Avoiding Vehicle Collisions Using GPS and Off-The-Shelf Camera

• Main Authors: Yung-Ting Chen, 陳勇廷
• Other Authors: 孫敏德
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/592a76

碩士 === 國立中央大學 === 資訊工程學系 === 105 === As more and more vehicles are on the road, the number of traffic accidents increases each year. To battle with the traffic accidents, one possible mean is to predict the future trajectory of the vehicle so that the driver can be informed when a possible collision is detected in advance. In this thesis, an algorithm for vehicle's future trajectory prediction is proposed. Although the similar research topic has been studied for many years, most of the existing solutions make use of expensive external sensors, which makes these solutions difficult to be adopted for the general public. On the contrary, our proposed trajectory prediction algorithm collects data from simple and inexpensive sensors like GPS and off-the-shelf camera. The radius of the vehicle from CAMP is adopted in our vehicle path prediction algorithm. The GPS data, such as latitude and longitude, can be used to localize/predict the current/future position of the vehicle. The turn detection data obtained from camera is used to determine if the host vehicle is making a turn. The driver's reaction time is taken into account as a delay to improve the accuracy of the prediction. The experiment results indicate that the position deviation between the predicted position and the ground truth has been significantly reduced by using our algorithm.