articleEgyptian Informatics JournalApr 13, 2022GOLD OA

Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques

National College of Business Administration and Economics · Skyline University College · +3 more institutions

Indexed incrossrefdoaj

Abstract

Smart cities have been developed over the past decade, and reducing traffic congestion has been the top concern in smart city development. Short delays in communication between vehicles and Roadside Units (RSUs), smooth traffic flow, and road safety are the key challenges of Intelligent Transportation Systems (ITSs). The rapid upsurge in the number of road vehicles has increased traffic congestion and the number of road accidents. To fix this issue, Vehicular Networks (VNs) have developed many new ideas, including vehicular communications, navigation, and traffic control. Machine Learning (ML) is an efficient approach to finding hidden insights into ITS without being programmed explicitly by learning from…

Citation impact

337
total citations
FWCI
35.19
Percentile
100%
References
60
Citations per year

Authors

6

Topics & keywords

Keywords
  • Computer science
  • Intelligent transportation system
  • Traffic congestion
  • Floating car data
  • Traffic flow (computer networking)
  • Network congestion
  • Traffic congestion reconstruction with Kerner's three-phase theory
  • Advanced Traffic Management System
UN Sustainable Development Goals
  • Sustainable cities and communities
No related works found for this paper.