We propose a distributed bundle adjustment (DBA) method using the exact Levenberg-Marquardt (LM) algorithm for super large-scale datasets. Most of the existing methods partition the global map to small ones and conduct bundle adjustment in the submaps. In order to fit the parallel framework, they use approximate solutions instead of the LM algorithm. However, those methods often give suboptimal results. Different from them, we utilize the exact LM algorithm to conduct global bundle adjustment where the formation of the reduced camera system (RCS) is actually parallelized and executed in a distributed way. To store the large RCS, we compress it with a block-based sparse matrix compression format (BSMC), which fully exploits its block feature. The BSMC format also enables the distributed storage and updating of the global RCS. The proposed method is extensively evaluated and compared with the state-of-the-art pipelines using both synthetic and real datasets. Preliminary results demonstrate the efficient memory usage and vast scalability of the proposed method compared with the baselines. For the first time, we conducted parallel bundle adjustment using LM algorithm on a real datasets with 1.18 million images and a synthetic dataset with 10 million images (about 500 times that of the state-of-the-art LM-based BA) on a distributed computing system.

Steering torque feedback provides drivers with road feel and haptic feedback on vehicle motion, which are necessary for drivers to properly operate vehicles. Therefore, simulating steering torque feedback with sufficient fidelity is of great significance to systems without actual steering systems, such as driving simulators and steer-by-wire systems. In this paper, a steering torque feedback model is developed and a global sensitivity analysis method is used to identify the influence degree of each model parameter on steering feel properties for on-center performance. The analysis results provide useful guidelines on how to configure steering characteristics to obtain accurate and tunable steering feel.