Design of Genetic Algorithms for the Simulation-Based Training of Artificial Neural Networks in the Context of Automated Vehicle Guidance

被引：0

作者：

Yarom, Or Aviv ^{[1
]}

Jacobitz, Sven ^{[1
]}

Liu-Henke, Xiaobo ^{[1
]}

机构：

[1] Ostfalia Univ Appl Sci, Dept Mech Engn, Wolfenbuettel, Germany

来源：

PROCEEDINGS OF THE 2020 19TH INTERNATIONAL CONFERENCE ON MECHATRONICS - MECHATRONIKA (ME) | 2020年

关键词：

Artificial Intelligence; AI; Artificial Neural Networks; ANN; Machine Learning; Gradient Free Reinforcement Learning; Genetic Algorithm; GA; Model-Based Design; Automated Lateral Guidance;

D O I：

10.1109/me49197.2020.9286464

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper describes the design of a Genetic Algorithm (GA) for intelligent control systems with Artificial Neural Networks (ANNs) in the context of autonomous driving in a model-based and verification-oriented process. First, a summary of the state of the art is given on the use of ANNs and GAs in control engineering. This is followed by an explanation of the design methodology used in this paper. Then the concept of a universal GA for the (simulation-based) training of any common ANNs is presented. Afterwards the design of the GA is explained in detail. Special aspects of parameterization and algorithms are also discussed. Finally, the presented method is validated by an example of a model-based design of a driving function based on an ANN for automated lateral guidance.

引用

页码：254 / 261

页数：8

共 20 条

[1] [Anonymous], 2017, MACHINE LEARNING CON
[2] CHARNEY DM, 1991, IEEE IJCNN, P1989, DOI 10.1109/IJCNN.1991.170673
[3] Du CY, 2006, WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, P2859
[4] Eraqi H. E., 2016, 8 INT C EV COMP THEO
[5] Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
Feng, Di
Haase-Schutz, Christian
Rosenbaum, Lars
Hertlein, Heinz
Glaser, Claudius
Timm, Fabian
Wiesbeck, Werner
Dietmayer, Klaus
[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (03) : 1341 - 1360
[6] Gomez-Avila J., 2019, Artificial Neural Networks for Engineering Applications, P55
[7] Jurado F., 2019, ARTIFICIAL NEURAL NE, P39
[8] Khandavalli G. B., 2020, 10 INT MUN CHASS S 2
[9] Kim SJ, 2018, INT C CONTR AUTOMAT, P1654
[10] Krupka P., 2020, 10 INT MUN CHASS S 2

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