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Unmanned Driving Systems for Smart Trains explores the core technologies involved in unmanned driving systems for smart railways and trains, from foundational theory to the latest advances. The volume introduces the key technologies, research results and frontiers of the field. Each chapter includes practical cases to ground theory in practice. Seven chapters cover key aspects of unmanned driving systems for smart trains, including performance evaluation, algorithm-based reasoning and learning strategy, main control parameters, data mining and processing, energy saving optimization and control, and intelligent algorithm simulation platforms. This book will help researchers find solutions in developing better unmanned driving systems.
- Responds to the expansion of smart railways and the adoption of unmanned global systems
- Covers core technologies of unmanned driving systems for smart trains
- Details a large number of case studies and experimental designs for unmanned railway systems
- Adopts a multidisciplinary view where disciplines intersect at key points
- Gives both foundational theory and the latest theoretical and practical advances for unmanned railways
Researchers and graduate students in transportation engineering and unmanned systems and engineers in applied robot systems and rail transit
Chapter 1: Introduction of train unmanned driving system
1.1 Overview of the train unmanned driving system
1.2 Fundamental key problems of the unmanned railway vehicle system
1.3 Scope of the book
Chapter 2: Train unmanned driving system and its comprehensive performance evaluation system
2.1 Overview of the ATO/ATP/ATS systems
2.2 The performance index of the train unmanned driving system
2.3 The comprehensive performance evaluation method of the train unmanned driving system
Chapter 3: Train unmanned driving algorithm based on reasoning and learning strategy
3.1 The current status and technical progress of train unmanned controlling algorithm
3.2 The connotation and composition of train unmanned driving algorithm
3.3 Calculation process and analysis of train unmanned driving algorithm
Chapter4 : Identification of main control parameters for train unmanned driving system
4.1 Common methods for driving control of main control parameter identification
4.2 Train unmanned driving dynamic models
4.3 Identification methods of train intelligent traction
Chapter 5: Data mining and processing for train unmanned driving system
5.1 Data mining and processing of manual driving mode
5.2 Data mining and processing of automatic driving mode
5.3 Data mining and processing of unmanned driving mode
Chapter 6: Energy saving optimization and control for train unmanned driving system
6.1 Technical status of train unmanned driving energy consumption analysis
6.2 Single target train energy saving and manipulation based on artificial intelligence algorithm optimization
6.3 Multi-target train energy saving and control based on group artificial intelligence
Chapter 7: Unmanned driving intelligent algorithm simulation platform
7.1 Introduction of MATLAB∕ Simulink simulation platform
7.2 Design method of train intelligent driving algorithm simulation platform
7.3 Train automatic operation control model and programming
7.4 Train intelligent driving algorithm simulation GUI design standard
7.5 Applications and case analysis of mainstream train unmanned driving systems
- No. of pages:
- © Elsevier 2021
- 18th November 2020
- Paperback ISBN:
- eBook ISBN:
Hui Liu is a Professor of Robotics and Artificial Intelligence, at Central South University, China, as well as a Vice Dean of the Faculty of Traffic and Transportation Engineering, and Director of the Institute of Artificial Intelligence and Robotics (IAIR). He received a Ph.D. in Automation Engineering, and his habilitation, from Rostock University in Germany. He has published more than 70 papers, and holds over 50 patents.
Central South University, in Changsha, China
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