A Lane Departure and Forward Collision Warning System for Smartphones
Date Issued
2011
Date
2011
Author(s)
Dong, Wei-Yi
Abstract
Among the 200,000 yearly traffic accidents in Taiwan, 18.91% and 3.95% of the fatal automobile accidents are caused by driving distractions and not maintaining a safe distance from other vehicles, respectively. Hence, the objective of this thesis is to develop a driving assistance system on smart phones. This system will utilize computer vision algorithms to achieve detections of driving lanes and distance to the front vehicle in order to ensure the safety of the driver and others. We choose smart phones as our development platform because of their prevalence in current society in addition to their low cost and easy installation.
The methods used in this thesis use computer vision techniques as basis. Lane detection uses properties of the lane markers in order to extract their features for best fit line through Hough transform. Using different properties exhibited by the vehicles during the day and night time, our system can detect the front vehicle with robustness. During the day, edge detection and vehicle shadows are used while the characteristics of vehicle tail lights are exploited for vehicle detection at night. Experimental results show that our system is capable of achieving an average lane detection rate of 90% in different time of day and weather conditions. In addition, front-vehicle detection has an average detection rate of 80%. The performance of our system is also satisfactory since it only requires 0.2 second which satisfies the requirements for real-time driving assistance systems.
Subjects
driving assistance system
lane detection
vehicle detection
SDGs
Type
thesis
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