Travel Behavior Characteristics Analysis Technology Based on Mobile Phone Location Data: Methodology and Empirical Research - Brossura

Yang, Fei; Yao, Zhenxing

Brossura

ISBN 10: 9811680108 ISBN 13: 9789811680106

Casa editrice: Springer, 2023

Riassunto

This book is devoted to the technology and methodology of individual travel behavior analysis and refined travel information extraction. Traditional resident trip surveys are characterized by many shortcomings, such as subjective memory errors, difficulty in organization and high cost. Therefore, in this book, a set of refined extraction and analysis techniques for individual travel activities is proposed. It provides a solid foundation for the optimization and reconstruction of traffic theoretical models, urban traffic planning, management and decision-making.

This book helps traffic engineering researchers, traffic engineering technicians and traffic industry managers understand the difficulties and challenges faced by transportation big data. Additionally, it helps them adapt to changes in traffic demand and the technological environment to achieve theoretical innovation and technological reform.

Su questo libro

Informazioni sull?autore

Fei Yang, Ph.D., professor, is the head of the Department of Traffic Engineering, Southwest Jiaotong University. He is a committee member of the Academic Committee of Urban Transport Planning of Urban Planning Society of China, the expert of the Young Expert Working Committee of China Intelligent Transportation Systems Association, the chairman of Technical Committee on public transport Operation and Management of the World Transport Convention, etc. Professor Yang has been selected into the Program for New Century Excellent Talents at University. He has conducted more than 10 national and provincial scientific research projects, including 4 projects of the National Natural Science Foundation of China and 1 subproject of the National Key R&D Program of China. He serves as the editorial board and reviewer of a number of international SCI journals and EI journals. In recent years, he has published more than 40 academic papers and 2 academic monographs, where one of the monographs is funded by the National Publication Foundation and selected into the National publication Plan for key publications of the “The 13th Five-Year Plan”. He has also applied for 13 invention patents, among which 7 have been authorized.

Zhenxing Yao, Ph.D., is an assistant professor at the College of Transportation Engineering, Chang’an University. He has long been engaged in the research and application of intelligent transportation systems, transportation big data, active traffic management and traffic simulation. He has participated in more than 10 national and provincial research projects, such as the National Natural Science Foundation of China and Social Sciences Foundation of the Ministry of Education, and participated in more than 30 traffic practice projects. He has published more than 20 academic papers, 2 monographs, 4 patents and 5 software copyrights. He also serves as the reviewer of several famous journals in traffic engineering, including Transportation Research Part C and IEEE Transactions on ITS, and is a committee member of the public transport management committee of the World Transport Convention.

Dalla quarta di copertina

This book is devoted to the technology and methodology of individual travel behavior analysis and refined travel information extraction. Traditional resident trip surveys are characterized by many shortcomings, such as subjective memory errors, difficulty in organization and high cost. Therefore, in this book, a set of refined extraction and analysis techniques for individual travel activities is proposed. It provides a solid foundation for the optimization and reconstruction of traffic theoretical models, urban traffic planning, management and decision-making.

This book helps traffic engineering researchers, traffic engineering technicians and traffic industry managers understand the difficulties and challenges faced by transportation big data. Additionally, it helps them adapt to changes in traffic demand and the technological environment to achieve theoretical innovation and technological reform.

Dettagli dell?edizione

• Editore: Springer
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 9811680108
• ISBN 13: 9789811680106
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 240
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania