Using the Interval Type-2 Fuzzy Inference Systems to Compare the Impact of Speed and Space Perception on the Occurrence of Road Traffic Accidents
A constantly increasing number of deaths on roads forces analysts to search for models that predict the driver’s propensity for road traffic accidents (RTAs). This paper aims to examine a relationship between the speed and space assessment capabilities of drivers in terms of their association with t...
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| Published in: | Mathematics (Basel) Vol. 8; no. 9; p. 1548 |
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01-09-2020
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| Abstract | A constantly increasing number of deaths on roads forces analysts to search for models that predict the driver’s propensity for road traffic accidents (RTAs). This paper aims to examine a relationship between the speed and space assessment capabilities of drivers in terms of their association with the occurrence of RTAs. The method used for this purpose is based on the implementation of the interval Type-2 Fuzzy Inference System (T2FIS). The inputs to the first T2FIS relate to the speed assessment capabilities of drivers. These capabilities were measured in the experiment with 178 young drivers, with test speeds of 30, 50, and 70 km/h. The participants assessed the aforementioned speed values from four different observation positions in the driving simulator. On the other hand, the inputs of the second T2FIS are space assessment capabilities. The same group of drivers took two types of space assessment tests—2D and 3D. The third considered T2FIS sublimates of all previously mentioned inputs in one model. The output in all three T2FIS structures is the number of RTAs experienced by a driver. By testing three proposed T2FISs on the empirical data, the result of the research indicates that the space assessment characteristics better explain participation in RTAs compared to the speed assessment capabilities. The results obtained are further confirmed by implementing a multiple regression analysis. |
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| AbstractList | A constantly increasing number of deaths on roads forces analysts to search for models that predict the driver’s propensity for road traffic accidents (RTAs). This paper aims to examine a relationship between the speed and space assessment capabilities of drivers in terms of their association with the occurrence of RTAs. The method used for this purpose is based on the implementation of the interval Type-2 Fuzzy Inference System (T2FIS). The inputs to the first T2FIS relate to the speed assessment capabilities of drivers. These capabilities were measured in the experiment with 178 young drivers, with test speeds of 30, 50, and 70 km/h. The participants assessed the aforementioned speed values from four different observation positions in the driving simulator. On the other hand, the inputs of the second T2FIS are space assessment capabilities. The same group of drivers took two types of space assessment tests—2D and 3D. The third considered T2FIS sublimates of all previously mentioned inputs in one model. The output in all three T2FIS structures is the number of RTAs experienced by a driver. By testing three proposed T2FISs on the empirical data, the result of the research indicates that the space assessment characteristics better explain participation in RTAs compared to the speed assessment capabilities. The results obtained are further confirmed by implementing a multiple regression analysis. |
| Author | Švadlenka, Libor Čubranić-Dobrodolac, Marjana Čičević, Svetlana Dobrodolac, Momčilo Trifunović, Aleksandar |
| Author_xml | – sequence: 1 givenname: Marjana surname: Čubranić-Dobrodolac fullname: Čubranić-Dobrodolac, Marjana – sequence: 2 givenname: Libor orcidid: 0000-0001-6484-6660 surname: Švadlenka fullname: Švadlenka, Libor – sequence: 3 givenname: Svetlana surname: Čičević fullname: Čičević, Svetlana – sequence: 4 givenname: Aleksandar surname: Trifunović fullname: Trifunović, Aleksandar – sequence: 5 givenname: Momčilo orcidid: 0000-0001-8112-8329 surname: Dobrodolac fullname: Dobrodolac, Momčilo |
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Sci. doi: 10.1016/j.ssci.2019.05.039 contributor: fullname: Fan – volume: 13 start-page: 63 year: 2019 ident: ref_35 article-title: Human-machine shared control for vehicle lane keeping systems: A Lyapunov-based approach publication-title: IET Intell. Transp. Syst. doi: 10.1049/iet-its.2018.5084 contributor: fullname: Sentouh |
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| Snippet | A constantly increasing number of deaths on roads forces analysts to search for models that predict the driver’s propensity for road traffic accidents (RTAs).... |
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| SubjectTerms | Computer simulation Data collection Developing countries Drivers Empirical analysis Experiments Fatalities Fuzzy logic Fuzzy systems GNP Gross National Product Inference LDCs Mathematics Multiple regression analysis Questionnaires road safety Roads & highways Space perception speed perception Traffic accidents Traffic accidents & safety Traffic control traffic simulator Traffic speed type-2 fuzzy inference systems Urban areas Vehicles |
| Title | Using the Interval Type-2 Fuzzy Inference Systems to Compare the Impact of Speed and Space Perception on the Occurrence of Road Traffic Accidents |
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