Towards Automatic Road Mapping By Fusing Vehicle-borne Multi-sensor Data

Abstract

The demand of spatial data has been an explosive growth in the past 20 years. This demand has numerous sources and takes many forms, but it is an ever-increasing thirst for spatial data, which is more accurate and higher density (Called as High-Definition Spatial Data), which is produced more rapidly and acquired less expensively. This research aims to satisfy with the high demands for the road spatial data. We presents an automatic road mapping technology by fusing vehicle-based navigation data, stereo image and laser scanning data for collecting, detecting, recognizing and positioning road objects, such as road boundaries, traffic marks, road signs, traffic signal, road guide fences, electric power poles and many other applications important to people’s safety and welfare. In the hand of hardware, a hybrid inertial survey system (HISS) which combined an inertial navigation system (INS), two GPS receiver, and an odometer acquires the posture data was developed. Two sets of stereo camera systems are used to collect colour images and three laser scanners are employed to acquire range data for road and roadside objects. On the other hand, an advanced data fusion technology was developed for the purpose of precise/automatic road sign extraction, traffic mark extraction, and road fence extraction and so on, by fusing collected initial navigation data, stereo images and laser range data. The major contributions of this research are high-accuracy object positioning and automatic road mapping by fusion-based processing of multi-sensor data. A lot of experiments were performed to certify and check the accuracy and efficiency of our fusion-based automatic road mapping technology. From achieved results of these experiments, our developed vehicle borne multi-sensor based mobile mapping system is efficient system for generating high-accuracy and high-density 3D road spatial data more rapidly and less expensively.