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
Author(s): Deepak Gupta, Suresh Chavhan
Series: Computational Intelligence For Data Analysis
Publisher: Bentham Science Publishers
Year: 2021
Language: English
Pages: 143
City: Sharjah
Cover
Title
Copyright
End User License Agreement
Contents
Preface
List of Contributors
An Intelligent Vehicular Traffic Flow Prediction Model Using Whale Optimization with Multiple Linear Regression
Hima Bindu Gogineni1, E. Laxmi Lydia2,* and N. Supriya3
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
B.M.S. Rani1, E. Laxmi Lydia2,* and G. Jose Moses3
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
M. Vasumathi Devi1, E. Laxmi Lydia2,* and Hima Bindu Gogineni3
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
Irina V. Pustokhina1, Denis A. Pustokhin2, M. Ilayaraja3 and K. Shankar4,*
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
B. Sai Viswanath1,*, P. Sandeep1 and Suresh Chavhan2
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
Dhananjay Kumar K.S.1, Prakash Reddy O.1, Sanath Gowtham G.1, Shailaja A. Chougule1 and Suresh Chavhan2
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
Bibaswan Bose1,*, Vijay Kumar Tayal1 and Bedatri Moulik1
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
Pranjal Kapur1,* and Suresh Chavhan2
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
Subject Index
Back Cover
