Exploration of the Assessment for AVP Algorithm Training in Underground Parking Garages Simulation Scenario

Fuente: arXiv
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Main Author: Li, Wenjin
Format: Preprint
Published: 2023
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_version_ 1866913508424155136
author Li, Wenjin
author_facet Li, Wenjin
contents The autonomous valet parking (AVP) functionality in self-driving vehicles is currently capable of handling most simple parking tasks. However, further training is necessary to enable the AVP algorithm to adapt to complex scenarios and complete parking tasks in any given situation. Training algorithms with real-world data is time-consuming and labour-intensive, and the current state of constructing simulation environments is predominantly manual. This paper introduces an approach to automatically generate 3D underground garage simulation scenarios of varying difficulty levels based on pre-input 2D underground parking structure plans.
format Preprint
id arxiv_https___arxiv_org_abs_2311_08410
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Exploration of the Assessment for AVP Algorithm Training in Underground Parking Garages Simulation Scenario
Li, Wenjin
Robotics
Artificial Intelligence
Systems and Control
The autonomous valet parking (AVP) functionality in self-driving vehicles is currently capable of handling most simple parking tasks. However, further training is necessary to enable the AVP algorithm to adapt to complex scenarios and complete parking tasks in any given situation. Training algorithms with real-world data is time-consuming and labour-intensive, and the current state of constructing simulation environments is predominantly manual. This paper introduces an approach to automatically generate 3D underground garage simulation scenarios of varying difficulty levels based on pre-input 2D underground parking structure plans.
title Exploration of the Assessment for AVP Algorithm Training in Underground Parking Garages Simulation Scenario
topic Robotics
Artificial Intelligence
Systems and Control
url https://arxiv.org/abs/2311.08410