Big Data Transportation Systems

✍ Scribed by Guanghui Zhao, Gusheng Zhu

• Publisher: World Scientific Publishing Company
• Year: 2021
• Tongue: English
• Leaves: 352
• Category: Library

✦ Synopsis

This book is designed as a popular science book on big data analytics in intelligent transportation systems. It aims to provide an introduction to big-data transportation starting from an overview on the development of big data transportation in various countries. This is followed by a discussion on the blueprint strategies of big data transportation which include innovative models, planning, transportation logistics, and application case studies. Finally, the book discusses applications of big data transportation platforms.

✦ Table of Contents

Contents
Foreword by Ni Jun
Foreword by You Zheng
Preface
About the Authors
Introduction
Part I Cognition: Understanding Big Data
Chapter 1 What is Big Data Transportation?
1.1 Big Data Transportation and Internet +
1.1.1 Big data is coming fast
1.1.2 Big data transportation is perfect
1.1.3 Internet + transportation is at the right time
1.2 Big Data Transportation and Intelligent Transportation
1.2.1 What is intelligent transportation
1.2.2 Big data in intelligent transportation
1.3 Big Data Transportation and Cloud Computing
1.4 Big Data Transportation and Artificial Intelligence
Chapter 2 Big Data Transportation: Getting Closer to Life
2.1 Self-Service Travel of Big Data Transportation
2.1.1 Self-service travel by bicycle
2.1.2 Other self-service travel
2.2 High-Speed Railway Travel of Big Data Transportation
2.2.1 Intelligence
2.2.2 Self-service
2.2.3 Low cost
2.2.4 Safety
2.3 Highway Travel of Big Data Transportation
2.3.1 Highway travel under the big data
2.3.2 Urban road travel under big data
2.4 Civil Aviation Travel of Big Data Transportation
2.4.1 Big data of civil aviation is a treasure
2.4.2 Highly self-service of civil aviation
2.4.3 Civil aviation big data can improve service quality
2.4.4 Civil aviation big data improves the aviation safety index
2.5 Freight Transportation of Big Data Transportation
2.5.1 How to predict freight transportation in advance
2.5.2 Carrying out freight transportation plan and crossing peak transportation
2.5.3 Freight data can better serve freight participants
Chapter 3 Strategy Blueprint of Big Data Transportation
3.1 Big Data Transportation in the United States
3.1.1 Years of technological sophistication and innovation
3.1.2 Extremely open data
3.1.3 Numerous innovation elements and complete industry chain
3.2 Big Data Transportation in Europe
3.2.1 The development of big data transportation is more humane and more beneficial to the people
3.2.2 Financial investment is increased
3.2.3 The construction of big data transportati on is focusedon public transportation
3.3 Big Data Transportation in Japan
3.3.1 Government-led and unified norms
3.3.2 The car companies are highly electronic
3.3.3 High degree of marketization
3.3.4 Information sharing is adequate
3.4 Big Data Transportation in China
3.4.1 The development has been rapid
3.4.2 Data types are diverse and data resources are abundant
3.4.3 The advantage of late development is obvious
3.4.4 Inadequate integrated planning
3.4.5 The division of the functions of the government and administrative departments has led to the failure of closed loop management
3.4.6 The financial investment should be balanced
3.4.7 Insufficient sharing of data resources
3.4.8 Lack of industry talent
Chapter 4 Big Data Transportation: Eight Innovative Modes
4.1 Feature 1 of Big Data Transportation: Shared Economy
4.2 Feature 2 of Big Data Transportation: Full Utilization of Resources
4.3 Feature 3 of Big Data Transportation: Precise Demand
4.4 Feature 4 of Big Data Transportation: Real-Time Control
4.5 Feature 5 of Big Data Transportation: Efficiency and Convenience
4.6 Feature 6 of Big Data: Intelligence
Part II Application: Practical Implementation of Big Data Transportation
Chapter 5 The Entrance of Big Data Transportation
5.1 T-Union
5.1.1 Accuracy of the entrance of T-union data
5.1.2 Scientific features of the entrance of T-union
5.1.3 Wide application of T-union data
5.1.4 Future development of T-union data collection
5.2 GPS and BeiDou System
5.2.1 Data application of taxi onboard system
5.2.2 Operation and management and support of urban traffic
5.2.3 Movement data application of smartphone
5.3 Internet of Vehicles
5.3.1 Data exchange between vehicle and road facilities
