtain 18 residuals.

Autonomous emergency braking (AEB) systems is one of the functions of the Advanced Driver Assists System to avoid or mitigate vehicle frontal collisions. Most of the previous studies focus on two-car scenario where the host vehicle monitors the distances to the vehicles in front, and automatically applies emergency brake when a collision is imminent. The purpose of this paper is to develop an Advanced-AEB control system that mitigates collisions in a multi-car scenario by measuring the distances to the vehicles in front as well as those to the vehicles behind using the concept of impedance control. A simple gain-scheduling PI controller was designed for the host vehicle to track the reference inputs generated by the impedance control. The preliminary simulation results demonstrate that the proposed AEB is effective in mitigating the collisions in a 3-car following scenario.

This paper presents the design and implementation of a new steering control method for lane following control (LFC) using a camera. With the road information provided by the image sensor, the LFC system calculates the steering command based on the Target and Control (T&C) driver steering model. The T&C driver model employs a look-ahead control structure to capture the drivers’ core steering mechanism. Based on the models of the steering actuator and the vehicle dynamics, optimal control gains can be determined for any given look-ahead distance (normalized by the vehicle speed). With these simple gains, the vehicle can track very well along the center of the lane. This LFC system was first simulated under the Model-in-the-Loop (MiL) test using the CarSim simulation. The simulations show that the resultant lateral offsets are smaller than those from typical driver models.