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Wyszukujesz frazę "Ismail, M.A." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Green Driver: driving behaviors revisited on safety
Autorzy:
Muslim, N. H. B.
Shafaghat, A.
Keyvanfar, A.
Ismail, M.
Powiązania:
https://bibliotekanauki.pl/articles/223891.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
travel behavior
safe driving
reckless driving
driving skills and practice
green driver
index assessment model
zachowania w czasie jazdy
bezpieczna jazda
jazda lekkomyślna
umiejętności i praktyka
młody kierowca
Opis:
Interactions between road users, motor vehicles, and environment affect to driver’s travel behavior; however, frailer of proper interaction may lead to ever-increasing road crashes, injuries and fatalities. The current study has generated the green driver concept to evaluate the incorporation of green driver to negative outcomes reduction of road transportation. The study aimed to identify the green driver’s behaviors affecting safe traveling by engaging two research phases. Phase one was to identify the safe driving behaviors using Systematic literature review and Content Analysis methods. Phase one identified twenty-four (24) sub-factors under reckless driving behaviors cluster, and nineteen (19) sub-factors under safe driving practice cluster. Second phase was to establish the actual weight value of the sub-factors using Grounded Group Decision Making (GGDM) and Value Assignment (VA) methods, in order to determine the value impact of each sub-factor to green driving. Phase two resulted that sub-factors Exceeding speed limits (DB f2.2.) and Driver’s cognitive and motor skills (SD f1.2.2.) have received highest actual values, 0.64 and 0.49, respectively; ranked as the High contributor grade. Contrary, the sub-factors Age cognitive decline (DB f1.2.) and Competitive attitude (DB f1.2.), and Avoid gear snatching (SD f1.1.4.) have the lowest actual values; and ranked in low-contribution grade. The rest of the sub-factors have ranked in medium-contribution grade. The research also found out drivers’ personalities (included, physical and psychological characteristics) remains unaccountable and non-measureable yet in driver travel behavior assessment models. The study outputs would be used in development of Green Driver Index Assessment Model.
Źródło:
Archives of Transport; 2018, 47, 3; 49-78
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ground Penetrating Radar’s (GPR) Imaging and Applications to Pavement Structural Assessment: a Case of Malaysia
Autorzy:
Muslim, N. H.
Mohamed, M. I.
Amin, Z. M.
Shafaghat, A.
Ismail, M.
Keyyanfar, A.
Powiązania:
https://bibliotekanauki.pl/articles/224097.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
pavement
assessment pavements
geophysical tools
ground penetrating radar
GPR
REFLEX 2D software
nawierzchnia
ocena nawierzchni
narzędzia geofizyczne
georadar
oprogramowanie REFLEX 2D
REFLEX 2D
Opis:
Traditionally, pavement distress evaluations were carried out by visual observation. Traditional practice requires a person to walk along the stretch of the pavement to conduct distress survey, take photo and measure defects occurred at deteriorated surfaces. However, this approach is too subjective, generates inconsistencies of information, less reliable and time-consuming. Due to these shortcomings, the transportation practitioners in pavement maintenance seek for other alternative tools and techniques to arrest incapability of traditional practices. One of the tools available in the market is Ground Penetrating Radar (GPR). GPR is a geophysical tool known by ability to accommodate extensive data in pavement assessment, geotechnical investigation and structural assessment. The application of GPR is such new to most of road maintenance industry in Malaysia. Therefore, this study has been undertaken to evaluate the benefits of using GPR imaging and its application in assessing pavement structures in Malaysia. The GPR survey was conducted in Meranti street located at UTM (Universiti Teknologi Malaysia) campus, and then analyzed using REFLEX 2D simulation software. The finding shows there are three (3) types of information obtained from GPR survey included; identification of raw image and processed image, identification of pavement segments thickness, and identification of GPR response towards surface and subsurface conditions, which illustrated in radargram images. Furthermore, the GPR can perform at high speed and can save time. It is also beneficial for long-term investment due to ability to provide extensive information at a greater depth. The research indicates that interpretation of GPR’s radargram images consumes time due to the low resolution. Therefore, selection of GPR system is subject to level of accuracy and clarity of radar images needed in a project.
Źródło:
Archives of Transport; 2017, 42, 2; 39-51
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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