Open AccessAutomotive Parking Assistant Testing Scene analysis and evaluation research
Author(s) -
Liang Xue,
Y. Y. Leng,
Xin Lian
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1873/1/012079
Subject(s) - computer science , process (computing) , automotive industry , set (abstract data type) , function (biology) , simple (philosophy) , car parking , parking lot , evaluation function , simulation , artificial intelligence , engineering , transport engineering , philosophy , civil engineering , epistemology , evolutionary biology , biology , programming language , aerospace engineering , operating system
Since the existing automatic parking testing procedure scene is way too simple and idealized, it’s necessary to explore a set of effective verification procedure for the complex scene of Automatic Parking Assistant, which can evaluate the overall performance of the automatic parking function of different vehicles comprehensively, objectively and accurately. In the actual vehicle parking process, there are a lot of harsh and complex scenes which cannot be covered by the current verification system. This paper aims to build a set of effective verification system for the complex scene of automatic parking based on Artificial Intelligence technology. It can comprehensively, objectively and accurately evaluate the comprehensive performance of the automatic parking function of different vehicles.