# Research on Control of Intelligent Vehicle Human-Simulated Steering System Based on HSIC
## 1 Introduction  
The intellectualization of automobiles is reflected in replacing manual operation with automatic driving. The controllable and predictable behavior and driving state of automobiles can not only make up for the deficiency of human sensory ability, but also reduce the disutility of driving and eliminate traffic accidents caused by human factors. Consequently, \"zero casualty and zero congestion\" of traffic can be realized based on the travel path planned according to the real-time traffic information. Therefore, the next generation of intelligent automobiles is safe, efficient, and energy efficient [1; 2]. It is of great significance to study intelligent vehicles, which have become the focus of attention in the global automotive industry. The automatic driving control technology of intelligent vehicle faces many difficulties in substituting human drivers completely within all conditions range and being accepted byconsumers [3; 4]. For an intelligent vehicle, when it only controls the steering wheel angle according to the signal of the Electric Power Steering (EPS) angle sensor, it does not control the EPS. When the output torque of the motor is invariant, the steering wheel angle or the rotation speed fluctuates, resulting in steering wheel jitter. If the damping of the EPS motor (reverse torque) is not controlled during the steering process of the large angle working condition, the steering wheel will be returned rapidly, causing a large yaw rate of the vehicle body. As a result, the steering quality of the intelligent vehicle will be deteriorated. There is even instability at high speed, which jeopardizes the safety of driving. Therefore, it is necessary to simulate the driving behavior of the real driver. Meanwhile, an intelligent control algorithm with a higher degree of intelligence is applied to the intelligent driving vehicle, it will lead the driving level of the intelligent vehicle is as close as possible to the handling quality of the human driver. In the research process of intelligent vehicle steering control, the classical control theory has been widely used in the 1980s. [PERSON] used the P controller in the design process of the intelligent vehicle control system [5]. Recent studies have shown that the classic PID control algorithm has certain limitations. For example, the parameters need to be artificially set, and cannot be adaptively adjusted according to different driving conditions. Therefore, the control accuracy can hardly be guaranteed [6]. According to the anti-step sliding mode theory, [PERSON] et al. designed a control algorithm for the coordinated vertical and horizontal motions of intelligent vehicles and verified the consistent and bounded convergence of tracking errors through the Lyapunov function [7]. Based on the strong coupling, nonlinearity, and parameter uncertainty of intelligent vehicles, [PERSON] and [PERSON] proposed a collaborative control strategy with hierarchical structure [8]. [PERSON] and [PERSON] established a lateral path tracking control system for intelligent vehicles. The control system mainly designed the corresponding feedback control logic based on the heading deviation [9]. According to the analysis, the above references cannot simulate the driving behavior of real drivers. [PERSON] et al., established an overtaking system for an automated vehicle equipped with path tracking and lane change functions, so that human behavior and response during overtaking can be stimulated through fuzzy controllers [10]. However, the above method only controls the steering wheel angle and does not consider the torque of the steering wheel, it leads fluctuate inevitably for the steering wheel angle or the rotation speed, thereby, steering wheel occurs shake. Human simulated intelligent control (HSIC) is a logic-based intelligent control algorithm. The main goal of HSIC is not the controlled object, but how the controller itself simulates the behavior of the expert.