WSN Based Road Vehicle Detection And Fusion Study Using Video And Magnetic Sensor

The issue of vehicle detection is the basic and key problem in Intelligent Traffic System Technology, as some basic traffic parameters that are acquired by vehicle detection, such as traffic flow, average vehicle speed and road duty-cycling rate are important foundation of implementation of high-level traffic management application like route guidance and traffic control. Traditional vehicle detection methods use only one type of sensor. However, constrained by the characteristic of sensor, there are always some disadvantages for single-type-sensor method to do vehicle detection. As the development of wireless sensor network technology, people have noticed that vehicle detection problem can be solved by using wireless network which is self-organized and constructed by nodes containing various types of sensor. In this way, system cost will be cut down and system robustness will be increased. Moreover, we can obtain more accurate traffic parameters by using multi-sensor methods.This paper is focus on wireless sensor network environment based video & magnetic sensor vehicle detection algorithm and multi-sensor data fusion. As video sensor is sensitive to change of lightness while magnetic sensor is not, magnetic sensor can be used to complement video sensor in vehicle detection when video is disabled in day-night transformation and complex weather situation.An improved video detection algorithm is presented in this thesis. The algorithm use edge information to reduce noise points which was caused by video shaking, so as to increase the robustness of algorithm, and use ROI area-shrinking method to increase efficiency. This Algorithm has low calculation complexity and good real-time performance, and has good detection result in multi-roadway situation. The experimental result shows high detection accuracy. And a new magnetic vehicle detection algorithm called adaptive window length algorithm is presented in the thesis. In the...