Traffic Flow Theory
Characteristics, Experimental Methods, and Numerical Techniques
- 1st Edition - October 22, 2015
- Author: Daiheng Ni
- Language: English
Creating Traffic Models is a challenging task because some of their interactions and system components are difficult to adequately express in a mathematical form. Traffic Flow… Read more
Creating Traffic Models is a challenging task because some of their interactions and system components are difficult to adequately express in a mathematical form. Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques provide traffic engineers with the necessary methods and techniques for mathematically representing traffic flow. The book begins with a rigorous but easy to understand exposition of traffic flow characteristics including Intelligent Transportation Systems (ITS) and traffic sensing technologies.
- Includes worked out examples and cases to illustrate concepts, models, and theories
- Provides modeling and analytical procedures for supporting different aspects of traffic analyses for supporting different flow models
- Carefully explains the dynamics of traffic flow over time and space
Transportation Engineers, Traffic Engineers, Traffic System Designers, Highway Engineers and undergraduate and graduate students
- Dedication
- Preface
- Part I: Traffic Flow Characteristics
- Chapter 1: Traffic Sensing Technologies
- Abstract
- 1.1 Traffic Sensors
- 1.2 Traffic Sensor Classification
- 1.3 Data Sources
- Problems
- Chapter 2: Traffic Flow Characteristics I
- Abstract
- 2.1 Mobile Sensor Data
- 2.2 Point Sensor Data
- 2.3 Space Sensor Data
- 2.4 Time-Space Diagram and Characteristics
- 2.5 Relationships among Characteristics
- 2.6 Desired Traffic Flow Characteristics
- Problems
- Chapter 3: Traffic Flow Characteristics II
- Abstract
- 3.1 Generalized Definition
- 3.2 Three-Dimensional Representation of Traffic Flow
- Problems
- Chapter 4: Equilibrium Traffic Flow Models
- Abstract
- 4.1 Single-Regime Models
- 4.2 Multiregime Models
- 4.3 The State-of-the-Art Models
- 4.4 Can We Go any Further?
- Problems
- Chapter 1: Traffic Sensing Technologies
- Part II: Macroscopic Modeling
- Chapter 5: Conservation Law
- Abstract
- 5.1 The Continuity Equation
- 5.2 First-Order Dynamic Model
- Problems
- Chapter 6: Waves
- Abstract
- 6.1 Wave Phenomena
- 6.2 Mathematical Representation
- 6.3 Traveling Waves
- 6.4 Traveling Wave Solutions
- 6.5 Wave Front and Pulse
- 6.6 General Solution to Wave Equations
- 6.7 Characteristics
- 6.8 Solution to the Wave Equation
- 6.9 Method of Characteristics
- 6.10 Some Properties
- Problems
- Chapter 7: Shock and Rarefaction Waves
- Abstract
- 7.1 Gradient Catastrophes
- 7.2 Shock Waves
- 7.3 Rarefaction Waves
- 7.4 Entropy Condition
- 7.5 Summary of Wave Terminology
- Problems
- Chapter 8: LWR Model
- Abstract
- 8.1 The LWR Model
- 8.2 Example: LWR with Greenshields Model
- 8.3 Shock Wave Solution to the LWR Model
- 8.4 Riemann Problem
- 8.5 LWR Model with a General q-k Relationship
- 8.6 Shock Path and Queue Tail
- 8.7 Properties of the Flow-Density Relationship
- 8.8 Example LWR Model Problems
- Problems
- Chapter 9: Numerical Solutions
- Abstract
- 9.1 Discretization Scheme
- 9.2 FREFLO
- 9.3 FREQ
- 9.4 KRONOS
- 9.5 Cell Transmission Model
- Problems
- Chapter 10: Simplified Theory of Kinematic Waves
- Abstract
- 10.1 Triangular Flow-Density Relationship
- 10.2 Forward Wave Propagation
- 10.3 Backward Wave Propagation
- 10.4 Local Capacity
- 10.5 Minimum Principle
- 10.6 Single Bottleneck
- 10.7 Computational Algorithm
- 10.8 Further Note on the Theory of Kinematic Waves
- Problems
- Chapter 11: High-Order Models
- Abstract
