Context-Aware Intelligent Traffic Light Control through Secure Messaging
In this paper, we propose STCM, a context-aware secure traffic control model to manage competing traffic flows at a given intersection by using secure messages with real-time traffic information. The vehicle is modeled as a virtual sensor which reports the traffic state, such as its speed and locati...
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2018/4251701 |
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doaj-37d259271ca44b10a6803fb348ffdd142020-11-24T21:27:43ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/42517014251701Context-Aware Intelligent Traffic Light Control through Secure MessagingMükremin Özkul0Ilir Capuni1Elton Domnori2Department of Computer Engineering, Epoka University, Tirana 1039, AlbaniaAdvanced Computing Research Center, University of New York Tirana, Tirana 1000, AlbaniaDepartment of Computer Engineering, Epoka University, Tirana 1039, AlbaniaIn this paper, we propose STCM, a context-aware secure traffic control model to manage competing traffic flows at a given intersection by using secure messages with real-time traffic information. The vehicle is modeled as a virtual sensor which reports the traffic state, such as its speed and location, to a traffic light controller through a secure and computationally lightweight protocol. During the reporting process, a vehicle’s identity and location are kept anonymous to any other vehicle in the system. At an intersection, the traffic light controller receives the messages with traffic information, verifies the identities of the vehicles, and dynamically implements and optimizes the traffic light phases in real-time. Moreover, the system is able to detect the presence of emergency vehicles (such as ambulances and fire fighting trucks) in the communication range and prioritize the intersection crossing of such vehicles to in order to minimize their waiting times. The simulation results demonstrate that the system significantly reduces the waiting time of the vehicles in both light and heavy traffic flows compared to the pretimed signal control and the adaptive Webster’s method. Simulation results also yield effective robustness against impersonating attacks from malicious vehicles.http://dx.doi.org/10.1155/2018/4251701 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mükremin Özkul Ilir Capuni Elton Domnori |
spellingShingle |
Mükremin Özkul Ilir Capuni Elton Domnori Context-Aware Intelligent Traffic Light Control through Secure Messaging Journal of Advanced Transportation |
author_facet |
Mükremin Özkul Ilir Capuni Elton Domnori |
author_sort |
Mükremin Özkul |
title |
Context-Aware Intelligent Traffic Light Control through Secure Messaging |
title_short |
Context-Aware Intelligent Traffic Light Control through Secure Messaging |
title_full |
Context-Aware Intelligent Traffic Light Control through Secure Messaging |
title_fullStr |
Context-Aware Intelligent Traffic Light Control through Secure Messaging |
title_full_unstemmed |
Context-Aware Intelligent Traffic Light Control through Secure Messaging |
title_sort |
context-aware intelligent traffic light control through secure messaging |
publisher |
Hindawi-Wiley |
series |
Journal of Advanced Transportation |
issn |
0197-6729 2042-3195 |
publishDate |
2018-01-01 |
description |
In this paper, we propose STCM, a context-aware secure traffic control model to manage competing traffic flows at a given intersection by using secure messages with real-time traffic information. The vehicle is modeled as a virtual sensor which reports the traffic state, such as its speed and location, to a traffic light controller through a secure and computationally lightweight protocol. During the reporting process, a vehicle’s identity and location are kept anonymous to any other vehicle in the system. At an intersection, the traffic light controller receives the messages with traffic information, verifies the identities of the vehicles, and dynamically implements and optimizes the traffic light phases in real-time. Moreover, the system is able to detect the presence of emergency vehicles (such as ambulances and fire fighting trucks) in the communication range and prioritize the intersection crossing of such vehicles to in order to minimize their waiting times. The simulation results demonstrate that the system significantly reduces the waiting time of the vehicles in both light and heavy traffic flows compared to the pretimed signal control and the adaptive Webster’s method. Simulation results also yield effective robustness against impersonating attacks from malicious vehicles. |
url |
http://dx.doi.org/10.1155/2018/4251701 |
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