Estimation of parameters and delay in driver models using L1-regularization

被引：0

作者：

Hosseini, SeyedMehrdad ^{[1
]}

Koroglu, Hakan ^{[1
]}

Sjoberg, Jonas ^{[1
]}

机构：

[1] Chalmers Univ Technol, Dept Signals & Syst, Gothenburg, Sweden

来源：

2016 EUROPEAN CONTROL CONFERENCE (ECC) | 2016年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new method is proposed for driver reaction time (delay) and parameter estimation using a generic lateral model that is expressed in terms of the steering angle, yaw rate and lateral lane offset. The idea behind the presented method is to reformulate the original driver model with an overparametrized one and then use the L-1-regularization method to enforce sparsity and thereby estimate the delay together with the parameters of the original model. A sequential algorithm is then presented to obtain better estimates of the parameters with a model in which the delay is fixed.

引用

页码：945 / 950

页数：6

共 50 条

[31] On l1-Regularization in Light of Nashed's Ill-Posedness Concept
Flemming, Jens
Hofmann, Bernd
Veselic, Ivan
COMPUTATIONAL METHODS IN APPLIED MATHEMATICS, 2015, 15 (03) : 279 - 289
[32] Object Tracking via 2DPCA and l1-Regularization
Wang, Dong
Lu, Huchuan
IEEE SIGNAL PROCESSING LETTERS, 2012, 19 (11) : 711 - 714
[33] Convergence rates in l1-regularization when the basis is not smooth enough
Flemming, Jens
Hegland, Markus
APPLICABLE ANALYSIS, 2015, 94 (03) : 464 - 476
[34] A unified approach to convergence rates for l1-regularization and lacking sparsity
Flemming, Jens
Hofmann, Bernd
Veselic, Ivan
JOURNAL OF INVERSE AND ILL-POSED PROBLEMS, 2016, 24 (02): : 139 - 148
[35] On Tolerant Fuzzy c-Means Clustering with L1-Regularization
Hamasuna, Yukihiro
Endo, Yasunori
Miyamoto, Sadaaki
PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE, 2009, : 1152 - 1157
[36] ROBUST UNCERTAINTY QUANTIFICATION USING PRECONDITIONED LEAST-SQUARES POLYNOMIAL APPROXIMATIONS WITH l1-REGULARIZATION
Van Langenhove, J. W.
Lucor, D.
Belme, A.
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 2016, 6 (01) : 57 - 77
[37] Direct Incorporation of L1-Regularization into Generalized Matrix Learning Vector Quantization
Lischke, Falko
Neumann, Thomas
Hellbach, Sven
Villmann, Thomas
Boehme, Hans-Joachim
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2018, PT I, 2018, 10841 : 657 - 667
[38] L1-Regularization Based EEG Feature Learning for Detecting Epileptic Seizure
Hussein, Ramy
Wang, Z. Jane
Ward, Rabab
2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP), 2016, : 1171 - 1175
[39] Binarized l1-Regularization Parameters Enhanced Stripe-Wise Optimization Algorithm for Efficient Neural Network Optimization
Ma, Xiaotian
Sun, Pu
Luo, Shiyi
Peng, Qidi
Demara, Ronald F.
Bai, Yu
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS, 2024, 5 (02): : 790 - 799
[40] Accelerating Cross-Validation in Multinomial Logistic Regression with l1-Regularization
Obuchi, Tomoyuki
Kabashima, Yoshiyuki
JOURNAL OF MACHINE LEARNING RESEARCH, 2018, 19

← 1 2 3 4 5 →