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.
Author(s): Yunpeng Wang, Xinping Yan, Guangquan Li, Chaozhong Wu
Publisher: Springer
Year: 2022
Language: English
Pages: 613
City: Singapore
Preface
Contents
Chapter 1: Introduction
1.1 Introduction to Intelligent Transportation System
1.1.1 Basic Concept of Intelligent Transportation System
1.1.2 History of Intelligent Transportation System
1.2 Development of Intelligent Transportation System
1.2.1 Development History and Present Situation of Intelligent Transportation System in the United States
1.2.1.1 Development History
1.2.1.2 System Framework
1.2.1.3 Main Technical Features
1.2.2 Development History and Present Situation of Intelligent Transportation System in Japan
1.2.2.1 Developmental History
1.2.2.2 System Framework
1.2.2.3 Main Technical Features
1.2.3 Development and Status of Intelligent Transportation Systems in Europe
1.2.3.1 Development History
1.2.3.2 System Framework
1.2.3.3 Main Technical Features
1.2.4 Development History and Present Situation of Intelligent Transportation System in China
1.2.4.1 Development History
1.2.4.2 System Framework
1.2.4.3 Main Technical Features
1.3 Development Trend of Intelligent Transportation System
1.4 Summary
Bibliography
Chapter 2: Information Collection Technology in ITS
2.1 Characteristics and Classification of Intelligent Transportation Information Technology
2.1.1 Characteristics of Intelligent Transportation Information
2.1.2 Classification of Intelligent Transportation Information Technology
2.1.2.1 Frequency of Information Change
2.1.2.2 Traffic Information Demand
2.1.2.3 Information Collection Method
2.2 Fixed Traffic Information Collection Technology
2.2.1 Information Collection Using Geomagnetic Sensor
2.2.1.1 Composition
2.2.1.2 The Structure of the Information Collection Protocol
2.2.1.3 Information Collection Algorithm
2.2.2 Information Collection Using Ultrasonic
2.2.3 Information Collection Using Video
2.2.3.1 Video Image Information
2.2.3.2 Video Image Information Object
2.2.3.3 Feature Attributes of Video Image Information Objects
2.2.3.4 Video Image Labels
2.2.3.5 Triggering Event
2.2.4 Information Collection Using Microwave Radar
2.2.5 Comparison
2.3 Mobile Traffic Information Collection Technology
2.3.1 Information Collection Using Floating Car
2.3.1.1 Mobile Traffic Information Collection Technology
2.3.1.2 Active Test Vehicle Technology
2.3.1.3 Passive Detecting Vehicle Technology
2.3.1.4 Basic Principles of Traffic Mobile Collection Technology
2.3.1.5 Introduction to Nagoya´s P-DRGS Based on Floating Car Information
2.3.2 Information Collection Using UAV
2.3.2.1 Characteristics of Drone Traffic Information Collection Technology
2.3.2.2 Application of Drones Traffic Information Collecting Technology
2.3.2.3 Traffic Detection Based on Drone Video
2.3.3 Crowdsourcing Information Collection Technology
2.3.3.1 Crowdsourcing of Traffic Information Users
2.3.3.2 Generated Content Platform Workflow
2.3.3.3 Problems with Current Generated Content Technology
2.3.3.4 Generated Content Application Case
References
Chapter 3: Traffic Data Management Technology in ITS
3.1 Data Cleaning Technology
3.1.1 Importance of Data Cleaning
3.1.2 The Main Content of Data Cleaning
3.1.3 The Main Method of Data Cleaning
3.2 Data Storage Technology
3.2.1 Data Format
3.2.2 Data Storage Method
3.2.3 Distributed Storage
3.3 Data Mining and Visualization
3.3.1 Data Query
3.3.2 Data Classification
3.3.3 Data Clustering
3.3.4 Data Association
3.3.5 Spatiotemporal Data Analysis
3.3.6 Geocoding
3.3.7 Location Matching
References
Chapter 4: Intelligent Transportation Information Interaction Technology
4.1 Overview
4.1.1 Concept
4.1.2 Development Status
4.2 Architecture and Key Technologies
4.2.1 Architecture
4.2.1.1 System Composition
4.2.1.2 Technical Realization of the Internet of Vehicles Communication System
