Map building with radar and motion sensors for automated highway vehicle navigation

Our long term goal is to integrate the position-based navigation with visual road following in order to build a more robust and reliable road navigation system. In this paper, we describe the first part of the project: constructing a navigation system that can build maps of highways and landmarks, and use those feature for position-based navigation. Speed and yaw rate gyro sensors are used for vehicle motion detection, and a millimeter wave radar system is used for landmark detection. To achieve position estimation and error correction, we use an extended Kalman filter. First, a map is built without previous knowledge of landmarks while human drives the vehicle. Then, at the stage of autonomous navigation, the previously produced map is used for position estimation. The experimental results show that a map produced by the proposed method can be used for later navigation, and that vehicle position is estimated accurately.