Behavior Analysis and Modeling of Traffic Participants, Song
Автор: Konstantin Naumenko; Holm Altenbach Название: Modeling High Temperature Materials Behavior for Structural Analysis ISBN: 3319316273 ISBN-13(EAN): 9783319316277 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph presentsapproaches to characterize inelastic behavior of materials and structures athigh temperature.
Описание: This monograph presentsapproaches to characterize inelastic behavior of materials and structures athigh temperature.
Автор: Konstantin Naumenko; Holm Altenbach Название: Modeling of Creep for Structural Analysis ISBN: 364208981X ISBN-13(EAN): 9783642089817 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book develops methods to simulate and analyze the time-dependent changes of stress and strain states in engineering structures up to the critical stage of creep rupture. The objective of this book is to review some of the classical and recently proposed approaches to the modeling of creep for structural analysis applications.
Автор: Song Xiaolin, Cao Haotian Название: Behavior Analysis and Modeling of Traffic Participants ISBN: 1636392628 ISBN-13(EAN): 9781636392622 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11227.00 р. Наличие на складе: Нет в наличии.
Описание: To bring down the rate of traffic fatalities, the development of the intelligent vehicle is a much-valued technology. Results and conclusions from this book are expected to offer potential guidance and benefits for promoting the development of intelligent vehicle technology and driving safety.
Автор: Haotian Cao, Xiaolin Song Название: Behavior Analysis and Modeling of Traffic Participants ISBN: 1636392644 ISBN-13(EAN): 9781636392646 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14414.00 р. Наличие на складе: Нет в наличии.
Описание:
A road traffic participant is a person who directly participates in road traffic, such as vehicle drivers, passengers, pedestrians, or cyclists, however, traffic accidents cause numerous property losses, bodily injuries, and even deaths to them. To bring down the rate of traffic fatalities, the development of the intelligent vehicle is a much-valued technology nowadays. It is of great significance to the decision making and planning of a vehicle if the pedestrians' intentions and future trajectories, as well as those of surrounding vehicles, could be predicted, all in an effort to increase driving safety. Based on the image sequence collected by onboard monocular cameras, we use the Long Short-Term Memory (LSTM) based network with an enhanced attention mechanism to realize the intention and trajectory prediction of pedestrians and surrounding vehicles.
However, although the fully automatic driving era still seems far away, human drivers are still a crucial part of the road‒driver‒vehicle system under current circumstances, even dealing with low levels of automatic driving vehicles. Considering that more than 90 percent of fatal traffic accidents were caused by human errors, thus it is meaningful to recognize the secondary task while driving, as well as the driving style recognition, to develop a more personalized advanced driver assistance system (ADAS) or intelligent vehicle. We use the graph convolutional networks for spatial feature reasoning and the LSTM networks with the attention mechanism for temporal motion feature learning within the image sequence to realize the driving secondary-task recognition.
Moreover, aggressive drivers are more likely to be involved in traffic accidents, and the driving risk level of drivers could be affected by many potential factors, such as demographics and personality traits. Thus, we will focus on the driving style classification for the longitudinal car-following scenario. Also, based on the Structural Equation Model (SEM) and Strategic Highway Research Program 2 (SHRP 2) naturalistic driving database, the relationships among drivers' demographic characteristics, sensation seeking, risk perception, and risky driving behaviors are fully discussed. Results and conclusions from this short book are expected to offer potential guidance and benefits for promoting the development of intelligent vehicle technology and driving safety.
Автор: Nathan H. Gartner; Gennaro Improta Название: Urban Traffic Networks ISBN: 3642796435 ISBN-13(EAN): 9783642796432 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The problems of urban traffic in the industrially developed countries have been at the top of the priority list for a long time.
Описание: Conservation and balance laws on networks have been the subject of much research interest given their wide range of applications to real-world processes, particularly traffic flow.
Описание: Conservation and balance laws on networks have been the subject of much research interest given their wide range of applications to real-world processes, particularly traffic flow.
Автор: Collendanchise, Michele (italian Institute Of Technology, Genova, Italy) Ogren, Petter (kth Royal Institute Of Technology, Stockholm, Sweden) Название: Behavior trees in robotics and al ISBN: 1138593737 ISBN-13(EAN): 9781138593732 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book on Behavior Trees (BTs) in robotics and AI.
Автор: Karimi, Hamid Reza Название: Vehicle Crash Modeling and Analysis ISBN: 0128127503 ISBN-13(EAN): 9780128127506 Издательство: Elsevier Science Рейтинг: Цена: 17854.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The mathematical and software-based modelling and analysis of vehicle crash scenarios have not been systematically investigated yet.
Numerous academic and industry studies have analysed vehicle safety during physical crash scenarios. Material responses during the crash serve as one of the most important performance indices for mechanical design problems. As a result, a large number of signal processing methodologies have been developed to seek convenient ways of computing the constrained design problems, among which the time, frequency, and time-frequency algorithms are three main categories to analyse crash responses. In addition to these mathematical methodologies, this book provides thorough coverage of computer simulations and software-based modeling and analysis methods capable of providing more flexibility in explicitly dealing with the trade-offs and constraints of the pre-specified crash requirements.
Vehicle Crash Modeling and Analysis is to shorten such a gap by providing a unified framework and a timely collection of up-to-date results in the area concerned. The analysis tools taken into consideration will be investigated for three different crash scenarios such as front crash, side crash and car to car crashes.
The book is ideal to be used as a reference. It is written in a way that the presentation is simple, clear, and easy to read and understand.
Unifies existing and emerging concepts concerning vehicle crash dynamics
Provides a series of latest results in mathematical-based modelling from the front and oblique perspectives
Contains almost everything needed to capture the essence of model development and analysis for vehicle crash
Numerical and simulation results are given in each chapter in order to reflect the engineering practice, yet demonstrate the main focus of the developed modelling approaches
Comprehensive, up-t0-date references perform an indicative role for further study
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