Implementation paper of Traffic Signal Detection and Recognition using deep learning

Abstract

Traffic boards and traffic signals are used to maintain proper traffic through busy roads. They help to recognize the rules to follow when driving the vehicle. These signs warn the distracted driver, and prevent his/her actions which could lead to an accident. We have proposed a system which can help recognize these boards and signals at real time thus avoiding major mishap. A real-time automatic sign detection and recognition can help the driver, significantly increasing his/her safety. Lately traffic sign recognition has got an immense interest lately by large scale companies such as Google, Apple and Volkswagen etc. which is driven by the market needs for intelligent applications such as autonomous driving, driver assistance systems (ADAS), mobile mapping, Mobil eye, Apple, etc. Hence, here, we have implemented to do the same with cost efficient manner using Raspberry Pi. The proposed system detects the traffic board or traffic signals, capture its image which through deep learning approach recognizes the same to give result on dashboard as well it gives the measures of distance from front obstacle which helps to implement brake system if obstacle is near. PiCam is used to capture images of traffic sings and is connected to RaspberryPi. Monitor is used to display required output, showing type of sign and distance of collision. This proposal will avoid large number of accidents occurring at bridges and work in progress area due to automated braking system and simultaneous reduce death ratio.