Green, Smart and Connected Transportation Systems

Proceedings of the 9th International Conference on Green Intelligent Transportation Systems and Safety
Herausgegeben:Wang, Wuhong; Baumann, Martin; Jiang, Xiaobei

• Broschiertes Buch

Produktbeschreibung

These proceedings gather selected papers from the 9th International Conference on Green Intelligent Transportation Systems and Safety, held in Guilin, China on July 1-3, 2018. They feature cutting-edge studies on Green Intelligent Mobility Systems, the guiding motto being to achieve "green, intelligent, and safe transportation systems." The contributions presented here can help promote the development of green mobility and intelligent transportation technologies to improve interconnectivity, resource sharing, flexibility and efficiency. Given its scope, the book will benefit researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and System Engineering, and Electrical Engineering alike.

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Produktdetails

• Lecture Notes in Electrical Engineering 617
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-15-0646-8
• 1st ed. 2020
• Seitenzahl: 1540
• Erscheinungstermin: 7. April 2021
• Englisch
• Abmessung: 235mm x 155mm
• ISBN-13: 9789811506468
• ISBN-10: 9811506469
• Artikelnr.: 61295522

Autorenporträt

Dr. Wang Wuhong spent two years as a postdoctoral fellow at Beihang University from 1997 to 1999 after finished his Ph. D studies at Southwest Jiaotong University. He then joined the Beijing Institute of Technology in 1999, first as an Associate Professor then as a full Professor. Prof. Dr. Wang stayed at the computer vision lab in the Institute of Industrial Science at the University of Tokyo, Japan, as a JSPS Researcher in 2002-2004 and as a Visiting Professor in 2005. From 2005 to 2007 Prof. Dr. Wang had been affiliated with Lehrstuhl für Ergonomie, Technische Universität München, Germany, where he was a Humboldt Research Fellow. He conducted research at Transportation Research Institute (IMOB), Hasselt University, Belgium in 2014 as a guest professor. He also acted as a visiting professor at Institute of Transportation Systems, Germany Aerospace Center(DLR) in 2015 and Institute for Traffic Safety and Automation Engineering, Technische Universität Braunschweig in 2016. Prof. Dr. Wang has published his research in several international journals such as the Transportation Research Part C, Part F, IEEE Transaction on Intelligent Transportation System and Safety Science. Dr. Xiaobei JIANG received the Dr.-Ing. in traffic technology from Institute of Ergonomics, Technische Universität München, Germany. She is currently a research fellow in BIT-TUM Joint Laboratory for Driver Behavior and Traffic Safety, she also an assistance professor in Department of Transportation Engineering, Beijing Institute of Technology. Her major study fields include road user behavior, ADAS and intelligent vehicle, vehicle's human-machine interface and traffic safety.

Inhaltsangabe

Ordinal Logistic Regression Modeling Research on Decreasing Perceived Metro Transfer Time.- Dynamic programming approaches for solving shortest path problem in transportation: comparison and application.- A review of the research on the entrance control method of Urban Expressway.- Operation optimization considering order cancellation and ticket discount for on-demand bus system.- Alleviate Traffic Congestion and Reduce Energy Consumption by Setting a Peak-only Bus Lane on a Bottleneck-Constrained Highway.- Influence of Lane Change on Driving Behaviours in Traffic Oscillations based on Vehicle Trajectory Data from Aerial Videos.- Study on Routing Optimization Model of Container Sea-Rail Intermodal Transport Based on Transit Period.- Parking Demand Forecasting Model for Urban Complex Based on Shared Parking.- Visualization of Spatio-temporal Traffic Performance in Urban Road Network Based on Grid Model.- Airfield Smart Operations Management and Application of Shared Services.- Bearing Fault Diagnosis with Impulsive Noise Based on EMD and Cyclic Correntropy.- Author Index.