Intelligent dynamic traffic light sequence using RFID

Al-Khateeb, Khalid A. Saeed; Johari, Jaiz A. Y

doi:10.1109/iccce.2008.4580829

Cited by 25 publications

(14 citation statements)

References 9 publications

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“…Plot designed in sub-image (b) of Fig. 4 compares their amounts through different frames • False detection rate (Al-Khateeb et al, 2008) is the third quantitative factor used in this research. Actually, it is equal to the number of pixels which the difference between their values and the value of corresponding pixel in the adapted background calculated with the less combination rate is more than a user predefined threshold (γ).…”

Section: Resultsmentioning

confidence: 99%

A Block-Based Multi-Scale Background Extraction Algorithm

Davarpanah¹

2010

Journal of Computer Science

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Problem statement: To extract the moving objects, vision-based surveillance systems subtract the current image from a predefined background image. The efficiency of these systems mainly depends on accuracy of the extracted background image. It should be able to adapt to the changes continuously. In addition, especially in real-time applications the time complexity of this adaptation is a critical matter. Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. Because of being less sensitive to local movements, block-based techniques are proper to control the non-stationary objects' movements, especially in outdoor applications. They can be useful to reduce the effect of these objects on the extracted background. We also used the blocking method to intelligently select the regions which the temporal filtering has to be applied on. In addition, an amended multi-scale algorithm is introduced. This algorithm is a hybrid algorithm, a combination of some nonparametric and parametric filters. It uses a nonparametric filter in the spatial domain to initiate two primary backgrounds. In continue two adapted two-dimensional filters will be used to extract the final background. Results: The qualitative and quantitative results of our experiments certify not only the quality of the final extracted background is acceptable, but also its time consumption is approximately half in compare to the similar methods. Conclusion: Using Multi scaling filtering and applying the filters just to some selected nonoverlapped blocks reduce the time consumption of the extracting background algorithm.

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Section: Resultsmentioning

confidence: 99%

A Block-Based Multi-Scale Background Extraction Algorithm

Davarpanah¹

2010

Journal of Computer Science

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“…A lot of research has been done on TLCs which use different technologies e.g. [4,7,8,10,13] just to mention a few. Recently, two TLCs have been proposed based on WSNs too [15,9].…”

Section: Traffic Light Controllersmentioning

confidence: 99%

UTOSPF with Waiting Times for Green Light consideration

Faez

Khanjary

2009

2009 IEEE International Conference on Systems, Man and Cybernetics

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Recently, the authors proposed a distributed dynamic route guidance system called UTOSPF (Urban Traffic Open Shortest Path First) based on Wireless Sensor Networks (WSNs) and Open Shortest Path First (OSPF) protocol. In UTOSPF, the routes will be found only based on Estimated StreetTravel Times (ESTTs) which will be needed to pass the streets and regardless of Waiting Times for Green Light (WTGLs) which drivers spend behind the red lights. In this paper, a simple method will be proposed to involve the WTGLs in calculation of optimal routes and its simulation results will be presented. Simulation results show that this method can improve the average speed of vehicles up to 66% as compared to random routes and up to 27% as compared to original UTOSPF, in the simulated scenarios.

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“…Niittymaki in [12] presented a field test of a simple two-phase fuzzy signal controller. The results showed that the fuzzy logic controller performed better than vehicle-actuated control in terms of delay, percentage stops and savings in fuel and emissions.…”

Section: Related Workmentioning

confidence: 99%

Mobile Road Traffic Management System Using Weighted Sensor

Akinboro

Adeyiga

Omotosho

et al. 2017

Int. J. Interact. Mob. Technol.

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Abstract-Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion has become a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model was simulated and the performance was assessed using response time, delay and throughput. Results showed that, mobile devices are capable of assisting road users' in faster decision making by providing real-time traffic information and recommending alternative routes.

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Intelligent dynamic traffic light sequence using RFID

Abstract: The proposed RFID

Cited by 25 publications

References 9 publications

A Block-Based Multi-Scale Background Extraction Algorithm

A Block-Based Multi-Scale Background Extraction Algorithm

UTOSPF with Waiting Times for Green Light consideration

Mobile Road Traffic Management System Using Weighted Sensor

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