Multiple road-objects detection and tracking for autonomous driving
Author
Source
Journal of Engineering Research
Issue
Vol. 10, Issue 1 A (31 Mar. 2022), pp.237-262, 26 p.
Publisher
Kuwait University Academic Publication Council
Publication Date
2022-03-31
Country of Publication
Kuwait
No. of Pages
26
Main Subjects
Abstract 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).
American Psychological Association (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
Modern Language Association (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
American Medical Association (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
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 260-262
Record ID
BIM-1495125