Journal of Computer Science and Technology Studies

Yazarlar: farhat ullah, Muhammad Imad, Muhammad Abul Hassan, Hazrat Junaid, Faiza, Izaz Ahmad

Konular:-

Anahtar Kelimeler:Traffic Sign,Traffic Light,Road Lane,Pedestrian,Cone,Car,Machine Learning,Deep Learning,Autonomous vehicle,Driverless Car

Özet: Advanced Driver Assistance Systems (ADAS) apply to various high-tech in-vehicle systems designed to enhance road traffic protection by making drivers become more mindful of the road and its potential hazards, as well as other vehicles around them. The design of traffic sign, traffic light, traffic cone, car, road lane, pedestrian and road blocker detection and Recognition, a significant ADAS subsystem, has been a problem for many years and thus becomes an essential and successful research topic in the field of smart transport systems. This paper present different approaches Devised over the last 3 years for the diverse modalities. We present a survey of each challenge in form of table in terms of “algorithm, parameter, result, advantage, and disadvantage. For each survey, we describe the possible implementations suggested and analyze their underlying assumptions, while impressive advancements were demonstrated at limited scenarios, inspection into the needs of next generation systems reveals significant gaps. We identify these gaps in disadvantage block and suggest research directions that may bridge them. we identify the future solutions proposed and examine their underlying assumptions, although promising development has been shown in restricted contexts, analysis of next-generation applications requirements shows significant gaps. We define certain holes in the block of drawbacks and propose avenues for work that can cross them.

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