Traffic flow parameter acquisition method based on video and sensor

Abstract

The invention relates to a traffic flow parameter acquisition method, and discloses a traffic flow parameter acquisition method based on a video and a sensor. The method comprises the steps of video inputting, office learning, target detection, target tracking, online learning, video flow counting, sensor flow counting and multi-data fusing counting. According to the traffic flow parameter acquisition method based on the video and the sensor, a target detector is obtained through offline learning, and traffic video image is detected to rapidly determine the types and quantity of objects in a current video scene; a target track is determined by using target tracking, an online learning mechanism is adopted to intermittently update a target model and the feature vector thereof, and the target detector and a tracker are corrected to ensure that the target can be tracked continuously, and the traffic flow parameter information of a current road segment can be acquired accurately through video detection; moreover, traffic data acquired by the sensor in a road is analyzed through multi-data fusing counting, thereby further increasing the accuracy of the acquired traffic flow parameter data.

Description

technical field [0001] The invention relates to a traffic flow parameter collection method, in particular to a video and sensor-based traffic flow parameter collection method. Background technique [0002] With the continuous and rapid development of China's social economy and the rapid increase of motor vehicles, urban traffic problems are becoming more and more serious. In order to improve traffic management level and traffic operation efficiency, people put forward intelligent transportation system (Intelligent Transportation Systems, ITS). In the intelligent transportation system, the accurate acquisition of traffic parameters: such as traffic volume, average vehicle speed, distance between vehicles, time occupancy, space occupancy and density, etc., its research in intelligent transportation has very important theoretical significance and application value. [0003] At present, the main ways to obtain traffic parameters are: loop coil method, radar (microwave) method, ...

AI Technical Summary

Problems solved by technology

Due to the complex environment of the existing video-based traffic statistics methods, shape changes, changes in lighting conditions, scale changes, occlusions, etc. will inevitably occur, resulting in the loss of tracking targets and affecting the accuracy of traffic statistics

Images