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Informed Urban Transport Systems examines how information gathered from new technologies can be used for optimal planning and operation in urban settings. Transportation researche… Read more
LIMITED OFFER
Immediately download your ebook while waiting for your print delivery. No promo code needed.
Informed Urban Transport Systems examines how information gathered from new technologies can be used for optimal planning and operation in urban settings. Transportation researchers, and those from related disciplines, such as artificial intelligence, energy, applied mathematics, electrical engineering and environmental science will benefit from the book’s deep dive into the transportation domain, allowing for smarter technological solutions for modern transportation problems. The book helps create solutions with fewer financial, social, political and environmental costs for the populations they serve.
Readers will learn from, and be able to interpret, the information and data collected from modern mobile and sensor technologies and understand how to use system optimization strategies using this information. The book concludes with an evaluation of the social and system impacts of modern transportation systems.
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
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
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