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Multiple road-objects detection and tracking for autonomous driving
المؤلف
المصدر
Journal of Engineering Research
العدد
المجلد 10، العدد 1 A (31 مارس/آذار 2022)، ص ص. 237-262، 26ص.
الناشر
جامعة الكويت مجلس النشر العلمي
تاريخ النشر
2022-03-31
دولة النشر
الكويت
عدد الصفحات
26
التخصصات الرئيسية
الملخص EN
In this paper, a real-time road-object detection and tracking (LR_ODT) method for autonomous driving is proposed.
The method is based on the fusion of lidar and radar measurement data, where they are installed on the ego car, and a customized unscented Kalman filter (UKF) is employed for their data fusion.
The merits of both devices are combined using the proposed fusion approach to precisely provide both pose and velocity information for objects moving in roads around the ego car.
Unlike other detection and tracking approaches, the balanced treatment of both pose estimation accuracy and its real-time performance is the main contribution in this work.
The proposed technique is implemented using the high-performance language C++ and utilizes highly optimized math and optimization libraries for best real-time performance.
Simulation studies have been carried out to evaluate the performance of the LR_ODT for tracking bicycles, cars, and pedestrians.
Moreover, the performance of the UKF fusion is compared to that of the extended Kalman filter fusion (EKF) showing its superiority.
The UKF has outperformed the EKF on all test cases and all the state variable levels (-24% average RMSE).
The employed fusion technique shows how outstanding is the improvement in tracking performance compared to the use of a single device (-29% RMES with lidar and -38% RMSE with radar).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Faraj, Wail. 2022. Multiple road-objects detection and tracking for autonomous driving. Journal of Engineering Research،Vol. 10, no. 1 A, pp.237-262.
https://search.emarefa.net/detail/BIM-1495125
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Faraj, Wail. Multiple road-objects detection and tracking for autonomous driving. Journal of Engineering Research Vol. 10, no. 1 A (Mar. 2022), pp.237-262.
https://search.emarefa.net/detail/BIM-1495125
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Faraj, Wail. Multiple road-objects detection and tracking for autonomous driving. Journal of Engineering Research. 2022. Vol. 10, no. 1 A, pp.237-262.
https://search.emarefa.net/detail/BIM-1495125
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 260-262
رقم السجل
BIM-1495125
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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