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IJSTR >> Volume 3- Issue 10, October 2014 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Advanced Centralised Rto

[Full Text]

 

AUTHOR(S)

Arati Singh, Sachin Pandey

 

KEYWORDS

Index Terms: Congestion, Dedicated short range, Solenoide, RYG, FUZZY Mode, Normal Mode

 

ABSTRACT

Abstract: Advanced Centralized RTO is a project in which the traffic is regulated depending on the vehicle density .It also consists of detecting those vehicles which break the signal and the message will go to owner that he has break signal and suppose to pay fine within limited interval of time. In case if fine is not paid then petrol tank will automatically get locked. For tracking vehicle density there will be 16 sensors on 4 way road such that 4 sensors on each road. If sensor one detects the vehicle then the signal will be on for minimum time and if all 4 sensors detects vehicles then signal will be on for already set maximum time. It can be further used to collect toll tax automatically, Reduce bribery among traffic personnel, To keep track of vehicles violating speed limits, Car theft can be easily found out, Exact location of car can be detected if GPS is installed.

 

REFERENCES

[1] Gangadhar, S. Instrum. Technol., R N Shetty Inst. of Technol., Bangalore, India ― An intelligent road traffic control system- E-ISBN :978-1-4244-5974-2-11308515

[2] Remy Chang, Tarak Gandhi and Mohan M. Trivedi, "Computer vision for multi-sensory structural health monitoring system," IEEE International Transportation Systems Conference, October 2004.

[3] Rita Cucchiara, Massimo Piccardi and Paola Mello, "Image analysis and rule-based reasoning for a traffic monitoring system," IEEE Transactions on Intelligent Transportation Systems, June 2000.

[4] Erhan bas, A. Murat Tekalp, F. Sibel Salman, "Automatic vehicle counting from video for traffic flow analysis," IEEE Transactions on Intelligent Transportation Systems, June 2007.

[5] Y. Liu and P. Payeur, "Vision-based detection of activity for traffic control," Canadian Conference on Electrical and Computer Engineering, 2003.

[6] Andrea Prati, Ivana Mikic, Mohan M. Trivedi and Rita Cucchiara, "Detecting moving shadows: Algorithms and evaluation," IEEE Transactions on Pattern Analysis and Machine Intelligence, July 2003.