Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions
Joint Authors
Törő, Olivér
Bécsi, Tamás
Aradi, Szilárd
Gáspár, Péter
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-04
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Robust object tracking and maneuver estimation methods play significant role in the design of advanced driver assistant systems and self-driving cars.
As an input to situation understanding and awareness, the performance of such algorithms influences the overall effectiveness of motion planning and plays high role in safety.
The paper examines the suitability of different probabilistic state estimation methods, namely, the Extended Kalman Filter (EKF) and the more general Particle Filter (PF) with the addition of the Interacting Multiple Model (IMM) approach.
These algorithms are not capable of predicting motion for long term in road traffic conditions, though their robustness and model classification capability are essential for the overall system.
The performance is evaluated in road traffic scenarios where the tracked object imitates the motion characteristics of a road vehicle and is observed from a stationary sensor.
The measurements are generated according to standard automotive radar models.
The analysis conducted along two aspects emphasizes the different performance and scaling properties of the examined state estimation algorithms.
The presented evaluation framework serves as a customizable method to test and develop advanced autonomous functions.
American Psychological Association (APA)
Törő, Olivér& Bécsi, Tamás& Aradi, Szilárd& Gáspár, Péter. 2019. Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1170116
Modern Language Association (MLA)
Törő, Olivér…[et al.]. Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions. Journal of Advanced Transportation No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1170116
American Medical Association (AMA)
Törő, Olivér& Bécsi, Tamás& Aradi, Szilárd& Gáspár, Péter. Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1170116
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170116