Contains 51 papers covering eight years of research on object detection, collision warning, and collision avoidance. Topics covered include: Parking aids; Target tracking with cameras; Sensor combinations; Blind spot detection; Imager chips; Lane tracking; Lane and road departure warning; Sensor fusion; Intersection collision warning; Front- and rear-end crash avoidance; Automatic collision avoidance systems; Braking systems for collision avoidance; and Driver-vehicle interface requirements.

The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

This two-volume set LNCS 12212 and 12213 constitutes the refereed proceedings of the Second International Conference on HCI in Mobility, Transport, and Automotive Systems, MobiTAS 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in Copenhagen, Denmark, in July, 2020.* A total of 1439 full papers and 238 posters have been carefully reviewed and accepted for publication in HCII 2020. The papers cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. MobiTAS 2020 includes a total of 59 papers and they are organized in the following topical sections: Part I, Automated Driving and In-Vehicle Experience Design: UX topics in automated driving, and designing in-vehicle experiences. Part II, Driving Behavior, Urban and Smart Mobility: studies on driving behavior, and urban and smart mobility. *The conference was held virtually due to the COVID-19 pandemic.

There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.

The conference is being organized by Madan Mohan Malaviya University of Technology Gorakhpur with an aim to provide a platform for researchers, scientists, technocrats, academicians and engineers to exchange their innovative ideas and new challenges facing in the field of Electrical and Electronics Engineering This Conference will be a platform to focus on the core technological developments in the emerging fields like wireless communication, RF microwave Radar, Electrical machine, power system, energy system, Image computing, intelligent information retrieval, intelligent agents, electrical and electronics materials, Fuzzy logic control, control system, evolutionary computing and so on

A comprehensive review and analysis of the human factors research associated with the implementation of crash warning system interfaces has led to the development of guidelines intended to be used by anyone responsible for the conceptualization, development, design, testing, or evaluation of in-vehicle crash avoidance systems, especially for forward collision (headway warning), lane change (blind-spot warning), and road departure warnings. This book is intended to highlight issues to be addressed and provide guidance in the development of Collision Warning Systems (CWSs). Information is presented on a variety of topics relevant to the driver-vehicle interface (DVI) of CWS devices.

The specific objectives of this handbook are to develop a set of clear, relevant, and easy-to-use lessons learned that can be used to support the development of the Driver-Vehicle Interface (DVI) of near-term Collision Warning Systems (CWS): 1) building on the 1996 effort conducted by Comsis, determine the current state of human factors knowledge applicable to DVI development; i.e., controls, displays, message content & timing; 2) to support the IVBSS program, develop guidelines for the integration of forward collision (headway warning), lane change (blind spot warning) and road departure warnings; 3) identify additional research that is needed to fill existing gaps in the knowledge base; 4) focus on passenger vehicles, but include information relevant to heavy trucks and buses.--P. 3, Power point overview.