VHDMap-SE: A Universal Vectorized High-Definition Map Aided Vehicle State Estimator

Abstract

As unmanned ground vehicles (UGVs) applications expand to large-scale and open road scenarios, vectorized high-definition maps (VHD maps) demonstrate greater potential in solving state correction problems than traditional metric maps. Previous related studies typically employ proprietary versions of VHD maps without fully leveraging the common traffic elements' information. In addition, there is a lack of research on efficient interaction methods between UGVs and VHD maps. To fill these gaps, we propose a universal UGV state estimation system and a query-based VHD map data exchange protocol. The system utilizes VHD maps to correct the lateral and longitudinal positions as well as the yaw orientation of UGVs. The data exchange protocol enables UGVs to obtain real-time VHD map information and process it efficiently. To ensure universality, we accommodate two widely used VHD map formats, ASAM OpenDRIVE and Apollo OpenDRIVE and provide corresponding map parsing methods. The evaluation of the system is conducted both in simulated and real-world scenes. In the simulation experiments, we fully measure the effectiveness and accuracy of our method, as well as its sensitivity to measurement noise. In real-world experiments, we compare the state estimation accuracy of our system with SOTA simultaneous localization and mapping methods on an open road. The results show that our system demonstrates better accuracy than other baselines on most data sequences. The proposed map data exchange protocol meets real-time requirements.