| ISBN13: | 9781032574646 |
| ISBN10: | 103257464X |
| Binding: | Hardback |
| No. of pages: | 242 pages |
| Size: | 234x156 mm |
| Weight: | 607 g |
| Language: | English |
| Illustrations: | 85 Illustrations, color; 10 Halftones, color; 75 Line drawings, color |
| 681 |
Data Analytics and Machine Learning for Integrated Corridor Management
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This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.
In an era defined by rapid urbanization and ever-increasing mobility demands, effective transportation management is paramount. This book takes readers on a journey through the intricate web of contemporary transportation systems, offering unparalleled insights into the strategies, technologies, and methodologies shaping the movement of people and goods in urban landscapes.
From the fundamental principles of traffic signal dynamics to the cutting-edge applications of machine learning, each chapter of this comprehensive guide unveils essential aspects of modern transportation management systems. Chapter by chapter, readers are immersed in the complexities of traffic signal coordination, corridor management, data-driven decision-making, and the integration of advanced technologies. Closing with chapters on modeling measures of effectiveness and computational signal timing optimization, the guide equips readers with the knowledge and tools needed to navigate the complexities of modern transportation management systems.
With insights into traffic data visualization and operational performance measures, this book empowers traffic engineers and administrators to design 21st-century signal policies that optimize mobility, enhance safety, and shape the future of urban transportation.
Chapter 1 Introduction
Chapter 2 Traffic Engineering and operations background
Chapter 3 Integrated Corridor Management System
Chapter 4 Traffic Data Modalities
Chapter 5 Data Mining and Machine Learning
Chapter 6 Traffic Simulation Frameworks for Data Generation
Chapter 7 Intersection Detector Diagnostics
Chapter 8 Intersector Performance
Chapter 9 Interruption Detection
Chapter 10 Estimating Turning Movement Counts
Chapter 11 Coordinating Corridors
Chapter 12 Modeling Input Output Behavior of Intersection
Chapter 13 Modeling Measures of Effectiveness for Intersection Performance
Chapter 14 Signal Timing Optimizations
Chapter 15 Visualisation of Traffic Data
