Computational Intelligence for Sustainable Transportation and Mobility
- Length: 143 pages
- Edition: 1
- Language: English
- Publisher: Bentham Science Publishers
- Publication Date: 2021-12-16
- ISBN-10: 1681089459
- ISBN-13: 9781681089454
- Sales Rank: #0 (See Top 100 Books)
New technologies and computing methodologies are now used to address the existing issues of urban traffic systems. The development of computational intelligence methods such as machine learning and deep learning, enables engineers to find innovative solutions to guide traffic in order to reduce transportation and mobility problems in urban areas.
This volume, Computational Intelligence for Sustainable Transportation and Mobility, presents several computing models for intelligent transportation systems, which may hold the key to achieving sustainable development goals by optimizing traffic flow and minimizing associated risks. The book begins with the basic computational Intelligence techniques for traffic systems and explains its applications in vehicular traffic prediction, model optimization, behavior analysis, traffic density estimation, and more. The main objectives of this book are to present novel techniques developed, new technologies and computational intelligence for sustainable mobility and transportation solutions, as well as giving an understanding of some Industry 4.0 trends.
Readers will learn how to apply computational intelligence techniques such as multiagent systems (MAS), whale optimization, artificial Intelligence (AI), deep neural networks (DNNs) so that they can to develop algorithms, models, and approaches for sustainable transportation operations.
Key Features:
- Provides an overview of machine learning models and their optimization for intelligent transportation systems in urban areas
- Covers classification of traffic behavior
- Demonstrates the application of artificial immune system algorithms for traffic prediction
- Covers traffic density estimation using deep learning models
- Covers Fog and edge computing for intelligent transportation systems
- Gives an IoT and Industry 4.0 perspective about intelligent transportation systems to readers
- Presents a current perspective on an urban hyperloop system for India
Welcome Table of Content Title BENTHAM SCIENCE PUBLISHERS LTD. End User License Agreement (for non-institutional, personal use) Usage Rules: Disclaimer: Limitation of Liability: General: PREFACE List of Contributors An Intelligent Vehicular Traffic Flow Prediction Model Using Whale Optimization with Multiple Linear Regression Abstract Introduction The Proposed IVTFP Model WOA Based Feature Selection Model Prey Encircling Exploitation Phase Exploration Phase MLR Based Predictive Model Performance Validation Dataset Description Results Analysis CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS References Intelligent Transportation Systems-based Behavior Characteristics Classification Abstract INTRODUCTION Literature Survey Proposed Methodology Intelligent Transportation Systems Normal Behavior Drunk Behavior Fatigue Behavior Reckless Behavior Driver Information and Behavior Traveler Information and Network Behavior Rule-Based Fuzzy Polynomial Neural Network Result and Discussion Conclusion CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS REFERENCES Artificial Immune Systems Imputation-based Traffic Prediction Abstract Introduction Literature Survey Proposed Methodology Openflow Based Software-defined Optical Network Artificial Immune System Results and Discussion CONCLUSION CONSENT FOR PUBLICATION CONFLICT OF INTEREST ACKNOWLEDGEMENTS REFERENCES An Intelligent Transportation System for Traffic Density Estimation and Prediction Using Deep Learning Models Abstract Introduction The Proposed Model CNN Model LSTM Model Constant Error Carousel (CEC) Input Gate Output Gate Input Input Gate Forget Gate Memory Cell Output Gate Output Performance Validation Analysis of Density Estimation Analysis of Density Prediction CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS References Fog and Edge Computing-based Intelligent Transport System Abstract Introduction Fog Computing Overview Characteristics of Fog Fog Working Algorithm I Edge Computing Overview Characteristics of Edge Computing Computing Offloading Processing Caching Data Storage Intelligent Transportation System RELATED WORKS IMPLEMENTING ITS WITH FOG AND EDGE COMPUTING (PROTOTYPE) Algorithm – II Advantages of the Prototype CHALLENGES [16] CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS REFERENCES IoT-based Integration of Sensors with DAQ Systems in Intelligent Transport Systems Abstract INTRODUCTION Transportation Networks and Intelligent Transportation System RELATED WORKS Advanced Traffic Management Systems Advance Parking Management Systems Advance Lane Management System METHODOLOGY Sensors DAQ Systems Big Data Analytics Cloud Computing FUTURE WORKS CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS REFERENCES Solar-based Electric Vehicle Charging Infrastructure with Grid Integration and Transient Overvoltage Protection Abstract INTRODUCTION MATHEMATICAL MODELING Solar PV Array Boost Converter Battery Supercapacitor Three-phase AC Inverter Three-phase Induction Motor IEEE 5 Bus System PID Controller SYSTEM ARCHITECTURE Modes of Operation SIMULATION RESULTS Three-phase Induction Motor (IM) Load IEEE 5 Bus system Load Transient Overvoltage Protection CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS REFERENCES Industry 4.0: Hyperloop Transportation System in India Abstract INTRODUCTION Capsule Tube Propulsion Route DETAILED VIEW OF THE HYPERLOOP PASSENGER CAPSULE HOW DOES THE HYPERLOOP TRANSPORTATION SYSTEM WORK? COST ANALYSIS OF HYPERLOOP TRANSPORTATION SYSTEM IN INDIA SAFETY AND RELIABILITY OF THE HYPERLOOP TRANSPORTATION SYSTEM Onboard Passenger Emergency Power Outage Capsule Depressurization Earthquakes COMMUNICATION TECHNOLOGIES FOR HYPERLOOP RENEWABILITY OF THE HYPERLOOP TRANSPORTATION SYSTEM COMPARISON BETWEEN DIFFERENT MODES OF PUBLIC TRANSPORTATION FUTURE PLANS FOR HYPERLOOP TRANSPORTATION SYSTEM IN INDIA RELATED WORKS CONCLUSION CONSENT FOR PUBLICATION CONFLICTS OF INTEREST ACKNOWLEDGEMENTS REFERENCES
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