کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1119102 1488463 2013 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Traffic Incident Duration Prediction based on Partial Least Squares Regression
موضوعات مرتبط
علوم انسانی و اجتماعی علوم انسانی و هنر هنر و علوم انسانی (عمومی)
پیش نمایش صفحه اول مقاله
Traffic Incident Duration Prediction based on Partial Least Squares Regression
چکیده انگلیسی

The prediction of the traffic incident duration is a very important issue to the Advanced Traffic Incident Management (ATIM). An accurate prediction of incident duration makes a lot contributes to making appropriate decisions to deal with incidents for traffic managers. The paper employed the Partial Least Squares Regression (PLSR) to build model between incident duration and its influence factors. Three models were established for three types of incident correspondingly, i.e. stopped vehicle, lost load and accident. Meanwhile, a model without distinguishing the incident type was built as a comparison. The experiments results indicated that the model obtained high prediction accuracy for those incidents which last 20 minutes to 90 minutes. The models got prediction accuracy of 77.24%, 86.59%, 83.33% and 71.30% for stopped vehicle, lost load, accident and all incidents within 20 minutes error, respectively. The results indicated that the PLSR has a promising application to predict traffic incident duration

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia - Social and Behavioral Sciences - Volume 96, 6 November 2013, Pages 425-432