Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information
This paper investigates the decision-making characteristics of the driver in the overtaking on the highway road. For the research purpose, a novel method was proposed by introducing a logistic regression model accompanied by the statistical test technique, which does not require prior knowledge abou...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9534758/ |
| _version_ | 1819091500891373568 |
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| author | Jude C. Nwadiuto Soichi Yoshino Hiroyuki Okuda Tatsuya Suzuki |
| author_facet | Jude C. Nwadiuto Soichi Yoshino Hiroyuki Okuda Tatsuya Suzuki |
| author_sort | Jude C. Nwadiuto |
| collection | DOAJ |
| description | This paper investigates the decision-making characteristics of the driver in the overtaking on the highway road. For the research purpose, a novel method was proposed by introducing a logistic regression model accompanied by the statistical test technique, which does not require prior knowledge about the explanatory variables. This study hypothesizes that the driver’s gazing behavior is crucial for the decision-making process in driving and hence, the line-of-sight information was introduced to estimate driver’s gazing behavior in the model of driver’s decision specifically for reproducing the overtaking driving behavior accurately. Consequently, the proposed model realized a high describability on the decision of the driver when performing the overtaking driving task, which is one of the significant advancements of the present study with respect to the past similar studies. This study integrates the perspectives of intelligent vehicle design and cognitive science by revealing which factor the driver pays attention to in a changeable driving environment due to various observable factors. In experiments based on the driving simulator with six human subjects, the overtaking behavior was successfully estimated by specifying a set of variables to reconstruct the driver’s behavior and then the proposed model provided a minimum set of necessary variables accompanied with key coefficients. In conclusion, the proposed approach based on a simple logistic regression model demonstrated driving behaviors with an accurate estimation of the driver’s intention without the need for prior knowledge, and it may contribute to higher describability for various driving actions in a dynamic environment. |
| first_indexed | 2024-12-21T22:40:43Z |
| format | Article |
| id | doaj.art-e6242d35af724c8a85a2e97436b3d0f2 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-21T22:40:43Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e6242d35af724c8a85a2e97436b3d0f22022-12-21T18:47:51ZengIEEEIEEE Access2169-35362021-01-01912767212768410.1109/ACCESS.2021.31117539534758Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing InformationJude C. Nwadiuto0https://orcid.org/0000-0001-5965-9844Soichi Yoshino1Hiroyuki Okuda2https://orcid.org/0000-0002-2910-4634Tatsuya Suzuki3https://orcid.org/0000-0002-0182-308XDepartment of Mechanical Systems Engineering, Nagoya University, Nagoya, JapanToyota Research Institute-Advanced Development, Tokyo, JapanDepartment of Mechanical Systems Engineering, Nagoya University, Nagoya, JapanDepartment of Mechanical Systems Engineering, Nagoya University, Nagoya, JapanThis paper investigates the decision-making characteristics of the driver in the overtaking on the highway road. For the research purpose, a novel method was proposed by introducing a logistic regression model accompanied by the statistical test technique, which does not require prior knowledge about the explanatory variables. This study hypothesizes that the driver’s gazing behavior is crucial for the decision-making process in driving and hence, the line-of-sight information was introduced to estimate driver’s gazing behavior in the model of driver’s decision specifically for reproducing the overtaking driving behavior accurately. Consequently, the proposed model realized a high describability on the decision of the driver when performing the overtaking driving task, which is one of the significant advancements of the present study with respect to the past similar studies. This study integrates the perspectives of intelligent vehicle design and cognitive science by revealing which factor the driver pays attention to in a changeable driving environment due to various observable factors. In experiments based on the driving simulator with six human subjects, the overtaking behavior was successfully estimated by specifying a set of variables to reconstruct the driver’s behavior and then the proposed model provided a minimum set of necessary variables accompanied with key coefficients. In conclusion, the proposed approach based on a simple logistic regression model demonstrated driving behaviors with an accurate estimation of the driver’s intention without the need for prior knowledge, and it may contribute to higher describability for various driving actions in a dynamic environment.https://ieeexplore.ieee.org/document/9534758/Overtaking behaviordecision-makinglogistic regressionmodel selectionstatistical testgazing behavior |
| spellingShingle | Jude C. Nwadiuto Soichi Yoshino Hiroyuki Okuda Tatsuya Suzuki Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information IEEE Access Overtaking behavior decision-making logistic regression model selection statistical test gazing behavior |
| title | Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information |
| title_full | Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information |
| title_fullStr | Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information |
| title_full_unstemmed | Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information |
| title_short | Variable Selection and Modeling of Drivers’ Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information |
| title_sort | variable selection and modeling of drivers x2019 decision in overtaking behavior based on logistic regression model with gazing information |
| topic | Overtaking behavior decision-making logistic regression model selection statistical test gazing behavior |
| url | https://ieeexplore.ieee.org/document/9534758/ |
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