4.2.2 Key Technologies Based on the Physical Layer
4.2.2.1 Communication Channel Modeling Analysis
4.2.2.2 Evaluation of Wireless Channel Communication Performance
4.2.2.3 Communication Channel Estimation Technology
4.2.3 Key Technologies Based on the MAC Layer
4.3 Technical Standards
4.3.1 Overview of the Development of Technical Standards
4.3.2 DSRC Technology and Standards
4.3.2.1 Physical Layer
4.3.2.2 MAC Layer
4.3.3 C-V2X Technology and Standards
4.3.3.1 Key Technologies of LTE-V2X
4.3.3.2 NR-V2X Key Technology
4.4 Typical Applications and Future Trends
4.4.1 Typical Applications
4.4.1.1 Cooperative Positioning of Vehicles Based on Information Interaction
4.4.1.2 Cooperative Perception Based on Information Interaction
4.4.2 Future Development Trends
References
Chapter 5: Traffic State Analysis and Prediction Technology
5.1 Concept and Connotation of Traffic State
5.1.1 Concept of Traffic Status
5.1.2 Index System of Traffic State
5.1.2.1 Volume
5.1.2.2 Speed
5.1.2.3 Traffic Flow Density
5.1.2.4 Time Headway and Space Headway
5.1.2.5 Occupancy
5.1.2.6 Queue Length
5.2 Discrimination and Analysis of Traffic States
5.2.1 Road Traffic States Discrimination
5.2.1.1 California Algorithm
5.2.1.2 Exponential Smoothing Method
5.2.1.3 McMaster Algorithm
5.2.1.4 Standard Deviation Method
5.2.1.5 Double Section ACI Algorithm Based on ANN
5.2.2 Traffic States Analysis Method
5.2.2.1 Analysis of Micro Traffic State
5.2.2.2 Analysis of Meso Traffic State
5.2.2.3 Analysis of Macro Traffic State
5.2.2.4 Case Study
5.3 Basic Theory and Method of Prediction
5.3.1 Overview of Traffic State Prediction
5.3.1.1 Prediction Based on Parameter Model
5.3.1.2 Prediction Based on Nonparametric Model
5.3.1.3 Prediction Based on Artificial Intelligence
5.3.1.4 Prediction Based on Combination Model
5.3.2 Analysis of Traffic State Prediction Methods
5.3.2.1 Time Series Prediction Method
5.3.2.2 Neural Network Algorithm
5.3.2.3 Traffic State Prediction Based on Support Vector Machine Regression
5.3.2.4 Road Network Traffic State Prediction Based on Deep Learning
5.4 Congestion Prediction Method and Application
5.4.1 Congestion Discrimination
5.4.1.1 Definition of Traffic Congestion
5.4.1.2 Classification of Traffic Congestion
5.4.1.3 Quantitative Standard of Traffic Congestion
5.4.1.4 Discrimination Method of Traffic Congestion
5.4.2 Basic Framework of Congestion State Prediction Method and Application
5.4.2.1 Congestion Prediction Method
5.4.2.2 Case Analysis
5.4.2.3 Basic Framework of Congestion Prediction Algorithm Application
References
Chapter 6: Intelligent Transportation Information Service Technology
6.1 The Connotation of Intelligent Transportation Information Service
6.1.1 Concept of Intelligent Transportation Information Service Systems
6.1.1.1 Concept of Intelligent Transportation Information Service Systems
6.1.1.2 Development Course
6.1.2 Function of Intelligent Transportation Information Service System
6.1.3 Classification of Intelligent Transportation Information Service System
6.2 Key Technologies of Intelligent Transportation Information Service
6.2.1 The Composition and Working Principle of the Traffic Information Service System
6.2.1.1 Traffic Information Center, TIC
6.2.1.2 Communication Network
6.2.1.3 User Information Terminal
6.2.2 Theoretical Basis of Traffic Information Service System
6.2.2.1 Dynamic Traffic Assignment
6.2.2.2 Route Selection and Optimization
6.2.2.3 Traffic Information Release
6.2.3 Technical Basis of Traffic Information Service System
6.2.3.1 Global Positioning System
6.2.3.2 Geographic Information System
6.2.3.3 Map Matching Technology
6.2.3.4 Advanced Vehicle Networking Traffic Information Transmission Technology
6.2.3.5 V2X Communication Technology Based on Cellular Network C-V2X
6.2.3.6 Variable Information Sign Information System
6.2.3.7 The New Generation of High-Speed Internet of Vehicles Communication System 5G