5.3.2 Interconnected and interactive data of vehicles
5.3.3 Data exchange between vehicle and transportation management department
5.3.4 Data integrated service of Internet of Vehicles
5.4 Road Network Monitoring
5.4.1 Technical advantages of road network monitoring
5.5 Electronic Navigation Map
5.6 ETC
5.6.1 Highly efficient collection of vehicle passing information
5.6.2 Provision of analysis report to competent department
5.6.3 Accurate access to road travel data
5.6.4 Attempt to support charging to regulate traffic congestion
Chapter 6 The Platform of Big Data Transportation
6.1 Expressway Management Platform
6.1.1 Definition of the management requirements of expressway big data
6.1.2 Overall framework design of the platform
6.1.3 System data flow design
6.1.4 Data interface system design
6.2 Accident Detection Platform
6.2.1 Design of accident detection platform
6.2.2 Operation mode of accident detection platform
6.2.3 Location of traffic accident
6.3 Passenger Flow Detection Platform
6.3.1 Design of passenger flow detection platform
6.3.2 Passenger flow monitoring at key nodes
6.4 Traffic Law Enforcement Platform
6.4.1 Data cloud center for traffic law enforcement platform
6.4.2 Transportation integrated law enforcement coordination system
6.4.3 Traffic law enforcement information service system
6.5 Logistics Information Platform
6.5.1 Improving the operation function of logistics information platform with big data
6.5.2 Strengthening the ability to use big data information
6.5.3 Improving the security level of logistics information platform
6.6 Emergency Command Platform
6.6.1 Sharing of big data by emergency platform
6.6.2 Cloud emergency system
6.6.3 Application of mobile monitoring and emergency response
Chapter 7 Big Data Transportation and Logistics
7.1 Big Data Transportation and Transportation Organization
7.1.1 Transportation environment forecast
7.1.2 Location of transportation nodes
7.1.3 Optimization of transportation routes
7.1.4 Bin-location optimization
7.2 Big Data Transportation and Rural Logistics
7.2.1 Innovation of transportation service
7.2.2 Solving the problem of insufficient transportation capacity of the “last kilometer”
7.2.3 Speeding up the construction of rural logistics information network
7.3 Big Data Transportation and Urban Delivery
7.3.1 Government takes the lead to establish the urban logistics resources sharing platform
7.3.2 Industry alliance to build a sharing platform
7.3.3 Attaching importance to the construction of urban logistics and storage platform
7.4 Big Data Transportation and Express Logistics
7.4.1 Use of e-waybill in express logistics
7.4.2 Application of big data routing sorting
7.4.3 Big data technology for accidental circumstance management
7.5 Big Data Transportation and Cold Chain Logistics
7.6 Big Data Transportation and Multimodal Transportation
7.6.1 Application space of big data in railway supply chain
7.6.2 Optimization and scheduling of multimodal transportation routes
7.6.3 Improvement of container multimodal transportation promoted by big data
7.7 Big Data Transportation and Cross-Border Logistics
7.8 Big Data Transportation and Aviation Logistics
7.9 Big Data Transportation and Non-Truck Operating Common Carrier
7.9.1 Risk control system established and guaranteed by the big data
7.9.2 Improving the user experience and stickiness
7.9.3 Connecting with the public platform to ensure transportation quality
7.10 Big Data Transportation and Logistics Costs
7.10.1 Effective cost saving at planning level
7.10.2 Optimization of logistics cost accounting method for manufacturing enterprises
7.10.3 Mining potential demands of distribution customers to realize strategic extension
Chapter 8 Big Data Transportation and Transportation Planning
8.1 Big Data Transportation and Route Planning
8.1.1 Problems in traditional route planning
8.1.2 New mode of big data transportation planning
8.1.3 Construction of big data “traffic brain” in Zigong
8.2 Big Data Transportation and Network Line Planning
8.2.1 The significance of big data technology for network line planning
8.2.2 The integrity of network line planning
8.3 Big Data Transportation and Road Planning
8.3.1 Disadvantages of traditional road planning
8.3.2 New ideas of road planning brought by big data
8.3.3 Big data convenience of the road planning
8.4 Big Data Transportation and Station Planning
8.4.1 Application of big data in active parking system
8.4.2 Application of big data in bus station
