Purpose-The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue. Design/methodology/approach-This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted. Findings-This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car. Originality/value-The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

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Traditional studies simplify vehicle-track-tunnel system into vehicle-track or vehicle-tunnel models and neglect dynamics influences of vehicle on tunnel through track or track-tunnel on vehicle. This study established the mathematical model of vehicle and finite element model of track-tunnel to disclose vibration characteristics of vehicle-track-tunnel coupled dynamic system. Next, a vehicletrack-tunnel dynamic coupled model was established based on the wheel-rail displacement coordinated relation. Finally, variation laws of vehicle and stress and displacement fields of tunnel surrounding rock when the train travelled at speed of 200 km/h were studied under different track slab stiffness and track structures. Numerical simulation results demonstrate that vehicle vibration indexes change in the linear law with the increase in track slab stiffness. Sleeper embedded ballastless slab track has better damping reduction performance than sleeper buried ballastless slab track. The best damping reduction performance is achieved when the track slab stiffness is 3.5 kPa. The maximum vertical displacement and stress of the tunnel surrounding rock due to vibration at low levels and the tunnel surrounding rock slightly influence vibration indexes of vehicles.

Novel view synthesis ͑NVS͒ is an important problem in image rendering. It involves synthesizing an image of a scene at any specified ͑novel͒ viewpoint, given some images of the scene at a few sample viewpoints. The general understanding is that the solution should bypass explicit 3-D reconstruction of the scene. As it is, the problem has a natural tie to interpolation, despite that mainstream efforts on the problem have been adopting formulations otherwise. Interpolation is about finding the output of a function f͑x͒ for any specified input x, given a few inputoutput pairs ͕͑x i , f i ͒ : i =1,2,3, . . . ,n͖ of the function. If the input x is the viewpoint, and f͑x͒ is the image, the interpolation problem becomes exactly NVS. We treat the NVS problem using the interpolation formulation. In particular, we adopt the example-based everything or interpolation ͑EBI͒ mechanism-an established mechanism for interpolating or learning functions from examples. EBI has all the desirable properties of a good interpolation: all given input-output examples are satisfied exactly, and the interpolation is smooth with minimum oscillations between the examples. We point out that EBI, however, has difficulty in interpolating certain classes of functions, including the image function in the NVS problem. We propose an extension of the mechanism for overcoming the limitation. We also present how the extended interpolation mechanism could be used to synthesize images at novel viewpoints. Real image results show that the mechanism has promising performance, even with very few example images.

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