Editors: Deepak Gupta, Suresh Chavhan

Series Title: Computational Intelligence For Data Analysis

Computational Intelligence for Sustainable Transportation and Mobility

Volume 1

eBook: US $49 Special Offer (PDF + Printed Copy): US $90
Printed Copy: US $65
Library License: US $196
ISSN: 2810-9457 (Print)
ISSN: 2810-9465 (Online)
ISBN: 978-1-68108-944-7 (Print)
ISBN: 978-1-68108-943-0 (Online)
Year of Publication: 2021
DOI: 10.2174/97816810894301210101

Introduction

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

This volume is essential reading for scholars and professionals involved in courses and training programs in the field of transportation, computer science, data science and applied machine learning.

Contributors

Editor(s):
Deepak Gupta
Maharaja Agrasen Institute of Technology
Rohini
Delhi
India


Suresh Chavhan
Automotive Research Centre
Vellore Institute of Technology
Vellore
India




Contributor(s):
B.M.S. Rani
Vignan's Nirula Institute of Technology and Science for Women
Guntur, India


B. Sai Viswanath
School of Electronics and Communication Engineering
Vellore Institute of Technology, Vellore
India


Bedatri Moulik
Department of Electrical and Electronics
Amity University Uttar Pradesh
Noida, India


Bibaswan Bose
Department of Electrical and Electronics
Amity University Uttar Pradesh
Noida, India


Deepak Gupta
Maharaja Agrasen Institute of Technology
Rohini
Delhi
India


Denis A. Pustokhin
State University of Management
Moscow, Russian Federation


Dhananjay Kumar K.S.
Department of Embedded Technology
School of Electronics Engineering, Vellore Institute of Technology
Vellore
India


E. Laxmi Lydia
Department of Computer Science and Engineering
Vignan's Institute of Information Technology (Autonomous)
Visakhapatnam
India


G. Jose Moses
Department of Computer Science and Engineering
Raghu Engineering College, Visakhapatnam
India


Hima Bindu Gogineni
Department of Computer Applications
Vignan's Institute of Information Technology (Autonomous)
Visakhapatnam, India


Irina V. Pustokhina
Plekhanov Russian University of Economics
Moscow, Russian Federation


K. Shankar
Department of Computer Applications, Alagappa University
Karaikudi
India


M. Ilayaraja
Department of Computer Science and Information Technology
Kalasalingam Academy of Research and Education
Krishnankoil, India


M. Vasumathi Devi
Department for Computer Science and Engineering
Vignan's Nirula Institute of Technology and Science for Women
Guntur
India


N. Supriya
Department of Computer Science and Engineering
Raghu Institute of Technology
Visakhapatnam
India


P. Sandeep
School of Electronics and Communication Engineering
Vellore Institute of Technology, Vellore
India


Prakash Reddy O.
Department of Embedded Technology
School of Electronics Engineering, Vellore Institute of Technology
Vellore
India


Pranjal Kapur
School of Electronics and Communication Engineering
Vellore Institute of Technology
Vellore, India


Sanath Gowtham G.
Department of Embedded Technology
School of Electronics Engineering, Vellore Institute of Technology
Vellore
India


Shailaja A. Chougule
Department of Embedded Technology
School of Electronics Engineering, Vellore Institute of Technology
Vellore
India


Suresh Chavhan
Automotive Research Centre
Vellore Institute of Technology, Vellore
India


Vijay Kumar Tayal
Department of Electrical and Electronics
Amity University Uttar Pradesh
Noida, India