Due to the progress in VLSI technology, integrated circuit chips are now available that allow video/image signal processing to be performed with a single VLSI chip or small sets of VLSI chips. Recent standardization on bandwidth compression schemes for still images (JPEG) and motion pictures (H.261, R723, MPEG) also encourage the development of VLSI video/image processors for cost-effective solutions. Furthermore, recent trends suggest that the standardization on HDTB bandwidth compression for broadcasting and storage purposes is just around the corner. In terms of device technology, however, the progress achieved in increasing speed is not as high as that achieved by integration. The development of high speed systems is due to architectural effort, rather than device technology. This is why high speed architectures, such as those for special wired logic realization and for multi-processors are of great interest to VLSI system designers. VLSI Video/Image Signal Processing is an edited volume of original research comprising invited contributions by leading researchers.

This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios. Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios. The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.