Temat: vehicle state estimation - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Estimation of vehicle sideslip angle via pseudo-multisensor information fusion method
Autorzy:: Chen, T.
Chen, L.
Cai, Y.
Xu, X.
Powiązania:: https://bibliotekanauki.pl/articles/220661.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: vehicle state estimation
sideslip angle
recursive least squares
multi-sensor information fusion
pseudo-measurements
Opis:: This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation. Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator is proposed based on the wheel speed coupling relationship using a modified recursive least squares algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.
Źródło:: Metrology and Measurement Systems; 2018, 25, 3; 499-516
0860-8229
Pojawia się w:: Metrology and Measurement Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Detailed evaluation and analysis of vision-based online traffic parameters estimation approach using low resolution web cameras
Autorzy:: Ali, M.
Touko Tcheumadjeu, L.
Zuev, S.
Ruppe, S.
Powiązania:: https://bibliotekanauki.pl/articles/393806.pdf
Data publikacji:: 2014
Wydawca:: Polskie Stowarzyszenie Telematyki Transportu
Tematy:: background estimation
vehicle detection
time mean speed
traffic flow
traffic state
classification
estymacja tła
detekcja pojazdu
płynność ruchu
stan ruchu
klasyfikacja
Opis:: In this paper, we give an overview and a detail analysis of our approach for vision-based real-time traffic parameters estimation using low-resolution web cameras. Traffic parameters estimation approach mainly includes three major steps, (1) stable background estimation, (2) vehicle detection, mean speed and traffic flow estimation, and (3) traffic scene classification into three states (normal and congested). The background image is estimated and updated in realtime by novel background estimation algorithm based on the median of First-in-First-Out (FIFO) buffer of rectified traffic images. Vehicles are detected by background subtraction followed by post-processing steps. By exploiting the domain knowledge of real-world traffic flow patterns, mean speed and traffic flow can be estimated reliably and accurately. Naive Bayes classifier with statistical features is used for traffic scene classification. The traffic parameter estimation approach is tested and evaluated at the German Aerospace Center’s (DLR) urban road research laboratory in Berlin for 24 hours of live streaming data from web-cameras with frames per second 1, 5 and 10. Image resolution is 348 x 259 and JPEG compression is 50%. Processed traffic data is cross-checked with synchronized induction loop data. Detailed evaluation and analysis shows high accuracy and robustness of traffic parameters estimation approach using low-resolution web-cameras under challenging traffic conditions.
Źródło:: Archives of Transport System Telematics; 2014, 7, 2; 9-13
1899-8208
Pojawia się w:: Archives of Transport System Telematics
Dostawca treści:: Biblioteka Nauki

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