Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System

Predicting the trajectories of neighboring vehicles is essential to evade or mitigate collision with traffic participants. However, due to inadequate previous information and the uncertainty in future driving maneuvers, trajectory prediction is a difficult task. Recently, trajectory prediction model...

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Autores principales:	Rongxia Wang, Malik Bader Alazzam, Fawaz Alassery, Ahmed Almulihi, Marvin White
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/b1e4861378e748c49ea8bb2cd7799846
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id	oai:doaj.org-article:b1e4861378e748c49ea8bb2cd7799846
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spelling	oai:doaj.org-article:b1e4861378e748c49ea8bb2cd77998462021-11-29T00:56:17ZInnovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System1875-905X10.1155/2021/3773688https://doaj.org/article/b1e4861378e748c49ea8bb2cd77998462021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3773688https://doaj.org/toc/1875-905XPredicting the trajectories of neighboring vehicles is essential to evade or mitigate collision with traffic participants. However, due to inadequate previous information and the uncertainty in future driving maneuvers, trajectory prediction is a difficult task. Recently, trajectory prediction models using deep learning have been addressed to solve this problem. In this study, a method of early warning is presented using fuzzy comprehensive evaluation technique, which evaluates the danger degree of the target by comprehensively analyzing the target’s position, horizontal and vertical distance, speed of the vehicle, and the time of the collision. Because of the high false alarm rate in the early warning systems, an early warning activation area is established in the system, and the target state judgment module is triggered only when the target enters the activation area. This strategy improves the accuracy of early warning, reduces the false alarm rate, and also speeds up the operation of the early warning system. The proposed system can issue early warning prompt information to the driver in time and avoid collision accidents with accuracy up to 96%. The experimental results show that the proposed trajectory prediction method can significantly improve the vehicle network collision detection and early warning system.Rongxia WangMalik Bader AlazzamFawaz AlasseryAhmed AlmulihiMarvin WhiteHindawi LimitedarticleTelecommunicationTK5101-6720ENMobile Information Systems, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Rongxia Wang Malik Bader Alazzam Fawaz Alassery Ahmed Almulihi Marvin White Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
description	Predicting the trajectories of neighboring vehicles is essential to evade or mitigate collision with traffic participants. However, due to inadequate previous information and the uncertainty in future driving maneuvers, trajectory prediction is a difficult task. Recently, trajectory prediction models using deep learning have been addressed to solve this problem. In this study, a method of early warning is presented using fuzzy comprehensive evaluation technique, which evaluates the danger degree of the target by comprehensively analyzing the target’s position, horizontal and vertical distance, speed of the vehicle, and the time of the collision. Because of the high false alarm rate in the early warning systems, an early warning activation area is established in the system, and the target state judgment module is triggered only when the target enters the activation area. This strategy improves the accuracy of early warning, reduces the false alarm rate, and also speeds up the operation of the early warning system. The proposed system can issue early warning prompt information to the driver in time and avoid collision accidents with accuracy up to 96%. The experimental results show that the proposed trajectory prediction method can significantly improve the vehicle network collision detection and early warning system.
format	article
author	Rongxia Wang Malik Bader Alazzam Fawaz Alassery Ahmed Almulihi Marvin White
author_facet	Rongxia Wang Malik Bader Alazzam Fawaz Alassery Ahmed Almulihi Marvin White
author_sort	Rongxia Wang
title	Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
title_short	Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
title_full	Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
title_fullStr	Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
title_full_unstemmed	Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System
title_sort	innovative research of trajectory prediction algorithm based on deep learning in car network collision detection and early warning system
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/b1e4861378e748c49ea8bb2cd7799846
work_keys_str_mv	AT rongxiawang innovativeresearchoftrajectorypredictionalgorithmbasedondeeplearningincarnetworkcollisiondetectionandearlywarningsystem AT malikbaderalazzam innovativeresearchoftrajectorypredictionalgorithmbasedondeeplearningincarnetworkcollisiondetectionandearlywarningsystem AT fawazalassery innovativeresearchoftrajectorypredictionalgorithmbasedondeeplearningincarnetworkcollisiondetectionandearlywarningsystem AT ahmedalmulihi innovativeresearchoftrajectorypredictionalgorithmbasedondeeplearningincarnetworkcollisiondetectionandearlywarningsystem AT marvinwhite innovativeresearchoftrajectorypredictionalgorithmbasedondeeplearningincarnetworkcollisiondetectionandearlywarningsystem
_version_	1718407728992354304

Innovative Research of Trajectory Prediction Algorithm Based on Deep Learning in Car Network Collision Detection and Early Warning System

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