دانلود مقاله انگلیسی رایگان:استفاده از داده های رانندگی در سطح طبیعی SHRP2 مسیر رانندگی برای بررسی توانایی نگه داشتن خط راننده در مه: یک رویکرد کاوش قوانین انجمنی - 2019
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  • Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach
    Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach


    ترجمه فارسی عنوان مقاله:

    استفاده از داده های رانندگی در سطح طبیعی SHRP2 مسیر رانندگی برای بررسی توانایی نگه داشتن خط راننده در مه: یک رویکرد کاوش قوانین انجمنی


    منبع:

    Sciencedirect - Elsevier - Accident Analysis and Prevention, 129 (2019) 250-262: doi:10:1016/j:aap:2019:05:024


    نویسنده:

    Anik Das⁎, Mohamed M. Ahmed, Ali Ghasemzadeh


    چکیده انگلیسی:

    The presence of fog has a significant adverse impact on driving. Reduced visibility due to fog obscures the driving environment and greatly affects driver behavior and performance. Lane-keeping ability is a lateral driver behavior that can be very crucial in run-off-road crashes under reduced visibility conditions. A number of data mining techniques have been adopted in previous studies to examine driver behavior including lane-keeping ability. This study adopted an association rules mining method, a promising data mining technique, to investigate driver lane-keeping ability in foggy weather conditions using big trajectory-level SHRP2 Naturalistic Driving Study (NDS) datasets. A total of 124 trips in fog with their corresponding 248 trips in clear weather (i.e., 2 clear trips: 1 foggy weather trip) were considered for the study. The results indicated that affected visibility was associated with poor lane-keeping performance in several rules. Furthermore, additional factors including male drivers, a higher number of lanes, the presence of horizontal curves, etc. were found to be significant factors for having a higher proportion of poor lane-keeping performance. Moreover, drivers with more miles driven last year were found to have better lane-keeping performance. The findings of this study could help transportation practitioners to select effective countermeasures for mitigating run-off-road crashes under limited visibility conditions.
    Keywords: Foggy weather conditions | Data mining techniques | Association rules mining | Lane-keeping | Naturalistic driving study | SHRP2 | Limited visibility


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 13
    حجم فایل: 1359 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




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