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Geographic Information Systems (GIS) can help transportation agencies conduct noise analyses, including assessing how highway traffic will affect noise levels and identifying noise migration options. To explore this topic in depth, Federal Highway Administration (FHWA) and the Volpe National Transportation Systems Center conducted a series of telephone discussions and sponsored a peer exchange in Nashville, Tennessee, focusing on select State DOT's use of GIS in highway noise analysis. These interviews and peer exchange provided an opportunity for practitioners to discuss new approaches for using GIS to address Federal mandates. They also facilitated opportunities for States to gain knowledge from others' successes and challenges in the application of GIS. Furthermore, resources that can support agencies' use of GIS can be found in the appendix.
This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.
Impact Assessment is becoming part and parcel of an increasing number of development proposals in the UK and Europe. As the practice of Impact Assessment develops it becomes more standardized and good practice starts to be defined. However, the quality of Impact Assessment is still far from satisfactory. Expert Systems and GIS for Impact Assessment
In recent years, the application of intelligent transportation systems (ITS) has steadily expanded, and has become a hot spot of common interest to universities, scientific research institutes, enterprises and institutions in the transportation field. ITS is the product of the deep integration of modern high-tech in the transportation industry, and its development has accompanied that of modern high-tech. ITS is now also becoming part of the Internet of Things (IoT), and is expected to contribute significantly to making our cities smarter and connecting with other infrastructure. Although there are many monographs and textbooks on intelligent transportation, with the advancement of technology and changes in demand, the key technologies of ITS are also rapidly changing. This book chiefly focuses on the main technologies of ITS, examining them from four perspectives: “sense” (perception and management of traffic information, chapters 2 & 3), “transmission” (interaction of traffic information, chapter 4), “prediction” (prediction of traffic states, chapter 6) and “application” (intelligent transportation applications, chapters 6 through 10). Given its scope, the book can be used as a textbook for undergraduates or graduates, as well as a reference book for research institutes and enterprises. This book emphasizes the use of basis traffic engineering principles and state-of-art methodologies to develop functional designs. It largely reflects the authors’ own experience in adapting these methodologies to ITS design. For example, the book addresses various forms of data collection, models used to predict and evaluate traffic states, comprehensive description in connected vehicles, applications for users and traffic managers, etc. The knowledge gained here will allow designers to estimate the performance differences among alternatives and gauge their potential benefits for functional design purposes. To gain the most from the book, readers should be somewhat familiar with the field of traffic engineering and interested in ITS.
During the past decade, we have witnessed the sharp increase in the use of Geographic Information Systems (GIS) for spatial data analysis, particularly in the Far East. This proceedings is a compilation of papers that range from advanced applications of GIS to the development of GIS. The papers present new research problems and results, experience, and strategies in developing GIS projects.