8.4.3 Customized public transportation: Application of big data public transportation system
8.5 Big Data Transportation and Hub Planning
8.5.1 Exploration of big data in hub planning
8.5.2 Transportation hub between cities
8.6 Big Data Transportation and Capacity Planning
8.6.1 Comprehensive utilization of big data for transportation capacity
8.7 Big Data Transportation and Emergency Planning
8.7.1 Construction of traffic emergency system
8.7.2 Application of big data intelligent equipment
8.7.3 Operation mode of emergency mechanism
Chapter 9 Big Data Transportation and Major Activities
9.1 Big Data Transportation and Beijing Olympic Games
9.1.1 Equipment application of big data
9.1.2 Advance response to big data transportation
9.1.3 Application of big data system
9.2 Big Data Transportation and Shanghai Expo
9.2.1 Big data forecast
9.2.2 Utilization of big data intelligent system
9.3 Big Data Transportation and Hangzhou G20 Summit
9.3.1 Attention on big data transportation from government level
9.3.2 Support of big data for road traffic
9.3.3 Accurate prediction of big data
9.3.4 Rooting and sprouting of intelligent big data
9.4 Big Data Transportation and One-Belt-One-Road International Forum
9.4.1 Traffic restriction measures under big data
9.4.2 Application of Beijing intelligent transportation
Chapter 10 Big Data Transportation and Traffic Management
10.1 State Diagnosis of Big Data Transportation
10.1.1 Operation of information collection module
10.1.2 Application of big data analysis module
10.1.3 Application of traffic data processing module
10.2 Information Analysis of Big Data Transportation
10.2.1 Deficiency of traditional information analysis
10.2.2 Information analysis and promotion of big data model
10.2.3 Analysis and application of big data transportation information in Guiyang
10.3 Technological Change of Big Data Transportation
10.3.1 Upgrade of hardware equipment
10.3.2 New big data technology change
10.3.3 Shenzhen: Forerunner and leader of the use of big data transportation
10.4 Organization Model of Big Data Transportation
10.4.1 Big data model changes “information island” effect
10.4.2 Three-level management organization structure of big data
10.4.3 Organization system of big data transportation
10.5 Management Model of Big Data Transportation
10.5.1 Common big data management model
10.5.2 Upgrade of big data transportation management model
10.5.3 Hangzhou model: Comprehensive utilization of big data
10.6 Credit Model of Big Data Transportation
10.6.1 Multi-channels and professional releasing
10.6.2 Easy to understand and professional interpretation
10.6.3 Uniting the public security department to crack down on rumors
Chapter 11 Future Development of Big Data Transportation
11.1 Personalized Service of Big Data Transportation Industry
11.1.1 Intelligent vehicle–road collaboration technology
11.1.2 Autopilot technology
11.1.3 Internet vehicle
11.1.4 Rapid promotion of ETC technology
11.1.5 Further integration with individuals
11.1.6 “Going to the rural areas” for Internet taxi
11.2 Expansion Trend of Big Data Transportation Industry
11.2.1 The general trend of cross-border
11.2.2 The further development of sharing culture
11.2.3 New opportunities of big data intelligent navigation industry
11.2.4 Application of big data tachograph
11.3 Investment and Financing of Big Data Transportation Industry
11.3.1 Strategic cooperation between China Transinfo and Inrix
11.3.2 The financing probability of start-ups increases greatly
11.3.3 Investment in big data transportation industry is surging
11.4 Police Guidance of Big Data Transportation Industry
11.4.1 Definite support for the 13th Five-Year Plan
11.4.2 The State Council’s Guiding Opinions on Actively Promoting the “Internet +” Action
11.4.3 Notice of the Ministry of Transport
11.4.4 Implementation Plan of Intelligent Transportation Development
Chapter 12 Unmanned Driving: Transportation Revolution Sweeping Across the Globe
12.1 Origin, Development, and Application of Unmanned Driving Technology
12.1.1 Unmanned driving starting the new era of intelligent transportation
12.1.1.1 Profile of development in the unmanned driving technology
12.1.1.2 Direction of applying the unmanned driving technology
12.1.1.3 Bottlenecks in the development of unmanned driving technology
12.1.1.4 Future outlook for the unmanned driving technology
12.1.2 Four stages of the development of the unmanned driving technology
12.1.2.1 Level 0: No automation
12.1.2.2 Level 1: Automation at single-function level
