AUTOMATION IN TRAFFIC CONTROL USING DIP

e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:02/Issue:09/September-2020

Impact Factor- 5.354

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AUTOMATION IN TRAFFIC CONTROL USING DIP Keta Patel *1, Shubhangi Sambare *2, Gaurav Patil *3 *1,2,3 Department of Electronics and Telecommunication Engineering, Savitribai Phule Pune University, India. *4,5 Associate Professor in Pimpri-Chinchwad College of Engineering And Research, Ravet. Department of Electronics and Telecommunication Engineering, Savitribai Phule Pune University, India.

ABSTRACT Road traffic is steadily growing around the worldwide coming about into blockage which has become a significant worry for the vehicle the executive's pros and chiefs. The current fixed time strategies for traffic light administration, reconnaissance, and control are not enough effective. The proposed framework is the Traffic Management System utilizing Density Calculation. Picture preparing based versatile traffic signal framework comprises of four significant parts: a telephone camera mounted on a drive engine, which is a DC engine and introduced at every crossing point, a PC with MATLAB for picture handling undertakings, and an Atmega32 processor for controlling DC engine and traffic signal signs.

After the pictures have been caught and prepared by PC, on time is doled out to each flag as per its traffic thickness. Every crossing point is allocated to a special code that can turn the signed green.

KEYWORDS: Traffic light signal, image processing, foreground detection, vehicle count.

I.

INTRODUCTION

Insufficient traffic signal control frameworks in significant urban communities of creating nations particularly in India has brought about gridlock issues. These fixed planning signals are not attractive in light of the fact that they don't consider the real street conditions accordingly delivering gridlock issues.

The postponements presented by these signs are antagonistically influencing personal satisfaction just as the earth. Individuals lose time, pass up on chances, and get disappointed. Likewise, this traffic prompts monetary emergencies in the nation. One answer to defeating these issues is to develop new streets, under-passes, fly-over; upgrade open vehicles, and present intercity trains. However, the accessibility of free space forces a major issue in making a new foundation, and furthermore the natural harm because of these improvements must be thought of. bigger zone. Consequently, they are utilized for vehicle following especially for vehicle tallies and speed estimations. Consequently, there is a need to improve the current traffic signal framework so as to deal with the traffic stream on the streets. Picture preparing based versatile traffic light toward the finish of the paper. the framework comprises of four significant segments: a camera mounted on a camera drive engine, which is a DC engine and introduced at every crossing point, a PC with MATLAB for picture handling undertakings, and an Atmega32 processor for controlling DC engine and traffic signal signs. After the pictures have been caught and handled by PC, on time is allowed to each flag as indicated by its traffic thickness. Every convergence is doled out an exceptional code that can turn the sign green Use of Traffic cameras is a financially savvy arrangement and is adaptable for checking traffic. They can be orchestrated and indirectly controlled and can cover zones of eagerness with its dish and zoom office enabling incorporation in a greater locale. Thus, they are used for vehicle following particularly for vehicle checks and speed assessments.

II.

METHODOLOGY

The proposed framework is actualized in Matlab with a target to decrease the traffic dependent on thickness. Four principle steps are considered for the framework: a) picture securing b) RGB to grayscale change c) picture improvement and d) morphological activities. A camera is introduced and used to catch a video of the expressway. The video is recorded ceaselessly in continuous casings and each casing is contrasted with the underlying caught picture. The absolute number of vehicles present in the video is discovered utilizing picture preparing calculations. In the event that the complete number of vehicles surpasses a predefined edge, hefty traffic status is shown as a message. The square chart of our proposed model appears in Fig. 1 www.irjmets.com

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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:02/Issue:09/September-2020

Impact Factor- 5.354

www.irjmets.com

Fig-1 1) Capture Image This is the initial step or the cycle of major computerized picture handling. In this segment, the first picture is obtained utilizing the camera focal point 2) Convert RGB to dark To change over the RGB to dark, include the three hues R, G, and B and gap it by 3 to get the grayscale picture 3) Resize picture 256*256 J = imresize (I, SCALE) J = imresize (I,[num columns num cols]) This grammar is utilized to resize the picture in 256*256 4) Preprocessing difference splendor alter The splendor and the difference is balanced in this part 5) Segmentation utilizing edge It is the way toward apportioning the picture in various portions or change the portrayal of the picture.

