In this research, brief survey of literature on current developments in the field of lateral and longitudinal control of autonomous vehicle motions. The paper categorizes the motions of vehicle to: car following, lane keeping, lane changing, subsequently, longitudinal control (brake and throttle), lateral control (steering) and integration of these controls for autonomous vehicles was investigated. Also different equipment and approaches to control of motions in each field was proposed.

A historical review on lateral and longitudinal control of autonomous vehicle motions

Rear-end collision is a very serious problem in modern traffic situations, and there have been a great number of research reports on the longitudinal control method for road vehicles. In many cases, however, the control problem is formulated under platoon configuration and for some predictable noncollision situations. For predictable collision situations, regional and hierarchical approaches have been employed, but these approaches render difficulties due to ignorance for modeling error and logical error in a decision process. In this paper, the vehicle control for collision avoidance is studied with two control objectives, i.e., minimization of the safety distance error and regulation of the relative velocity between two vehicles. For this, a longitudinal controller using terminal sliding mode (TSM) with hierarchical structure is proposed for rear-end collision avoidance. The TSM is employed to achieve convergence in finite time, while the hierarchical approach is used for the system to accommodate the intelligence of the driver to handle various situations. The effectiveness of the proposed control scheme is verified by software simulations

Hierarchical Longitudinal Controller for Rear-End Collision Avoidance

In marketing research, one of the most exciting, innovative, and promising trends is quantification of customer interest. This paper presents a deep learning-based system for monitoring customer behavior specifically for detection of interest. The proposed system first measures customer attention through head pose estimation. For those customers whose heads are oriented toward the advertisement or the product of interest, the system further analyzes the facial expressions and reports customers’ interest. The proposed system starts by detecting frontal face poses; facial components important for facial expression recognition are then segmented and an iconized face image is generated; finally, facial expressions are analyzed using the confidence values of obtained iconized face image combined with the raw facial images. This approach fuses local part-based features with holistic facial information for robust facial expression recognition. With the proposed processing pipeline, using a basic imaging device, such as a webcam, head pose estimation, and facial expression recognition is possible. The proposed pipeline can be used to monitor emotional response of focus groups to various ideas, pictures, sounds, words, and other stimuli.

Deep learning-based face analysis system for monitoring customer interest

Vehicle collision avoidance system is a kind of auxiliary driving system based on vehicle active safety, which can assist the driver to take the initiative to avoid obstacles under certain conditions, so as to effectively improve the driving safety of vehicle. This paper presents a collision avoidance system for an autonomous vehicle based on an active front steering, which mainly consists of a path planner and a robust tracking controller. A path planner is designed based on polynomial parameterization optimized by simulated annealing algorithm, which plans an evasive trajectory to bypass the obstacle and avoid crashes. The dynamic models of the AFS system, vehicle as well as the driver model are established, and based on these, a robust tracking controller is proposed, which controls the system to resist external disturbances and work in accordance with the planning trajectory. The proposed collision avoidance system is testified through CarSim and Simulink combined simulation platform. The simulation results show that it can effectively track the planning trajectory, and improve the steering stability and anti-interference performance of the vehicle.

Path planning and stability control of collision avoidance system based on active front steering

A comprehensive review of technologies and approaches for active safety systems designed to reduce ground vehicle crashes, as well as the associated severity of injuries and fatalities, is provided...

A review of vehicle active safety control methods: From antilock brakes to semiautonomy:

This paper suggests a novel technology that can clone a user's facial expression to his avatar in 3D virtual worlds realistically using only one color camera on a smart TV. To do this, the user's 3D head movement information and 3D position of facial feature points are needed in real time. We propose two novel approaches to achieve this. Firstly, we use a personalized 3D and 2D facial expression model to deal with head movement and various expressions. Secondly, we use a facial muscle model to generate natural motion of facial feature points located in cheeks and forehead which are difficult to be tracked using a camera. Experimental results demonstrate that the proposed method would be an efficient technique to perform realistic 3D facial expression cloning.

Real-time realistic 3D facial expression cloning for smart TV

A high quality deflection yoke (DY) is an essential factor for a high quality monitor. Currently, the DY adjustment process is done manually by attaching ferrite sheets on the inside surface of the DY. In this paper, we deal with the convergence adjustment algorithms employed in the guidance system. An inference engine that is based on soft computing techniques is proposed to systematically deal with several resources including the expert's knowledge in the convergence adjustment process of the DY. In our approach, the rough set theory is used to handle the input/output data collections of the DY adjustment, and the fuzzy logic and evolutionary programming are used to model the plant and to tune the model. With the given initial convergence, a rough set driven coarse search part finds a coarse area and then more precise positions are searched and decided in the fuzzy inference engine driven fine search part. Initial experimental results show that the proposed algorithm works well in the real convergence adjustment process of the DY.

Joo-Han Kim

Papers

Real-time realistic 3D facial expression cloning for smart TV

Convergence adjustment of deflection yoke using soft computing techniques

A study on active collision avoidance system for the road vehicle

Fuzzy Logic Controller Design for Lateral Vehicle Guidance