6.2.3.8 Cloud Computing-Based Traffic Big Data Mining Technology
6.2.3.9 Variable Message Signs Information System
6.3 Advanced Traffic Information Service System
6.3.1 Typical Traffic Information Service System and Its Key Technologies
6.3.1.1 The U.S. Traffic Information Service System
6.3.1.2 European Traffic Information Service System
6.3.2 Traffic Information Service System of China
6.3.2.1 Traffic Public Travel Service Management System in Hubei Province
6.3.2.2 The Representative Enterprise-Level Road Traffic Information Service System in China
6.3.2.3 Traffic Information Service System Based on Mobile Internet
6.3.2.4 Hangzhou City Brain Information System
6.4 Summary
References
Chapter 7: Intelligent Traffic Management and Control Technology
7.1 Overview of Intelligent Traffic Management System (ITMS)
7.1.1 Concept and Development Status of ITMS
7.1.2 Framework and Function of ITMS
7.1.2.1 Basic Application System
7.1.2.2 Integrated Command Platform
7.1.2.3 Integrated Business Management System
7.1.2.4 Information Service Platform
7.2 Typical ITMS and Application
7.2.1 Intelligent Traffic Monitoring System
7.2.1.1 Overview of Intelligent Traffic Monitoring System
7.2.1.2 Composition and Function of Intelligent Traffic Monitoring System
7.2.2 Electronic Police System
7.2.2.1 Overview of Electronic Police System
7.2.2.2 Composition and Function of Electronic Police System
7.2.2.3 Key Technologies for Electronic Police Systems
7.2.3 Intelligent Public Transport Management System
7.2.3.1 Overview of Intelligent Public Transport Management System
7.2.3.2 Composition and Function of Intelligent Public Transport Management System
7.2.3.3 Key Technologies of Intelligent Public Transport Management System
7.2.4 Parking Guidance Information System
7.2.4.1 Overview of Parking Guidance Information System
7.2.4.2 Composition and Functions of Parking Guidance Information System
7.2.5 Emergency Management System
7.2.5.1 Overview of Emergency Management System
7.2.5.2 Composition and Function of Emergency Management System
7.2.6 Typical Urban Intelligent Traffic Management System and Its Application
7.2.6.1 Intelligent Traffic Management System of Beijing
7.2.6.2 Intelligent Traffic Management System of Shenzhen
7.2.6.3 Intelligent Traffic Management System of Wuhan
7.3 Overview of Intelligent Traffic Signal Control System
7.3.1 Brief Introduction of Traffic Signal Control System
7.3.1.1 Development Process
7.3.1.2 Genealogical Classification
7.3.2 Typical Intelligent Traffic Control System
7.3.2.1 SCATS System
7.3.2.2 SCOOT System
Principle and Structure of SCOOT System
Signal Timing Parameters Optimization of SCOOT System
Characteristics of SCOOT System
7.3.2.3 RHODES System
Principle and Structure of RHODES System
The Structure of the RHODES System
Control Method of RHODES System
Intersection Control
Network Flow Control
Characteristics of RHODES System
7.3.2.4 SPOT/UTOPIA System
SPOT System
UTOPIA System
Characteristics of SPOT/UTOPIA System
7.4 Application and Development Trend of Intelligent Traffic Control System in China
7.4.1 Nanjing Rice Urban Traffic Control System
7.4.2 Qingdao Haixin HiCon Traffic Signal Control System
7.4.3 Shenzhen SMOOTH Traffic Signal Control System
References
Chapter 8: Vehicle Intelligent Driving Technology
8.1 Intelligent Vehicles
8.1.1 Introduction of Intelligent Vehicles
8.1.2 Classification of Intelligent Vehicles
8.1.3 Composition of Intelligent Vehicles
8.1.3.1 The System that Improves the Performance of the Vehicle Itself
8.1.3.2 The System that Enhances Driver´s Ability
8.1.4 Development at Home and Abroad
8.1.4.1 With the Goal of Commercialization as Soon as Possible, Accelerate the Introduction of Road Testing and Regulations
8.1.4.2 With the Direction of China Unicom, Promote the Research and Development of the System and the Communication Standard ...
