A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model
Abstract The interpretation of driver behaviour decisions is an essential part of driver behaviour research. Unlike previous studies that use driver's vision indicators or behaviour indicators as the basis for behaviour decision‐making models, this paper proposes a new concept of vision pressur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | IET Intelligent Transport Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/itr2.12123 |
| _version_ | 1811183747245015040 |
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| author | Yi Li Bo Yu Yuren Chen Zhihua Hu |
| author_facet | Yi Li Bo Yu Yuren Chen Zhihua Hu |
| author_sort | Yi Li |
| collection | DOAJ |
| description | Abstract The interpretation of driver behaviour decisions is an essential part of driver behaviour research. Unlike previous studies that use driver's vision indicators or behaviour indicators as the basis for behaviour decision‐making models, this paper proposes a new concept of vision pressure energy field to describe driver's vision perception. Driver behaviours are regarded as the results of the energy fluctuation of the “Potential Energy‐Field Energy‐Kinetic Energy” cycle. The energy field model and corresponding classification method of driving risk level are presented. The micro‐effect and macro‐effect of driver behaviour decisions are considered in the decision effect evaluation process. These models are integrated into an RNN (Recurrent Neural Network) framework. After the field test data training, the model results show that the decision‐making framework with a hidden layer can successfully describe the car‐following and lane‐changing behaviours. The phenomenon of continuous behaviour change can be explained by the prediction result of decision effect level. The vision pressure energy field theory integrates the driver behaviour into the physical energy field theory. It presents a new way to interpret driver's vision perception results. The driver behaviour changes can also be successfully predicted through this theory. |
| first_indexed | 2024-04-11T09:51:03Z |
| format | Article |
| id | doaj.art-c65196c2f0424ab6bee7d286c0c133c6 |
| institution | Directory Open Access Journal |
| issn | 1751-956X 1751-9578 |
| language | English |
| last_indexed | 2024-04-11T09:51:03Z |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Intelligent Transport Systems |
| spelling | doaj.art-c65196c2f0424ab6bee7d286c0c133c62022-12-22T04:30:47ZengWileyIET Intelligent Transport Systems1751-956X1751-95782022-01-0116111210.1049/itr2.12123A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making modelYi Li0Bo Yu1Yuren Chen2Zhihua Hu3Logistics Research Center Shanghai Maritime University 1550 Haigang Ave. Shanghai People's Republic of ChinaThe Key Laboratory of Road and Traffic Engineering, Ministry of Education Tongji University No. 4800 Cao'an Hwy. Shanghai People's Republic of ChinaThe Key Laboratory of Road and Traffic Engineering, Ministry of Education Tongji University No. 4800 Cao'an Hwy. Shanghai People's Republic of ChinaLogistics Research Center Shanghai Maritime University 1550 Haigang Ave. Shanghai People's Republic of ChinaAbstract The interpretation of driver behaviour decisions is an essential part of driver behaviour research. Unlike previous studies that use driver's vision indicators or behaviour indicators as the basis for behaviour decision‐making models, this paper proposes a new concept of vision pressure energy field to describe driver's vision perception. Driver behaviours are regarded as the results of the energy fluctuation of the “Potential Energy‐Field Energy‐Kinetic Energy” cycle. The energy field model and corresponding classification method of driving risk level are presented. The micro‐effect and macro‐effect of driver behaviour decisions are considered in the decision effect evaluation process. These models are integrated into an RNN (Recurrent Neural Network) framework. After the field test data training, the model results show that the decision‐making framework with a hidden layer can successfully describe the car‐following and lane‐changing behaviours. The phenomenon of continuous behaviour change can be explained by the prediction result of decision effect level. The vision pressure energy field theory integrates the driver behaviour into the physical energy field theory. It presents a new way to interpret driver's vision perception results. The driver behaviour changes can also be successfully predicted through this theory.https://doi.org/10.1049/itr2.12123Traffic engineering computingSocial and behavioural sciences computingNeural nets |
| spellingShingle | Yi Li Bo Yu Yuren Chen Zhihua Hu A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model IET Intelligent Transport Systems Traffic engineering computing Social and behavioural sciences computing Neural nets |
| title | A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model |
| title_full | A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model |
| title_fullStr | A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model |
| title_full_unstemmed | A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model |
| title_short | A new theory of driver vision pressure energy field and its application in driver behaviour decision‐making model |
| title_sort | new theory of driver vision pressure energy field and its application in driver behaviour decision making model |
| topic | Traffic engineering computing Social and behavioural sciences computing Neural nets |
| url | https://doi.org/10.1049/itr2.12123 |
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