| Summary: | 碩士 === 中原大學 === 通訊工程碩士學位學程 === 102 === In this thesis, we propose a driving assistance system based on the traffic lights recognition and prediction. We use a smart phone to recognize traffic lights and predict traffic light duration. This system can assist drivers to drive on the road more safe and effective.
In this thesis, we will present our system architecture and model. At first, we introduce our system model includes recognition, prediction, voice notification and driving speed monitoring. Second, we use the smart phone camera to recognize traffic lights. We use the Sobel filter to do edge detection, then we limit the width and length to locate the traffic signal. After that, we convert the frame from RGB to HSI which helps us for traffic lights statue recognition. Third, the prediction of the traffic light duration and the traffic congestion situation is achieved by receiving other cars’ recognition data. Through Wi-Fi Direct 802.11g, it transfers the traffic lights statue information to drivers to know the next traffic signal statue. Fourth, we add safe-drive model to assist drivers to drive more safe on the road. The voice notification and driving speed monitoring will remind drivers the traffic lights statue while the camera recognizes the traffic lights. Finally, we will present the simulation experiments and the comparison with the other researches.
The contributions of our research are as follows:
1.Solve the costly problem of intelligent transportation system’s core device like on board unit (OBU) and road side unit (RSU). It can be more widely implemented in the city.
2.Propose a more practical system, not only recognize traffic signals but also predict the traffic signal duration and traffic congestion situation.
3.To ensure driving safety, we add voice notification and driving speed monitoring to assist drivers to drive on the road.
4.Avoid driving into the traffic congestion road.
5.Provide a better driving environment for the color-blind patients.
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