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This book introduces groundbreaking concepts for understanding and managing urban traffic congestion through the lens of the Ideal Flow Network (IFN). Developed over a decade of research, grounded in graph theory, information theory, and Markov chains principles, it reveals that every network has a natural, optimal steady-state flow distribution, which is an intrinsic property of a network's structure, independent of transient demand. The central thesis presents Premagic Equilibrium, a theoretical state where congestion is uniformly distributed across all links, and mathematically proves how this ideal resolves the classic tension between individual driver choices and system-wide efficiency. Planners will discover practical, data-light techniques to calibrate the model that sidesteps costly origin-destination matrices. Readers will explore a formal "chemistry of transport policy" where interventions are defined as auditable "atomic" and "molecular" actions. This approach provides a systematic grammar for policy design, simulation, and optimization. All of these original insights aim to provide an innovative theoretical solution to traffic congestion. With accessible mathematical explanations, step-by-step guides, and integration with practical tools such as IFN-Transport software (available as open source on GitHub and online in Revoledu.com) and an IFN Excel Add-In, this book empower readers to experiment with the theory and apply it to real-world situations. Illustrations, tables, and diagrams clarify complex ideas, making the content approachable for both professionals and students in transport engineering, urban planning, computer science, geography, and related fields. This book not only reveals hidden patterns in nature through the mathematics of IFN but also empowers readers to tackle traffic congestion creatively and ethically, offering theoretical and practical benefits to researchers, software developers, and problem solvers alike.
List of contents
Introduction to Mathematical Modelling.- Ideal Flow Network (IFN).- Graph Theory.- Linear Algebra.- Algebraic Graph Theory.- Stochastic Process.- Entropy.- Markov Chain.- Calculus Based Optimization.- Manual Computation of IFN.- IFN with Equal Outflow or Inflow.- Network Structure and Utilization.- Random Walk on Network.- Ideal Flow of Markov Chain.- Probabilities in IFN.- Trajectory Probability.- Modelling with Source and Sink in a Reducible Network.- Equivalent Ideal Flow Networks.- Premagic Capacity.- IFN based on Maximum Entropy.- Dual Network.- Link and Network Degree of Freedom.- Ideal Flow with Local Scaling.- Symmetric Ideal Flow Matrix.- Perturbation Analysis.- Eulerian Network.- Traffic Congestion Solutions.- Ideal Flow Model for Traffic Assignment.- Link Flow based IFN Calibration.- Link Flow Calibration Based on Maximum Entropy.- Model Comparison.- Intersection Analysis.- Dual Network Scenarios.- Flow Stochastic from Origin Destination (OD).- Intelligent Transportation System.- Braess Paradox.- Scenario Analysis using IFN.
About the author
Dr. Kardi Teknomo is an internationally recognized expert in the field of transportation engineering, applied mathematics, and computer science. He is best known for his pioneering work on the Ideal Flow Network, Teknomo-Fernandez algorithm, the queuing rule of thumb (QROT), as well as for his numerous educational tutorials in Revoledu.Com. With extensive experience as an international consultant for organizations such as the International Finance Corporation—World Bank Group, Toyota Corp, and Decathlon, has contributed significantly to advancing research and innovation in mobility systems worldwide. He held academic positions at Ateneo de Manila University (Philippines), Saga University (Japan), the University of Wisconsin (USA), Petra Christian University (Indonesia), and served as a Hertha Finberg Research Fellow at Austrian Institute of Technology. He is currently affiliated with the University of the Philippines Diliman School of Urban and Regional Planning.
