Expressway abnormal event scene library construction method

A technology for abnormal events and highways, applied in 3D modeling, image data processing, special data processing applications, etc., can solve the problems of easy distortion, difficult to truly describe the traffic flow operation, etc., achieve high compatibility and improve simulation The effect of testing efficiency

Active Publication Date: 2022-03-18
江苏博宇鑫信息科技股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the existing technology, the abnormal traffic event scene library used for algorithm testing is often only manually set, and it is difficult to truly describe the traffic flow operation situation affected by the abnormal event, which is relatively simple and easy to be distorted

Method used

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  • Expressway abnormal event scene library construction method
  • Expressway abnormal event scene library construction method
  • Expressway abnormal event scene library construction method

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Embodiment Construction

[0018] The embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0019] A highway exception event scenario construct, such as the drawings, including the following steps:

[0020] Step S1, obtain highway video data, identify highway traffic abnormal events, common highway traffic abnormal events include: traffic bottlenecks, abnormal weather, road conditions, vehicle faults, and dispersion of articles such as temporary traffic control. Traffic congestion or traffic accident, depending on the intensive detection of the highway abnormal events in the intelligence road construction, you can extract an abnormal video data in an abnormal segment, according to the actual situation of the abnormal event, determine the boundary of the road segment, in the video The pixel level processing defined area is directly used in the screen, and the two-dimensional area information is written to the video for the vehicle position determ...

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Abstract

The invention relates to a highway abnormal event scene library construction method, which comprises the following steps of: acquiring vehicle track data by utilizing a yolk neural network, Kalman filtering and other algorithms, reproducing a vehicle track by utilizing a TraCI interface, acquiring simulated vehicle track data, and constructing an abnormal event scene library through joint simulation of an SUMO simulation environment and a CARLA three-dimensional simulation environment. A real test environment is provided for a vehicle algorithm for testing automatic driving and the like, the construction method is high in compatibility, a multi-category abnormal event scene library can be constructed, the robustness of the vehicle algorithm to abnormal road conditions is tested, and the simulation test efficiency is improved.

Description

Technical field [0001] The present invention relates to a highway abnormal event scenario construction method. Background technique [0002] In recent years, the intelligent level of traffic in my country has continued to improve, and the pace of traffic and Internet integration applications has accelerated, and intelligent transportation has become an important part of my country's smart city construction. In order to save test time and cost, avoid the risk of road measurement, improve testing and optimization efficiency, digital twins are widely applied to intelligent transportation, traffic emulation of digital twins as the core is rapidly evolved. [0003] At the same time, with the gradual integration of big data technology in the transportation field, emerging data drive methods (such as machine learning, strengthening learning, etc.) provide more good to the vehicle operation trajectory through information processing and extraction of road video data. Thoughts. [0004] In...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06T17/00
CPCG06F30/20G06T17/00
Inventor 宣帆徐璀肖通叶嘉骏史云阳顾子渊
Owner 江苏博宇鑫信息科技股份有限公司
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