- 11.1 High-Order Models
- 11.2 Relating Continuum Flow Models
- 11.3 Relative Merits of Continuum Models
- 11.4 Taxonomy of Macroscopic Models
- Problems
- Chapter 5: Conservation Law
- Part III: Microscopic Modeling
- Chapter 12: Microscopic Modeling
- Abstract
- 12.1 Modeling Scope and Time Frame
- 12.2 Notation
- 12.3 Benchmarking Scenarios
- Problems
- Chapter 13: Pipes and Forbes Models
- Abstract
- 13.1 Pipes Model
- 13.2 Forbes Model
- 13.3 Benchmarking
- Problems
- Chapter 14: General Motors Models
- Abstract
- 14.1 Development of GM Models
- 14.2 Microscopic Benchmarking
- 14.3 Microscopic-Macroscopic Bridge
- 14.4 Macroscopic Benchmarking
- 14.5 Limitations of GM Models
- Problems
- Chapter 15: Gipps Model
- Abstract
- 15.1 Model Formulation
- 15.2 Properties of the Gipps Model
- 15.3 Benchmarking
- Problems
- Chapter 16: More Single-Regime Models
- Abstract
- 16.1 Newell Nonlinear Model
- 16.2 Newell Simplified Model
- 16.3 Intelligent Driver Model
- 16.4 Van Aerde Model
- Problems
- Chapter 17: More Intelligent Models
- Abstract
- 17.1 Psychophysical Model
- 17.2 CARSIM Model
- 17.3 Rule-based Model
- 17.4 Neural Network Model
- 17.5 Summary of Car-Following Models
- Problems
- Chapter 12: Microscopic Modeling
- Part IV: Picoscopic Modeling
- Chapter 18: Picoscopic Modeling
- Abstract
- 18.1 Driver, Vehicle, and Environment
- 18.2 Applications of Picoscopic Modeling
- Problems
- Chapter 19: Engine Modeling
- Abstract
- 19.1 Introduction
- 19.2 Review of Existing Engine Models
- 19.3 Simple Mathematical Engine Models
- 19.4 Validation and Comparison of the Engine Models
- 19.5 Conclusion
- 19.A A Cross-Comparison of Engine Models
- Chapter 20: Vehicle Modeling
- Abstract
- 20.1 Overview of the DIV Model
- 20.2 Modeling Longitudinal Movement
- 20.3 Modeling Lateral Movement
- 20.4 Model Calibration and Validation
- Problems
- Chapter 21: The Field Theory
- Abstract
- 21.1 Motivation
- 21.2 Physical Basis of Traffic Flow
- 21.3 The Field Theory
- 21.4 Simplification of the Field Theory
- 21.5 Discussion of the Field Theory
- 21.6 Summary
- Problems
- Chapter 22: Longitudinal Control Model
- Abstract
- 22.1 Introduction
- 22.2 The LCM
- 22.3 Model Properties
- 22.4 Empirical Results
- 22.5 Applications
- 22.6 Related Work
- 22.7 Summary
- Problems
- Chapter 18: Picoscopic Modeling
- Part V: The Unified Perspective
- Chapter 23: The Unified Diagram
- Abstract
- 23.1 Motivation
- 23.2 A Broader Perspective
- 23.3 The Unified Diagram
- 23.4 Summary
- Problems
- Chapter 24: Multiscale Traffic Flow Modeling
- Abstract
- 24.1 Introduction
- 24.2 The Spectrum of Modeling Scales
- 24.3 The Multiscale Approach
- 24.4 Summary
- Problems
- Chapter 23: The Unified Diagram
- Bibliography
- Index
- Edition: 1
- Published: October 22, 2015
- Language: English
DN
Daiheng Ni
Dr. Ni has been a Professor at UMass Amherst since 2006. At the Georgia Institute of Technology, he earned his PhD in Transportation and Operations Research in 2004, his MSc in Industrial Engineering in 2003, his MSc in Transportation in 2001, and his MSc in Mechanical Engineering at the Beijing Agricultural Engineering University in 1994. His research interests focus on traffic flow modeling and simulation, intelligent transportation systems, traffic sensing and information technology, connected and automated vehicles. He is an Associate Editor for the Journal of Intelligent Transportation Systems (Taylor & Francis) and a ‘friend’ member of the TRB Committee on Traffic Flow Theory and Characteristics (ACP50).
Affiliations and expertise
Professor, Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, MA, USARead Traffic Flow Theory on ScienceDirect