A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience
Existing studies had shown that advanced driver assistance systems (ADAS) and driver individual characteristics can significantly affect driving behavior. Therefore, it is necessary to consider these factors when building the car-following model. In this study, we established a car-following model b...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/6619137 |
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| _version_ | 1832550076085436416 |
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| author | Yugang Wang Nengchao Lyu |
| author_facet | Yugang Wang Nengchao Lyu |
| author_sort | Yugang Wang |
| collection | DOAJ |
| description | Existing studies had shown that advanced driver assistance systems (ADAS) and driver individual characteristics can significantly affect driving behavior. Therefore, it is necessary to consider these factors when building the car-following model. In this study, we established a car-following model based on risk homeostasis theory, which uses safety margin (SM) as the risk level quantization parameter. Firstly, three-way Analysis of Variance (ANOVA) was used to analyze the influencing factors of car-following behavior. The results showed that ADAS and driving experience have a significant effect on the drivers’ car-following behavior. Then, according to these two significant factors, the car-following model was established. The statistical method was used to calibrate the parameter reaction response τ. Other four parameters (SMDL, SMDH, α1, and α2) were calibrated using a classical genetic algorithm, and the effects of ADAS and driving experience in these four parameters were analyzed using T-test. Finally, the proposed model was compared with the GHR model, and the result showed that the proposed model has a smaller Root Mean Square Error (RMSE) than the GHR model. The proposed model is a method of simulating different driving behaviors that are affected by ADAS and individual characteristics. Considering more driver individual characteristics, such as driving style, is the future research goal. |
| format | Article |
| id | doaj-art-6d4d8342a6ab454f96511f77cd9b7ef1 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-6d4d8342a6ab454f96511f77cd9b7ef12025-02-03T06:07:42ZengWileyAdvances in Civil Engineering1687-80861687-80942021-01-01202110.1155/2021/66191376619137A Car-Following Model Based on Safety Margin considering ADAS and Driving ExperienceYugang Wang0Nengchao Lyu1Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, ChinaExisting studies had shown that advanced driver assistance systems (ADAS) and driver individual characteristics can significantly affect driving behavior. Therefore, it is necessary to consider these factors when building the car-following model. In this study, we established a car-following model based on risk homeostasis theory, which uses safety margin (SM) as the risk level quantization parameter. Firstly, three-way Analysis of Variance (ANOVA) was used to analyze the influencing factors of car-following behavior. The results showed that ADAS and driving experience have a significant effect on the drivers’ car-following behavior. Then, according to these two significant factors, the car-following model was established. The statistical method was used to calibrate the parameter reaction response τ. Other four parameters (SMDL, SMDH, α1, and α2) were calibrated using a classical genetic algorithm, and the effects of ADAS and driving experience in these four parameters were analyzed using T-test. Finally, the proposed model was compared with the GHR model, and the result showed that the proposed model has a smaller Root Mean Square Error (RMSE) than the GHR model. The proposed model is a method of simulating different driving behaviors that are affected by ADAS and individual characteristics. Considering more driver individual characteristics, such as driving style, is the future research goal.http://dx.doi.org/10.1155/2021/6619137 |
| spellingShingle | Yugang Wang Nengchao Lyu A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience Advances in Civil Engineering |
| title | A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience |
| title_full | A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience |
| title_fullStr | A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience |
| title_full_unstemmed | A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience |
| title_short | A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience |
| title_sort | car following model based on safety margin considering adas and driving experience |
| url | http://dx.doi.org/10.1155/2021/6619137 |
| work_keys_str_mv | AT yugangwang acarfollowingmodelbasedonsafetymarginconsideringadasanddrivingexperience AT nengchaolyu acarfollowingmodelbasedonsafetymarginconsideringadasanddrivingexperience AT yugangwang carfollowingmodelbasedonsafetymarginconsideringadasanddrivingexperience AT nengchaolyu carfollowingmodelbasedonsafetymarginconsideringadasanddrivingexperience |