Road infrastructure data acquisition using a vehicle-based mobile mapping system

This study presents the technology of a vehicle-based mobile mapping system to maintain an updated transportation database. The mobile mapping system that integrates the global positioning system (GPS), the inertial navigation system (INS), and digital cameras has been developed to collect data on position and attributes of road infrastructure. The vehicle-based mobile mapping system works by having the GPS and INS record the position and attitude data, and digital cameras take road images. The stereo vision system can determine the position of objects that are visible on the image pair in the global coordinate system with GPS and INS data. As field data acquisition is a very expensive task, a mobile mapping system offers a greatly improved solution. In this study, we successfully created a road infrastructure map with mobile mapping technology and proposed automatic algorithms for detecting and identifying road signs from road images. The proposed detection algorithm includes line and color region extraction processes and uses the Hopfield neural networks. The identification algorithm uses seven invariant moments and parameters that present geometric characteristics. With this combined method, we could successfully detect and identify road signs.