دانلود مقاله ISI انگلیسی شماره 92254
ترجمه فارسی عنوان مقاله

تأثیرات سیستم های هشدار دهنده در زمان واقعی در رانندگی تحت شرایط مه با استفاده از یک چارچوب مدل سازی انتخابی که به صورت تجربی پشتیبانی می شود

عنوان انگلیسی
Effects of real-time warning systems on driving under fog conditions using an empirically supported speed choice modeling framework
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
92254 2018 14 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Transportation Research Part C: Emerging Technologies, Volume 86, January 2018, Pages 97-110

ترجمه کلمات کلیدی
شرایط دید کاهش یافته، سیستم هشدار مهمان واقعی تنظیم سرعت، پارامتر تصادفی مدل رگرسیون بتا موانع،
کلمات کلیدی انگلیسی
Reduced visibility conditions; Real-time fog warning system; Speed adjustment; Random parameter; Hurdle beta regression model;
پیش نمایش مقاله
پیش نمایش مقاله  تأثیرات سیستم های هشدار دهنده در زمان واقعی در رانندگی تحت شرایط مه با استفاده از یک چارچوب مدل سازی انتخابی که به صورت تجربی پشتیبانی می شود

چکیده انگلیسی

Fog warning systems can convey warning messages to drivers and help to reduce crashes that may occur due to the sudden occurrence of low visibility conditions. This study aims to assess the effectiveness of real-time fog warning systems by quantifying and characterizing drivers’ speed adjustments under different roadway types, traffic conditions, and fog levels. In order to explore how a driver perceives the fog warning systems (i.e., beacon and dynamic message signs (DMS)) when approaching a fog area, this paper divides the roads into three zones (i.e., clear zone, transition zone, fog zone) according to visibility levels and suggests a hierarchical assessment concept to explore the driver’s speed adjustment maneuvers. For the three different zones, different indexes are computed corresponding to drivers’ speed adjustments. Two linear regression models with random effects and one hurdle beta regression model are estimated for the indexes. In addition, the three models were modified by allowing the parameters to vary across the participants to account for the unobserved heterogeneity. To validate the proposed analysis framework, an empirical driving simulator study was conducted based on two real-world roads in a fog prone area in Florida. The results revealed that the proposed modeling framework is able to reflect drivers’ speed adjustment in risk perception and acceleration/deceleration maneuvering when receiving real-time warning massages. The results suggested that installing a beacon could be beneficial to speed reduction before entering the fog area. Meanwhile, DMS may affect drivers’ brake reaction at the beginning section of reduced visibility. However, no effects of warning systems for drivers’ final speed choice in the fog can be observed. It is suggested that proper warning systems should be considered for different conditions since they have different effects. It is expected that more efficient technology can be developed to enhance traffic safety under fog conditions with a better understanding of the drivers’ speed adjustments revealed in this study.