• Aswathy VN
• Satish B Basapur

The motorists or driver are provided with opulent information travel environment with the help of connected vehicle technology. The developing size of towns and growing population mobility have decided a fast boom in the number of motors at the roads, which has resulted in lots of demanding situations for road visitors management authorities in relation to traffic congestion, accidents and air pollution. Over the latest years, researchers from each enterprise and academia were focusing their efforts on exploiting the advances in sensing, communique and dynamic adaptive technologies to make the prevailing traffic management systems (TMS) more efficient to deal with the above problems in smart cities .In any case, these endeavors are as yet deficient to construct a dependable and secure TMS that can deal with the predictable ascent of populace and vehicles in shrewd urban communities. In this paper, we present an exceptional survey of the various innovations utilized in the various stages included in a TMS, and examine the potential utilization of savvy vehicles and internet based life to empower quick and increasingly exact traffic congestion location and moderation. The connected vehicle solution is expected to be the next frontier for automotive revolution and the key to the evolution to next generation intelligent transportation systems. This paper focus on different data mining techniques used for decision concerning the cause of urban traffic congestion via connected vehicle technology.

Connected vehicle, Traffic Management system, Machine Learning.

"Incident based Traffic Classification via Connected Vehicle", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.292-294, June 2019, Available :http://www.jetir.org/papers/JETIR1906P45.pdf

"Incident based Traffic Classification via Connected Vehicle", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp292-294, June 2019, Available at : http://www.jetir.org/papers/JETIR1906P45.pdf