This unique edited collection derives from an international workshop uniting experts from the transport industry, legislators and research workers. The text focuses on issues from fatigue and their impact on performance and safety. Fatigue and Driving provides an overview of the individual and organisational perspectives of the problem including its many causes and consequences. Transport drivers describe their real-life experience of fatigue and how they identify and manage it; transport managers discuss the demands and constraints on their industry; researchers discuss their current research methodologies and the use of driving simulators.

This study proposes a method based on Dempster-Shafer theory (DST) and fuzzy neural network (FNN) to improve the reliability of recognizing fatigue driving. This method measures driving states using multifeature fusion. First, FNN is introduced to obtaint he basic probability assignment (BPA) of each piece of evidence given the lack of a general solution to the definition of BPA function. Second, a modified algorithm that revises conflict evidence is proposed to reduce unreasonable fusion results when unreliable information exists.

Elisabeth Schmidt investigates the effect of thermal stimulation during passive driver fatigue in a series of driving simulator experiments. Thermal stimulation of the upper body resulted in significantly decreased subjective fatigue ratings as well as an increase in pupil diameter and skin conductance. The effects of different stimulus temperatures, durations, lower leg cooling and repetitive cooling were also examined. The studies show that thermal stimulation of the upper body causes physiological and subjective effects, which can be associated with a short-term sympathetic activation, whereas lower leg cooling does not cause physiological activation.

Thanks to advances in computer technology in the last twenty years, navigation system, cabin environment control, ACC, advanced driver assistance system (ADAS) and automated driving have become a part of the automobile experience. Improvement in technology enables us to design these with greater flexibility and provide greater value to the driver (human centered design). To achieve this, research is required by laboratories, automobile and auto parts manufacturers. Although there has been a lot of effort in human factors research and development, starting from basic research to product development, the knowledge and experience has not been integrated optimally. The aim of this book is to collect and review the information for researchers, designers and developers to learn and apply them for further research and development of human centered design of future automotive technologies. Automotive human factors include psychological, physiological, mathematical, engineering and even sociological aspects. This book offers valuable insights to applying the right approach in the right place.

This book contains selected papers resulting from the 2020 International Conference on Road and Traffic Engineering (CRTE 2020) covering Road Engineering and Traffic Engineering, aiming to provide an academic and technical communication platform for scholars and engineers engaged in scientific research and engineering practice in the field of Road Engineering and Materials, Traffic Engineering and Management and Transportation Engineering. By sharing the research status of scientific research achievements and cutting-edge technologies, it helps scholars and engineers all over the world to comprehend the academic development trends and broaden research ideas. So as to strengthen international academic research, academic topics exchange and discussion, and promote the industrialization cooperation of academic achievements.

These proceedings collect selected papers from the 8th International Conference on Green Intelligent Transportation Systems and Safety held in Changchun on July 1-2, 2017. The selected works, which include state-of-the-art studies, are intended to promote the development of green mobility and intelligent transportation technology to achieve interconnectivity, resource sharing, flexibility and higher efficiency. They offer valuable insights for researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and Systems Engineering, and Electrical Engineering.

This Proceedings volume gathers outstanding papers submitted to the 19th Asia Pacific Automotive Engineering Conference & 2017 SAE-China Congress, the majority of which are from China – the largest car-maker as well as most dynamic car market in the world. The book covers a wide range of automotive topics, presenting the latest technical advances and approaches to help technicians solve the practical problems that most affect their daily work.

Brain imaging has been successfully used to generate image-based biomarkers for various neurological and psychiatric disorders, such as Alzheimer’s and related dementias, Parkinson’s disease, stroke, traumatic brain injury, brain tumors, depression, schizophrenia, etc. However, accurate brain image-based diagnosis at the individual level remains elusive, and this applies to the diagnosis of neuropathological diseases as well as clinical syndromes. In recent years, deep learning techniques, due to their ability to learn complex patterns from large amounts of data, have had remarkable success in various fields, such as computer vision and natural language processing. Applying deep learning methods to brain imaging-assisted diagnosis, while promising, is facing challenges such as insufficiently labeled data, difficulty in interpreting diagnosis results, variations in data acquisition in multi-site projects, integration of multimodal data, clinical heterogeneity, etc. The goal of this research topic is to gather cutting-edge research that showcases the application of deep learning methods in brain imaging for the diagnosis of neurological and psychiatric disorders. We encourage submissions that demonstrate novel approaches to overcome various abovementioned difficulties and achieve more accurate, reliable, generalizable, and interpretable diagnosis of neurological and psychiatric disorders in this field.

This conference proceeding is a collection of the papers accepted by the CENet2021 – the 11th International Conference on Computer Engineering and Networks held on October 21-25, 2021 in Hechi, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.