Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data
المؤلفون المشاركون
Lu, Jian
Xue, Qingwen
Wang, Ke
Liu, Yujie
المصدر
Journal of Advanced Transportation
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-01-23
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Rear-end collision crash is one of the most common accidents on the road.
Accurate driving style recognition considering rear-end collision risk is crucial to design useful driver assistance systems and vehicle control systems.
The purpose of this study is to develop a driving style recognition method based on vehicle trajectory data extracted from the surveillance video.
First, three rear-end collision surrogates, Inversed Time to Collision (ITTC), Time-Headway (THW), and Modified Margin to Collision (MMTC), are selected to evaluate the collision risk level of vehicle trajectory for each driver.
The driving style of each driver in training data is labelled based on their collision risk level using K-mean algorithm.
Then, the driving style recognition model’s inputs are extracted from vehicle trajectory features, including acceleration, relative speed, and relative distance, using Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), and statistical method to facilitate the driving style recognition.
Finally, Supporting Vector Machine (SVM) is applied to recognize driving style based on the labelled data.
The performance of Random Forest (RF), K-Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) is also compared with SVM.
The results show that SVM overperforms others with 91.7% accuracy with DWT feature extraction method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xue, Qingwen& Wang, Ke& Lu, Jian& Liu, Yujie. 2019. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xue, Qingwen…[et al.]. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xue, Qingwen& Wang, Ke& Lu, Jian& Liu, Yujie. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1170283
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر