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Wyszukujesz frazę "Keyvanfar, A." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
A decision support tool for a walkable integrated neighbourhood design using a multicriteria decision-making method.
Autorzy:
Keyvanfar, A.
Shafaghat, A.
Lamit, H.
Powiązania:
https://bibliotekanauki.pl/articles/196315.pdf
Data publikacji:
2018
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
walkability
walkable city
assessment model
pedestrian behavior
decision tree
decision support tool
dostępność piesza
piesze miasto
model oceny
zachowanie pieszych
drzewo decyzyjne
narzędzie wspomagania decyzji
Opis:
Growing concern about transportation emissions and energy security has persuaded urban professionals and practitioners to pursue non-motorized urban development. They need an assessment tool to measure the association between the built environment and pedestrians’ walking behaviour more accurately. This research has developed a new assessment tool called the Walkable Integrated Neighbourhood Design (WIND) support tool, which interprets the built environment’s qualitative variables and pedestrians’ perceptual qualities in relation to quantifiable variables. The WIND tool captures and forecasts pedestrians’ mind mapping, as well as sequential decision-making during walking, and then analyses the path walkability through a decision-tree-making (DTM) algorithm on both the segment scale and the neighbourhood scale. The WIND tool measures walkability by variables clustered into five features, 11 criteria and 92 subcriteria. The mind-mapping analysis is presented in the form of a ‘Walkability_DTM-Mind-mapping sheet’ for each destination and the overall neighbourhood. The WIND tool is applicable to any neighbourhood cases, although it was applied to the Taman Universiti neighbourhood in Malaysia. The tool’s outputs aid urban designers to imply adaptability between the neighbourhood environment and residents’ perceptions, preferences and needs.
Źródło:
Zeszyty Naukowe. Transport / Politechnika Śląska; 2018, 100; 45-68
0209-3324
2450-1549
Pojawia się w:
Zeszyty Naukowe. Transport / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
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
    Wyświetlanie 1-2 z 2

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