12.1.2.3 Level 2: Partial automation
12.1.2.4 Level 3: Conditional automation
12.1.2.5 Level 4: Full automation (unmanned driving)
12.1.3 The evolutionary path of unmanned driving technology
12.1.3.1 Application of the unmanned driving technology
12.1.3.2 Promotion of the unmanned driving technology
12.1.3.3 Mission of the unmanned driving technology
12.1.4 The unmanned driving disrupting and reshaping the transportation ecology
12.1.4.1 Enhancing highway safety
12.1.4.2 Relief of traffic congestion
12.1.4.3 Reducing air pollution
12.2 Global Distribution: Competing for the High Ground of Unmanned Driving
12.2.1 Competitive pattern of the global unmanned driving industry
12.2.1.1 A look at the unmanned driving industry from California road test qualifications
12.2.1.2 The penetration rate of global automated driving will increase rapidly, and the market space may exceed hundreds of billions of dollars
12.2.1.3 Startups are an important force in the global unmanned driving industry promoting multi-industry integration
12.2.1.4 High-speed development of startups reshaping competitive landscape of the unmanned driving industry
12.2.2 Development of the unmanned driving technology around the world
12.2.2.1 Development of the unmanned driving technology in foreign countries
12.2.2.2 The development of the unmanned driving technology in China
12.2.3 Global prospects for commercial applications of unmanned driving
12.2.3.1 Public transportation
12.2.3.2 Express vehicles and industrial applications
12.2.3.3 Elderly and disabled people
12.2.4 World’s leading companies’ unmanned driving car research and development
12.2.4.1 Tesla planning to realize full unmanned driving
12.2.4.2 Volvo planning to achieve automated driving by 2021
12.2.4.3 Baidu planning to spin off its automated driving car business for mass production
12.2.4.4 Audi creating automated driving subsidiary
12.2.4.5 Microsoft seeking cooperation with automakers
12.2.4.6 Toyota’s “guardian angel”
12.3 Technology Routes: Key Technologies for the Unmanned Driving Industry
12.3.1 Key components of the unmanned driving technology
12.3.1.1 The systematic structure of automotive
12.3.1.2 Perception and identification of external environment
12.3.1.3 Position navigation system
12.3.1.4 Path planning technology
12.3.1.5 Vehicle control technology
12.3.2 Perceptual level: Collecting environmental and driving information
12.3.3 Decision-making level: Route planning and real-time navigation
12.3.4 Intelligent transport executive level: Precise control of the car’s operation
12.3.5 Application of unmanned driving in the field of intelligent transportation
12.3.6 The impact of unmanned vehicles on urban traffic flow
12.3.6.1 Analysis of factors related
12.3.6.2 Analysis of the introduction of the unmanned driving vehicles on different roads
12.4 Intelligent Traffic Management Model Based on the Unmanned Driving
12.4.1 Deep integration of free travel and shared modes
12.4.2 The unmanned driving taxi and the free travel model
12.4.3 Intelligent traffic management based on the integration of vehicles and roads
12.4.3.1 Classifying vehicles into different uses
12.4.3.2 Travel on separate roads
12.5 Key Factors in Unmanned Driving from Concept to Practice
12.5.1 Safety: The inevitable destination for unmanned driving development
12.5.2 Performance: The unmanned driving practice
12.5.3 Experience: Meeting the user’s lifestyle and entertainment needs
12.5.3.1 The optimization of appearance and styling, space layout, and basic functions
12.5.3.2 Providing communication office and life entertainment services based on the internet of vehicles
12.6 Application of the Unmanned Driving Technology in Urban Rail Transit
12.6.1 Profile of the application of domestic and foreign metro automation technology
12.6.1.1 Advantages of unmanned driving technology
12.6.1.2 Profile of the application of foreign unmanned driving technology in urban rail transit
12.6.1.3 Profile of the unmanned driving technology applications in China
12.6.2 Functional features of unmanned urban rail transit system
12.6.3 The requirements of the unmanned driving for urban rail transit
12.6.4 Difficulties in the application of the unmanned driving in urban rail transit
12.6.5 Solutions of urban rail transit based on unmanned driving
12.6.5.1 Guarantee of facilities and equipments
12.6.5.2 Innovative management model
12.6.5.3 Personnel Quality
12.6.5.4 Passengers’ cooperation
References
Index