Sensor Fusion-Based Low-Cost Vehicle Localization System for Complex Urban Environments

This paper proposes a sensor fusion-based low-cost vehicle localization system. The proposed system fuses a global positioning system (GPS), an inertial measurement unit (IMU), a wheel speed sensor, a single front camera, and a digital map via the particle filter. This system is advantageous over previous methods from the perspective of mass production. First, it only utilizes low-cost sensors. Second, it requires a low-volume digital map where road markings are expressed by a minimum number of points. Third, it consumes a small computational cost and has been implemented in a low-cost real-time embedded system. Fourth, it requests the perception sensor module to transmit a small amount of information to the vehicle localization module. Last, it was quantitatively evaluated in a large-scale database.