Lidar‐Binocular Camera‐Integrated Navigation System for Underground Parking

It is well known that vehicles highly rely on satellite navigation in an open intelligent traffic environment. However, satellite navigation cannot obtain accurate positioning information for vehicles in the interior of underground garage, as they comprise a semienclosed navigation space, worse light than outdoors in a special traffic environment. To address this problem in this research, the Lidar‐binocular camera‐integrated navigation system (LBCINS) is established for underground parking indoor environment. The obtained Lidar data from the simulation experiment are preprocessed, and the matching results of the inertial navigation system (INS) under the normal distributions transform (NDT) algorithm and the iterative closest point (ICP) algorithm are compared. The simulation experiment results show that in the complex underground parking environment, the INS under Lidar‐NDT algorithm with binocular camera achieves a better performance. Then, in the field experiment, the 3D cloud point data were collected by the test vehicle that equipped with the proposed navigation system from an underground parking and obtained 199 pairs of feature points’ distances. Finally, four different statistical methods were used to analyze the calculated distance errors. Results show that under different error statistical methods, the distance error values of the proposed navigation system are 0.00901, 0.059, 0.00766, and 0.087 m, respectively which present a much higher precision than 5.0 m in the specification requested for inertial‐integrated navigation terminal.