Informed Urban Transport Systems

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.

• 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

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