Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition

Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS,...
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Autor*in:	Jianhua Guo [verfasserIn] Yinhang Wang [verfasserIn] Xingji Yin [verfasserIn] Peng Liu [verfasserIn] Zhuoran Hou [verfasserIn] Di Zhao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics

Übergeordnetes Werk:	In: Machines - MDPI AG, 2013, 10(2022), 10, p 895
Übergeordnetes Werk:	volume:10 ; year:2022 ; number:10, p 895

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/machines10100895

Katalog-ID:	DOAJ022450718

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520			\|a Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier.
650		4	\|a AEBS
650		4	\|a mass estimation
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650		4	\|a tire-road friction coefficient
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650		4	\|a longitudinal dynamics
653		0	\|a Mechanical engineering and machinery
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700	0		\|a Di Zhao \|e verfasserin \|4 aut
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spelling	10.3390/machines10100895 doi (DE-627)DOAJ022450718 (DE-599)DOAJ0e01c064c5194e0b94e461e094ad6ae2 DE-627 ger DE-627 rakwb eng TJ1-1570 Jianhua Guo verfasserin aut Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier. AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics Mechanical engineering and machinery Yinhang Wang verfasserin aut Xingji Yin verfasserin aut Peng Liu verfasserin aut Zhuoran Hou verfasserin aut Di Zhao verfasserin aut In Machines MDPI AG, 2013 10(2022), 10, p 895 (DE-627)73728823X (DE-600)2704328-9 20751702 nnns volume:10 year:2022 number:10, p 895 https://doi.org/10.3390/machines10100895 kostenfrei https://doaj.org/article/0e01c064c5194e0b94e461e094ad6ae2 kostenfrei https://www.mdpi.com/2075-1702/10/10/895 kostenfrei https://doaj.org/toc/2075-1702 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 10, p 895
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allfieldsGer	10.3390/machines10100895 doi (DE-627)DOAJ022450718 (DE-599)DOAJ0e01c064c5194e0b94e461e094ad6ae2 DE-627 ger DE-627 rakwb eng TJ1-1570 Jianhua Guo verfasserin aut Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier. AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics Mechanical engineering and machinery Yinhang Wang verfasserin aut Xingji Yin verfasserin aut Peng Liu verfasserin aut Zhuoran Hou verfasserin aut Di Zhao verfasserin aut In Machines MDPI AG, 2013 10(2022), 10, p 895 (DE-627)73728823X (DE-600)2704328-9 20751702 nnns volume:10 year:2022 number:10, p 895 https://doi.org/10.3390/machines10100895 kostenfrei https://doaj.org/article/0e01c064c5194e0b94e461e094ad6ae2 kostenfrei https://www.mdpi.com/2075-1702/10/10/895 kostenfrei https://doaj.org/toc/2075-1702 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 10, p 895
allfieldsSound	10.3390/machines10100895 doi (DE-627)DOAJ022450718 (DE-599)DOAJ0e01c064c5194e0b94e461e094ad6ae2 DE-627 ger DE-627 rakwb eng TJ1-1570 Jianhua Guo verfasserin aut Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier. AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics Mechanical engineering and machinery Yinhang Wang verfasserin aut Xingji Yin verfasserin aut Peng Liu verfasserin aut Zhuoran Hou verfasserin aut Di Zhao verfasserin aut In Machines MDPI AG, 2013 10(2022), 10, p 895 (DE-627)73728823X (DE-600)2704328-9 20751702 nnns volume:10 year:2022 number:10, p 895 https://doi.org/10.3390/machines10100895 kostenfrei https://doaj.org/article/0e01c064c5194e0b94e461e094ad6ae2 kostenfrei https://www.mdpi.com/2075-1702/10/10/895 kostenfrei https://doaj.org/toc/2075-1702 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 10, p 895
language	English
source	In Machines 10(2022), 10, p 895 volume:10 year:2022 number:10, p 895
sourceStr	In Machines 10(2022), 10, p 895 volume:10 year:2022 number:10, p 895
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics Mechanical engineering and machinery
isfreeaccess_bool	true
container_title	Machines
authorswithroles_txt_mv	Jianhua Guo @@aut@@ Yinhang Wang @@aut@@ Xingji Yin @@aut@@ Peng Liu @@aut@@ Zhuoran Hou @@aut@@ Di Zhao @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
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callnumber-first	T - Technology
author	Jianhua Guo
spellingShingle	Jianhua Guo misc TJ1-1570 misc AEBS misc mass estimation misc road grade misc tire-road friction coefficient misc least square method misc longitudinal dynamics misc Mechanical engineering and machinery Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition
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topic_title	TJ1-1570 Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition AEBS mass estimation road grade tire-road friction coefficient least square method longitudinal dynamics
topic	misc TJ1-1570 misc AEBS misc mass estimation misc road grade misc tire-road friction coefficient misc least square method misc longitudinal dynamics misc Mechanical engineering and machinery
topic_unstemmed	misc TJ1-1570 misc AEBS misc mass estimation misc road grade misc tire-road friction coefficient misc least square method misc longitudinal dynamics misc Mechanical engineering and machinery
topic_browse	misc TJ1-1570 misc AEBS misc mass estimation misc road grade misc tire-road friction coefficient misc least square method misc longitudinal dynamics misc Mechanical engineering and machinery
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title	Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition
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title_full	Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition
author_sort	Jianhua Guo
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author_browse	Jianhua Guo Yinhang Wang Xingji Yin Peng Liu Zhuoran Hou Di Zhao
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title_sort	study on the control algorithm of automatic emergency braking system (aebs) for commercial vehicle based on identification of driving condition
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title_auth	Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition
abstract	Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier.
abstractGer	Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier.
abstract_unstemmed	Automatic emergency braking systems (AEBS) significantly improve the active safety performance of commercial vehicles, but their effectiveness is affected by the vehicle’s driving conditions, which mainly include the vehicle load and road conditions. In order to improve the adaptability of the AEBS, an AEBS control strategy with adaptive driving conditions was proposed and validated using a simulation and experimentation. This AEBS control strategy was designed based on an estimation of the vehicle mass, the center of gravity position, road grade, and the tire-road friction coefficient. In the simulation and experimental verification, the braking deceleration and braking distance under different driving conditions were compared. The results show that the AEBS control strategy proposed in this paper can avoid collisions in all test scenarios and maintain a parking spacing of approximately 5 m. In an extreme test scenario with a full load and low tire–road friction, as compared with the fixed threshold control strategy, the warning can be issued 0.2 s earlier and the maximum intensity braking can be carried out 0.5 s earlier.
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title_short	Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition
url	https://doi.org/10.3390/machines10100895 https://doaj.org/article/0e01c064c5194e0b94e461e094ad6ae2 https://www.mdpi.com/2075-1702/10/10/895 https://doaj.org/toc/2075-1702
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Study on the Control Algorithm of Automatic Emergency Braking System (AEBS) for Commercial Vehicle Based on Identification of Driving Condition

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