8.1.4.3 Leading by Innovative Formats, Internet Companies have Become an Important Driving Force
8.1.4.4 Taking Corporate Mergers and Acquisitions as a Breakthrough, Start-Ups, and Leading Companies Become Targets
8.2 Perception
8.2.1 Environmental Perception
8.2.2 Composition of Environmental Perception System
8.2.3 Overall Function of Environmental Perception
8.2.4 LiDAR
8.2.4.1 Introduction of LiDAR
8.2.4.2 Principle Analysis and Design of Ranging Module
8.2.4.3 Engineering Realization of Ranging Module
8.2.4.4 Engineering Realization of LiDAR Scanning
8.2.5 Millimeter Wave Radar
8.2.5.1 Introduction to Millimeter WaveRadar
8.2.5.2 Millimeter Wave Radar Detection Principle
8.2.5.3 Application of Millimeter Wave Radar in ADAS
8.2.6 Visual Perception System
8.2.6.1 Camera Classification
8.2.6.2 Application of Computer Vision in Unmanned Driving
8.3 Decision Planning Control
8.3.1 Decision Planning Control System
8.3.2 Decision
8.3.3 Planning
8.3.3.1 Path Planning
8.3.3.2 Speed Planning
8.3.4 Vehicle Control
8.3.4.1 Vertical Motion Control
8.3.4.2 Horizontal Motion Control
8.4 Application of New Technologies for Intelligent Vehicles
8.4.1 Deep Learning
8.4.1.1 Vehicle Application
8.4.1.2 Convolutional Neural Network
8.4.2 Reinforcement Learning
8.4.2.1 Introduction to Reinforcement Learning
8.4.2.2 Application of Reinforcement Learning in Autonomous Driving
8.4.3 Slam
References
Chapter 9: Intelligent Internet of Vehicles (IoV) and Vehicle Infrastructure Cooperative Technology
9.1 Introduction
9.1.1 From Driver Assistance to Connected Automated Vehicle
9.1.2 From Internet of Vehicles to Vehicle Infrastructure Cooperative Technology
9.2 Intersection Signal Control Technology Based on Internet of Vehicles
9.2.1 Prediction of Traffic Flow Parameters Based on Data of Internet of Vehicles
9.2.1.1 Traffic Flow Parameters Based on Internet of Vehicles Data
9.2.1.2 Data Filtering
9.2.1.3 Data Repair
9.2.1.4 Traffic Flow Parameter Prediction Based on IoV Data
9.2.2 Signal Timing Identification Based on Data of Internet of Vehicles
9.2.2.1 Basic Concepts of Urban Traffic Signal Control
9.2.2.2 Signal Timing Identification Based on Internet of Vehicles Data
9.2.3 Signal Timing Optimization Based on Data of Internet of Vehicles
9.2.3.1 Traffic Signal Control Evaluation Index
9.2.3.2 Signal Timing Optimization Method Based on IoV Data
Traffic Signal Timing Optimization with Dynamic Adjustment in the Environment of IoV
Traffic Signal Timing Optimization of On-Demand Distribution in IoV Environment
9.3 Travel Path Planning Technology in the Environment of Internet of Vehicles
9.3.1 Short-Time Forecasting of Road Network Operation Condition Based on Internet of Vehicles Data
9.3.2 Optimal Path Problem and Algorithm for Dynamic Road Network in Internet of Vehicles
9.3.2.1 Definition of Dynamic Road Network
9.3.2.2 Modeling of Optimal Path Problem for Dynamic Road Network
9.3.2.3 Optimal Path Algorithm for Dynamic Transportation Network
9.3.2.4 Improve Dijkstra Algorithm
9.3.2.5 A* Algorithm Based on Euclidean Distance
9.3.2.6 Improved A* Algorithm
9.3.3 Vehicle Service Routing Problem and Algorithm in the Environment of Internet of Vehicles
9.3.3.1 Problem Description
9.3.3.2 The optimization Goals
9.3.3.3 Problem Modeling
9.4 Intelligent Control Technology in Vehicle-to-Infrastructure Cooperation Environment
9.4.1 Platoon Cooperative Control of Car-Following Based on Vehicle-to-Vehicle Communication
9.4.1.1 Car-Following Process and Platoon Control Based on Vehicle-to-Vehicle Communication
9.4.1.2 Structure of Platoon Control System in Car Following Process
