Internet of Things Enabled Vehicular and Ad Hoc Networks for Traffic Monitoring and Controlling in Smart Cities

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 3500

Special Issue Editors

Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand
Interests: IoT; smart cities; congestion; data dissemination model; vehicular communication; request processing
Department of Computer Engineering, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: mobile ad hoc networks; vehicular networks; mobile communication; computer networks; wireless networks; MANETs; VANETs
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Special Issue Information

Dear Colleagues,

Traffic Congestion is becoming a huge issue in the cities of both developing and developed countries. One prominent solution is to solve this issue in terms of smart cities. In smart cities, all end points, including people, houses, buildings, and vehicles, are connected to each other through some networking technology. The most considered technologies include Internet of Things (IOT) and adhoc networks. The smart city project can also be applied through the combination of IOT and adhoc networks. The literature studies show that very little work has been done on the combination of traffic congestion, IOT, and adhoc networks in terms of smart cities. Furthermore, to improve the communication reliability in VANETs, extensive research is required along with data models to determine the storage and processing communication demands and time dependency of road side communication assistance.

The goal of the special issue is to present an overview of advanced technologies related to the smart city-based traffic management and communication mechanism in VANETs. 

Topics of interest include, but are not limited to:

  • Intelligent transportation systems
  • Communication protocols in VANETs
  • Navigation and positioning in ITS
  • Intelligent vehicles
  • Robotics and automation

Dr. Tanveer Ahmad
Prof. Dr. Juan-Carlos Cano
Guest Editors

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Keywords

  • IoT
  • Congestion
  • Smart city
  • Adhoc networks
  • Navigation
  • Positioning

Published Papers (1 paper)

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Research

15 pages, 4333 KiB  
Article
An Intersection Signal Control Mechanism Assisted by Vehicular Ad Hoc Networks
by Zhen Cai, Zizhen Deng, Jinglei Li, Jinghan Zhang and Mangui Liang
Electronics 2019, 8(12), 1402; https://doi.org/10.3390/electronics8121402 - 25 Nov 2019
Cited by 6 | Viewed by 2298
Abstract
The urban intersection signal decision-making in traditional control methods are mostly based on the vehicle information within an intersection area. The far vehicles that have not reached the intersection area are not taken into account, which results in incomplete information and even incorrectness [...] Read more.
The urban intersection signal decision-making in traditional control methods are mostly based on the vehicle information within an intersection area. The far vehicles that have not reached the intersection area are not taken into account, which results in incomplete information and even incorrectness in decision-making. This paper presents an intersection signal control mechanism assisted by far vehicle information. Using the aid of real-time information collection for far vehicles through vehicular ad hoc networks (VANETs), we can consider them together and calculate the accumulative waiting time for each intersection traffic flow at a future moment to make the optimal signal decision. Simulation results show that, under three different traffic flow environments—same even traffic flows, same uneven traffic flows, and different traffic flows—the two proposed implementation schemes based on the mechanism (fixed phase and period timing improvement scheme, and dynamic phase and period control scheme) show good performances, in which the average waiting time and the ratio of long-waiting vehicles are both less than the results of the traditional signal timing scheme. Especially, in the second scheme, the waiting time was reduced by an average of 38.6% and the ratio of long-waiting vehicles was reduced by an average of 7.67%. Full article
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