6) Count the vehicle In light of the picture portions, the vehicles are tallied.

7) Send a sign to the microcontroller Subsequent to getting the check of vehicles, the tally is sent to the microcontroller for additional cycle

III.

MODELING AND ANALYSIS

The primary parts required for this framework are equipment, interfacing and programming module Hardware Module: A telephone camera to catch pictures of the traffic on street. The equipment module comprises of an Arduino board used to control LEDs speaking to the red and green lights. A clock module is utilized to show the rest of the time Software Module: MATLAB variant R2016a is utilized as the picture preparing programming which involves particular modules that perform explicit errands. Matlab coding is finished utilizing the reference and caught pictures. Interfacing: A webcam is interfaced with the framework and Arduino is interface Matlab utilizing sequential correspondence. www.irjmets.com

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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:02/Issue:09/September-2020

Impact Factor- 5.354

www.irjmets.com

The calculation behind the square chart comprises of the accompanying advances.

1.

Start program

2. Capture picture of the clear street by the associated camera module for reference 3. Capture picture with vehicles 4. The pictures are changed over from RGB to dark 5. Find the distinction between outlines utilizing a limit 6. Add Gaussian clamor to the distinction yield 7. Apply Weiner channel to it to channel the masses 8. Convert to a paired picture 9. Fill openings to the masses 10. Open all masses having a region more noteworthy than 2000 11. Determine the number of vehicles 12. Display the yield picture 13. The tally of vehicles is found and shown.

IV.

RESULTS AND DISCUSSION

Simulation results of the proposed system are shown in . Fig. 2(a) shows the captured image of the road with two cars, Fig. 2(b) indicates the road without vehicles, Fig. 2(c) represents the segmented image and output image after enhancement is shown in Fig.

V.

CONCLUSION

We have decided the traffic thickness by estimating the all-out region involved by vehicles out and about and utilized it as traffic thickness. We have set a variable traffic cycle contingent upon the all-out traffic thickness of the considerable number of streets at the intersection. Contingent upon the traffic thickness weight is resolved for every street and the complete traffic cycle is weighted for the streets. Along these lines, a robotized traffic signal framework might be planned. This model could be reached out to fuse an enormous number of interconnected traffic intersections and utilizing their traffic thickness to change neighboring intersection's time portion.

VI.

REFERENCES

[1] Ninad Lanke , Sheetal Koul (International Journal of Computer Applications (0975 – 8887) Volume 75– No.7, August 2013). Smart Traffic Management System. ( www.ijcaonline.org)

[2] P.M. Xavier, Raju Nedunchezhia (IJRET: International Journal of Research in Engineering and www.irjmets.com

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e-ISSN: 2582-5208 International Research Journal of Modernization in Engineering Technology and Science Volume:02/Issue:09/September-2020

Impact Factor- 5.354

www.irjmets.com

Technology (eISSN: 2319-1163 | pISSN: 2321- 7308)Volume: 03 Special Issue: 15 | Dec-2014 | IWCPS-2014) A comparative study on road traffic managem systems. ( www.ijret.org)

[3] Farheena Shaikh, Dr. Prof. M. B. Chandak (IOSR Journal of Computer Science (IOSR-JCE) -2014 e-ISSN: 2278-0661, p-ISSN: 2278-8727 PP 24-27 ) An Approach towards Traffic Management System using Density Calculation and Emergency Vehicle Alert. (www.iosrjournals.org)

[4] Saima Maqbool*, Ulya Sabeel, Nidhi Chandra Rouf-Ul-Alam Bha(Volume 3, Issue 6, June 2013 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Soft Engineering Research Paper )

[5] Courtesy of MathWorks - MATLAB and Simulink for TechnicalComputing.URL: http://www.mathworks.com

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