9.4.1.3 Goal of Platoon Cooperative Control in Car Following Process
9.4.1.4 Stability Analysis of the Platoon Cooperative Control in Car Following Process
9.4.1.5 String Stability Analysis Based on Fixed Time Headway
9.4.1.6 String Stability Analysis Based on Fixed Spacing Headway
9.4.2 Lane-Changing Control Under the Vehicle-to-Infrastructure Cooperation Environment
9.4.2.1 Lane-Changing Behavior
9.4.2.2 Objective of Cooperative Lane-Changing Control
9.4.2.3 Cooperative Lane-Changing Control
9.4.3 Traffic Control Method of Intersections Under the Vehicle-to-Infrastructure Cooperation Environment
9.4.3.1 Classification of Main Methods and Basic Principles of Cooperative Control at Intersections
9.4.3.2 Distributed Traffic Control Model at Intersections
Gap acceptable model
Bibliography
Chapter 10: Typical Intelligent Transportation Applications
10.1 Urban Traffic Status Monitoring and Index Evaluation System
10.1.1 System Profile
10.1.1.1 History and Current Situation of Traffic Data Acquisition and Preprocessing
10.1.1.2 History and Present Situation of Traffic Condition Monitoring
10.1.2 System Composition
10.1.2.1 Factors Influencing Traffic Safety in Cities
10.1.2.2 Urban Road Traffic Safety Monitoring Index System
10.1.2.3 Domestic and Foreign Road Traffic Index Summary
10.1.3 Example: Application of Shanghai Road Traffic State Index
10.1.3.1 Urban Express Network
10.1.3.2 Ground Road Network
10.2 Network Control System for Key Operating Vehicles
10.2.1 System Profile
10.2.1.1 Development Background and History of Network Control System for Key Operating Vehicles
10.2.1.2 System Framework of Networked Control System for Key Operating Vehicles
10.2.1.3 Main Functions of Networked Control System for Operating Vehicles
10.2.1.4 Main Features of Networked Control System for Operating Vehicles
10.2.2 System Composition and Service Functions
10.2.2.1 On-Board Mobile Terminal
10.2.2.2 Monitoring Platform
10.2.3 Example: Driving Behavior Monitoring and Early Warning System
10.2.3.1 Vehicle Terminal System
10.2.3.2 Remote Information Release and Supervision Platform
10.3 Intelligent Networked Vehicle Testing and Evaluation System
10.3.1 Background and Development
10.3.1.1 The Development of U.S. Intelligent Connected Vehicle (ICV) Testing
10.3.1.2 The Development of Domestic Intelligent Connected Vehicle (ICV) Testing
10.3.2 Test Verification Technology and Test Method
10.3.2.1 Analysis of Requirements for Test Verification of Intelligent Connected Vehicles
10.3.2.2 Common Test Methods
10.3.3 Case: The Closed Test Zone in Shanghai International Automobile City (F-Zone)
10.3.3.1 Test Environment
10.3.3.2 Testing Ability
10.3.3.3 Test Equipment
10.4 Traffic Organization and Management System for Large-Scale Event
10.4.1 A Brief Introduction to the System
10.4.2 Composition of the System
10.4.2.1 Analysis of Traffic Characteristics of Large-Scale Events
10.4.2.2 Forecast of Traffic Demand for Large-Scale Events
10.4.2.3 Traffic Demand Management for Large-Scale Events
10.4.2.4 Traffic Organization Planning of Large-Scale Events
10.4.2.5 Release of Traffic Information for Large-Scale Events during Large-Scale Events
10.4.2.6 Emergency Traffic Organization and Management Plan of Large-Scale Events
10.4.3 Example: Transportation Organization and Management of the Shenzhen World University Games
10.4.3.1 Traffic Demand Forecasting of Shenzhen World University Games
10.4.3.2 Traffic Demand Management during the WUG
10.4.3.3 Transport Organization Planning for the WUG
10.4.3.4 Summary After the WUG
References
