Imitation learning for end-to-end autonomous driving has drawn attention from academic communities. Current methods either only use images as the input which is ambiguous when a car approaches an intersection, or use additional command information to navigate the vehicle but not automated enough. Focusing on making the vehicle drive along the given path, we propose a new navigation command that does not require human's participation and a novel model architecture called angle branched network. Both the new navigation command and the angle branched network are easy to understand and effective. Besides, we find that not only segmentation information but also depth information can boost the performance of the driving model. We conduct experiments in a 3D urban simulator and both qualitative and quantitative evaluation results show the effectiveness of our model. Preprint. Work in progress.
This article concerns a hybrid vehicle suspension system that can regenerate energy from vibrations. To further improve the performance of the hybrid vehicle suspension system, the design of the energy-regenerative circuit is investigated. First, the force tests of the linear motor used in the hybrid vehicle suspension were carried out, and the key parameters of the linear motor were obtained. Then, the selection procedures of the protective resistance, inductance, and initial terminal voltage of the super capacitor were discussed. These aforementioned parameters' values were determined by considering the impact of the hybrid suspension on the dynamic performance indexes and the energy-regenerative efficiency. Simulations showed that, in comparison to the original hybrid suspension system, the designed hybrid suspension effectively improved the energy-regenerative efficiency, and that the dynamic performance indexes of the suspension were synchronously improved. Given the result of the simulation analysis, which were validated by bench tests, it is shown that the optimized energy-regenerative circuit presents an enhanced regeneration efficiency, with an improvement of nearly 13% compared to the original suspension system.
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