Next Article in Journal
Detail Preserved Surface Reconstruction from Point Cloud
Next Article in Special Issue
A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification
Previous Article in Journal
A Technological Review of Wearable Cueing Devices Addressing Freezing of Gait in Parkinson’s Disease
Previous Article in Special Issue
A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing
Article Menu
Issue 6 (March-2) cover image

Export Article

Open AccessArticle

Internet of Vehicles and Cost-Effective Traffic Signal Control

Department of Computer Science and Engineering, University of Seoul, Seoul 02504, Korea
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(6), 1275; https://doi.org/10.3390/s19061275
Received: 31 January 2019 / Revised: 8 March 2019 / Accepted: 8 March 2019 / Published: 13 March 2019
(This article belongs to the Special Issue Future Research Trends in Internet of Things and Sensor Networks)
  |  
PDF [1616 KB, uploaded 13 March 2019]
  |  

Abstract

The Internet of Vehicles (IoV) is attracting many researchers with the emergence of autonomous or smart vehicles. Vehicles on the road are becoming smart objects equipped with lots of sensors and powerful computing and communication capabilities. In the IoV environment, the efficiency of road transportation can be enhanced with the help of cost-effective traffic signal control. Traffic signal controllers control traffic lights based on the number of vehicles waiting for the green light (in short, vehicle queue length). So far, the utilization of video cameras or sensors has been extensively studied as the intelligent means of the vehicle queue length estimation. However, it has the deficiencies like high computing overhead, high installation and maintenance cost, high susceptibility to the surrounding environment, etc. Therefore, in this paper, we propose the vehicular communication-based approach for intelligent traffic signal control in a cost-effective way with low computing overhead and high resilience to environmental obstacles. In the vehicular communication-based approach, traffic signals are efficiently controlled at no extra cost by using the pre-equipped vehicular communication capabilities of IoV. Vehicular communications allow vehicles to send messages to traffic signal controllers (i.e., vehicle-to-infrastructure (V2I) communications) so that they can estimate vehicle queue length based on the collected messages. In our previous work, we have proposed a mechanism that can accomplish the efficiency of vehicular communications without losing the accuracy of traffic signal control. This mechanism gives transmission preference to the vehicles farther away from the traffic signal controller, so that the other vehicles closer to the stop line give up transmissions. In this paper, we propose a new mechanism enhancing the previous mechanism by selecting the vehicles performing V2I communications based on the concept of road sectorization. In the mechanism, only the vehicles within specific areas, called sectors, perform V2I communications to reduce the message transmission overhead. For the performance comparison of our mechanisms, we carry out simulations by using the Veins vehicular network simulation framework and measure the message transmission overhead and the accuracy of the estimated vehicle queue length. Simulation results verify that our vehicular communication-based approach significantly reduces the message transmission overhead without losing the accuracy of the vehicle queue length estimation. View Full-Text
Keywords: Internet of Vehicles; Internet of Things; traffic signal control; vehicle queue; vehicular communication Internet of Vehicles; Internet of Things; traffic signal control; vehicle queue; vehicular communication
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Ahn, S.; Choi, J. Internet of Vehicles and Cost-Effective Traffic Signal Control. Sensors 2019, 19, 1275.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top