Bie / Gao / Howlett Smart Transportation Systems 2023

Proceedings of 6th KES-STS International Symposium
1. Auflage 2023
ISBN: 978-981-99-3284-9
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 242 Seiten

Reihe: Engineering

This book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES STS 2023). Modern transportation systems have undergone a rapid transformation in recent years, producing a range of technological innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations, and breakthroughs in smart transportation systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.

Zielgruppe

Research

Autoren/Hrsg.

Bie, Yiming

Gao, Kun

Howlett, Robert J.

Jain, Lakhmi C.

Inhaltsverzeichnis

Chapter 1: Research Progress on Key Technologies of Environmental Perception and Detection of Transport System in Goaf of Coal Mine.- Chapter 2: LSTM-based vehicle trajectory prediction using UAV drone data.- Chapter 3: Dynamic Pricing for Mobile Charging Service Considering Electric Vehicles Spatiotemporal Distribution.- Chapter 4: Guidance method of connected autonomous vehicles under automatic control intersections.- Chapter 5: Multivariate Sequences Clustering for Driving Preferences Classification Based on Wide-range Trajectory Data.- Chapter 6: Optimizing the Deployment of Automated Speed Camera at the Intersections Using GPS Trajectories.- Chapter 7: Examining the effect of speeding patterns on speeding-related harsh decelerations for commercial drivers with survival analysis.- Chapter 8: Research and Application Analysis of Stepwise Incremental fine Model for Speeding Behavior.- Chapter 9: Interaction-Aware Trajectory Prediction for Autonomous Vehicle Based on LSTM-MLP Model.-Chapter 10: Speed Profile Optimization for Energy-saving Operations of Electric Buses. etc.

Über Autor(innen)

Yiming Bie is Professor of Transportation Engineering with the School of Transportation, Jilin University, China. He obtained his Ph.D. degree at Jilin University in June 2012. His research interests include public transportation operations, traffic control, and intersection design. He has authored or co-authored over 70 journal articles at top-tier journals such as Transportation Research Part C, Computer-Aided Civil and Infrastructure Engineering, Journal of Transportation Engineering-ASCE. The algorithms developed by him were adopted by the most popular adaptive traffic control system in China and has been implemented to more than 20 cities. Recently, his research is focused on electric bus operations in cold regions. He is Principal Investigator for two projects funded by National Natural Science Foundation of China and a few projects from other funding agencies. In 2019, he was conferred the outstanding reviewer recognition by Journal of Transportation Engineering-ASCE.

Kun Gao is an Assistant Professor in the Urban Mobility Systems research group, Department of Architecture and Civil Engineering. His research focuses on promoting sustainable mobility with focuses on electrification, shared mobility, and connected automation. Special interests are attached to establishing new approaches and tools for system planning, optimization and evaluation of emerging transport systems leveraging big data and machine learning. The overall goal is to facilitate the development of a safer, more sustainable, and equitable transportation system.

Dr. Robert J. Howlett is Executive Chair of KES International, a non-profit organization that facilitates knowledge transfer and the dissemination of research results in areas including Intelligent Systems, Sustainability, and Knowledge Transfer. He is Visiting Professor at Bournemouth University in the UK. His technical expertise is in the use of intelligent systems to solve industrial problems. He has been successful in applying artificial intelligence, machine learning, and related technologies to sustainability and renewable energy systems; condition monitoring, diagnostic tools and systems; and automotive electronics and engine management systems. His current research work is focused on the use of smart microgrids to achieve reduced energy costs and lower carbon emissions in areas such as housing and protected horticulture.

Dr. Lakhmi C. Jain, Ph.D., ME, BE(Hons), Fellow (Engineers Australia), is with the University of Technology Sydney, Australia, and Liverpool Hope University, UK. She serves the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation, and teaming. Involving around 5,000 researchers drawn from universities and companies worldwide, KES facilitates international cooperation and generates synergy in teaching and research. KES regularly provides networking opportunities for professional community through oneof the largest conferences of its kind in the area of KES.