• Spoorthi D N
• Ashwini B P

Today, safety is one of the important key factors for everyone. With the increase in the number of automobiles on the urban roads, highways face many challenges in traffic regulations. Advanced Driver Assistance Systems (ADAS) provides more optimistic way in controlling and managing the accidents and road traffic. It also ensures the safety and provides better driving experience. Vehicle detection is one of the basic and important components in the ADAS technology. Vehicle detection provides a necessary data to solve the problem of traffic management. Precisely detecting the vehicles in real time is difficult and also the challenging task in the field of research. Recently deep learning has manifest favorable in resolving the innumerable computer vision task such as object recognition, detection. In this survey, latest developments of the models for vehicle detection are discussed and compared based on the analysis of architecture and their performance.

Vehicle detection, deep learning, object detection, ADAS, traffic management

"Real Time Vehicle Detection Using Deep Neural Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.306-311, May-2019, Available :http://www.jetir.org/papers/JETIRCD06054.pdf

"Real Time Vehicle Detection Using Deep Neural Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp306-311, May-2019, Available at : http://www.jetir.org/papers/JETIRCD06054.pdf