Informed Urban Transport Systems
Classic and Emerging Mobility Methods toward Smart Cities
Description
Key Features
- Takes a fresh look at transportation systems analysis and design, with an emphasis on urban systems and information/data use
- Serves as a focal point for those in artificial intelligence and environmental science seeking to solve modern transportation problems
- Examines current analytical innovations that focus on capturing, predicting, visualizing and controlling mobility patterns
- Provides an overview of the transportation systems benefitting from modern technologies, such as public transport, freight services and shared mobility service models, such as bike sharing, peer-to-peer ride sharing and shared taxis
Readership
Transportation system professionals, and urban planning researchers and practitioners. Non-transportation researchers, such as computer science, energy, economics, environmental science, and electrical engineering, interested in transportation. State and federal transportation and urban policy decisions makers, and planners
Table of Contents
Part A: Fundamentals
1. Urban Transport Systems
1.1 Introduction
1.2 Urban Transport Systems (UTS): Definitions
1.3 Examples of the Need for UTS Engineers
1.4 Manheim-Florian-Gaudry (MFG) Framework
1.5 A Simulation Tool for Evaluating UTS: MATSim
1.6 Use Case Motivations for Book Chapters
Research and Design Challenges
2. Monitoring Mobility in Smart Cities
2.1 Introduction
2.2 Smart Cities, Big Data, and the Internet of Things
2.3 Monitoring Mobility
2.4 Time Geography
2.5 Travel Momentum Fields (TMFs)
2.6 TMF: Transport Route Projections
2.7 TMF: Before-After Analysis
Research and Design Challenges
Part B: Evaluation of Informed Systems
3. Network Equilibrium Under Congestion
3.1 The Need to Evaluate Congestion Effects
3.2 User Equilibrium in Road Networks
3.3 Fixed Route Transit Assignment
3.4 Other Equilibria
3.5 Transport Systems as Two-Sided Markets
Research and Design Challenges
4. Market Schedule Equilibrium for Multimodal Systems
4.1 The Need to Evaluate Activity Scheduling Behavior
4.2 Complexity of Activity Scheduling
4.3 A Model of User Activity Scheduling Behavior
4.4 Market Schedule Equilibrium for a Transport System
4.5 Urban Freight Activity Analysis
Research and Design Challenges
Part C Learning From Public Information
5. Inverse Transportation Problems
5.1 Introduction
5.2 Machine Learning Applications in Urban Transport
5.3 Inverse Transportation Problems
5.4 Multiagent Inverse Transportation Problems
5.5 Network Learning
Research and Design Challenges
6. Privacy in Learning
6.1 Introduction
6.2 User Privacy
6.3 Operator Competitive Privacy Control
6.4 Network Learning With Privacy Awareness
Research and Design Challenges
Part D Design of Informed Systems
7. Network Design
7.1 Introduction
7.2 Network Design Problems
7.3 Bilevel Network Design
7.4 Network Design Under Coexisting Systems
Research and Design Challenges
8. Network Portfolio Management
8.1 Introduction
8.2 Decision-Making Under Uncertainty
8.3 Optimal Timing Under Uncertainty: Real Options Methods
8.4 Operating Mode Switching Under Uncertainty
8.5 Sequential Network Design and Timing
Product details
- No. of pages: 490
- Language: English
- Copyright: © Elsevier 2018
- Published: July 25, 2018
- Imprint: Elsevier
- Paperback ISBN: 9780128136133
- eBook ISBN: 9780128136140