A Vision-based Detection System of Vehicle Motion and Traffic Signal Transition

• Main Authors: Lin, Bing-Sheng, 林秉聖
• Other Authors: Chuang, Jen-Hui
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/29172773013596828435

碩士 === 國立交通大學 === 資訊學院資訊學程 === 101 === In general, Driving Assistance Systems continuously monitor surrounding environment, providing information to assist human driver, in order to increase safety and convenience. By observation we found when stopping at a long-waiting traffic signal, a driver may be distracted by other tasks and not focus on traffic. When it is time to go, he or she may block the traffic or be honked by the rear car for blocking the traffic, if he or she does not move. This thesis provides a vision-based detection system which reminds the driver while it is time to start moving. The system includes three modules: (1) a spatiotemporal-profile-based or scan-line-based ego-motion detection mechanism which determines whether the driver’s vehicle is moving, (2) a Gentle AdaBoost-based vehicle detector finds possible front vehicles and sends notifications once they move, and (3) a traffic signal detector based on color/shape attributes and a background model finds possible candidates and notifies the driver once the traffic signal turns green. This system tries to provide a convenient functionality that assists people in easing driving effort in such a less critical condition. Experiments show when a driver stops at a red traffic signal in day-time urban areas, this detecting system sends notifications at a recall of 95.5% and a precision of 87.5%, therefore prevents a driver from blocking the traffic.