Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation

Electric automated vehicles are zero-emission, energy-saving, and environmentally friendly vehicles, and testing and verification is an important means to ensure their safety. Because of the scarcity of dangerous scenarios in natural driving roads, it is required to conduct accelerated tests and eva...

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Autores principales:	Qin Xia, Yi Chai, Haoran Lv, Hong Shu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Monte Carlo simulation Metropolis–Hastings sampling importance sampling critical scenario accelerated test Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/f514595cc2d6421294a5c103c5834172
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spelling	oai:doaj.org-article:f514595cc2d6421294a5c103c58341722021-11-25T19:04:15ZResearch on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation10.3390/su1322127762071-1050https://doaj.org/article/f514595cc2d6421294a5c103c58341722021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12776https://doaj.org/toc/2071-1050Electric automated vehicles are zero-emission, energy-saving, and environmentally friendly vehicles, and testing and verification is an important means to ensure their safety. Because of the scarcity of dangerous scenarios in natural driving roads, it is required to conduct accelerated tests and evaluations for electric automated vehicles. According to the scenario data of the natural road in cut-in conditions, we used the kernel density estimation method to calculate the probability distribution of the scenario parameters. Additionally, we used the Metropolis–Hastings algorithm to sample based on the probability distribution of the parameters, and the Euclidean distance was combined with the paired combination to accelerate the simulation test process. The critical scenarios were screened out by the safety indicator, and the feature distribution of the critical scenario parameters was analyzed based on the Euclidean distance clustering method, so as to design importance sampling parameters and carry out importance sampling. The study obtained the distribution characteristics of critical scenario parameters under cut-in conditions and found that the importance sampling method can accelerate the test under the condition of ensuring that the relative error is small, and the improved accelerated simulation method makes the overall calculation amount smaller.Qin XiaYi ChaiHaoran LvHong ShuMDPI AGarticleMonte Carlo simulationMetropolis–Hastings samplingimportance samplingcritical scenarioaccelerated testEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12776, p 12776 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Monte Carlo simulation Metropolis–Hastings sampling importance sampling critical scenario accelerated test Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	Monte Carlo simulation Metropolis–Hastings sampling importance sampling critical scenario accelerated test Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Qin Xia Yi Chai Haoran Lv Hong Shu Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
description	Electric automated vehicles are zero-emission, energy-saving, and environmentally friendly vehicles, and testing and verification is an important means to ensure their safety. Because of the scarcity of dangerous scenarios in natural driving roads, it is required to conduct accelerated tests and evaluations for electric automated vehicles. According to the scenario data of the natural road in cut-in conditions, we used the kernel density estimation method to calculate the probability distribution of the scenario parameters. Additionally, we used the Metropolis–Hastings algorithm to sample based on the probability distribution of the parameters, and the Euclidean distance was combined with the paired combination to accelerate the simulation test process. The critical scenarios were screened out by the safety indicator, and the feature distribution of the critical scenario parameters was analyzed based on the Euclidean distance clustering method, so as to design importance sampling parameters and carry out importance sampling. The study obtained the distribution characteristics of critical scenario parameters under cut-in conditions and found that the importance sampling method can accelerate the test under the condition of ensuring that the relative error is small, and the improved accelerated simulation method makes the overall calculation amount smaller.
format	article
author	Qin Xia Yi Chai Haoran Lv Hong Shu
author_facet	Qin Xia Yi Chai Haoran Lv Hong Shu
author_sort	Qin Xia
title	Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
title_short	Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
title_full	Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
title_fullStr	Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
title_full_unstemmed	Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation
title_sort	research on accelerated testing of cut-in condition of electric automated vehicles based on monte carlo simulation
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f514595cc2d6421294a5c103c5834172
work_keys_str_mv	AT qinxia researchonacceleratedtestingofcutinconditionofelectricautomatedvehiclesbasedonmontecarlosimulation AT yichai researchonacceleratedtestingofcutinconditionofelectricautomatedvehiclesbasedonmontecarlosimulation AT haoranlv researchonacceleratedtestingofcutinconditionofelectricautomatedvehiclesbasedonmontecarlosimulation AT hongshu researchonacceleratedtestingofcutinconditionofelectricautomatedvehiclesbasedonmontecarlosimulation
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Research on Accelerated Testing of Cut-In Condition of Electric Automated Vehicles Based on Monte Carlo Simulation

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