Automatic driving test scene set updating method and system based on real data
A test scene and automatic driving technology, applied in the direction of electrical digital data processing, software testing/debugging, error detection/correction, etc., can solve the problems of insufficient learning and iteration ability of complex scenes, low efficiency of test scene update, etc., and achieve high efficiency of iterative update Effect
Pending Publication Date: 2022-05-03
嬴彻星创智能科技(上海)有限公司
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Problems solved by technology
[0007] The present invention provides an automatic driving test scene set update method and system based on real data, which is used to solve the defects in the prior art that the automatic driving model has insufficient learning and iterative ability for complex scenes with long-tail distribution and low update efficiency of test scenes. Realize more efficient automatic driving test scene update
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[0078] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0079] Combine below figure 1 , figure 2 , Figure 5 The real data-based automatic driving test scene set updating method of the present invention is described.
[0080] Such as figure 1 As shown, the embodiment of the present invention provides a method for updating the automatic driving test scene set based on real data, including:
[0081] Step 102, according to the first condition, ...
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The invention relates to the technical field of automatic driving, and provides an automatic driving test scene set updating method and system based on real data. The method comprises the following steps: dividing real road operation data of automatic driving into complex scene data fragments and non-complex scene data fragments according to a first condition; extracting a design operation domain ODD element and a dynamic parameter group in the complex scene data fragment, and generating an iterative test scene according to the design operation domain ODD element and the dynamic parameter group in the complex scene data fragment; updating a parameter space of a logic scene in an existing test scene set based on the non-complex scene data fragment; according to the method, the scene admission rule is introduced through the first condition, the complex scene data fragments are extracted from the real road operation data, the data fragments with poor processing effects of the automatic driving model can be quickly positioned, the test scene set is updated on the basis, and a more efficient test scene basis is provided for iterative updating of the automatic driving model.
Description
technical field [0001] The invention relates to the technical field of automatic driving, in particular to a method and system for updating a test scene set of automatic driving based on real data. Background technique [0002] Autonomous driving, also known as unmanned driving, computer driving or wheeled mobile robot, is a cutting-edge technology that relies on computer and artificial intelligence technology to complete complete, safe and effective driving without human manipulation. [0003] However, unmanned driving also faces many challenges, such as bad weather, complex traffic environments, etc., so the performance in some scenarios may not match that of human drivers. In order to solve this problem, more tests and iterative updates of autonomous driving models are required to improve the processing ability in complex scenarios. [0004] There is a generally accepted long-tail distribution assumption in the above complex scenarios, that is, 80% of the cases are commo...
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IPC IPC(8): G06F11/34G06F11/36G06K9/62
CPCG06F11/3457G06F11/3676G06F18/23
Inventor 张泰培叶晨桦程伟胡洁义申思琪
Owner 嬴彻星创智能科技(上海)有限公司