A Fusion Method for Localization of Intelligent Vehicles in Carparks

• Main Authors: Dinh-Van Nguyen, Trung-Kien Dao, Eric Castelli, Fawzi Nashashibi
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Autonomous vehicle; fusion; Gaussian mixture; GPS-denied environment; intelligent vehicles; localization
• Online Access: https://ieeexplore.ieee.org/document/9097221/

With the increasing demand for urban space, more and more multistory carparks are needed as they will play a central role in the city transportation system. An autonomous navigation solution for Intelligent Vehicles in these indoor scenarios is then required. One step to solve this problem is to localize Intelligent Vehicles in these specific environments. However, the lack of GPS due to signal obstruction (multipath, non-line of sight, interference, etc.) appears to be a significant concern for any localization system, let alone indoor ones. Hence, in this paper, a wireless sensor network based approach is proposed to replace the GPS (Global Positioning System) role for indoor environments. In addition, a fusion framework for multiple sensors such as Wi-Fi access points, Inertial Measurement Unit (IMU) or LiDAR is studied. Experiments in almost one-year duration yield a stable result of mean global localization error at 0.5m.