Abstract
This article proposes a simple simulation methodology that allows to experiment with the dynamic behavior of vehicles, which applies control laws that allow automated driving in unstructured environments, through the use of robotic application simulation software Webots, which shortens the experimentation times of autonomous driving systems, It also allows to overcome the limitations that this type of projects involves, such as, high infrastructure costs, the difficulties of validating the system, qualified personnel and the participation of various elements with different dynamic behaviors that make up a real traffic space. The use of the virtualized model of a BMW X5 vehicle and the instrumentation of multiple sensors necessary for its operation are presented. Finally, a path tracking algorithm is developed using Matlab scientific programming software, and the dynamic behavior of the vehicle is evaluated through the response curves of the robot states, these results represent the starting point for future research and the implementation of physical tests.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kümmerle, R., Hähnel, D., Dolgov, D., Thrun, S., Burgard, W.: Autonomous driving in a multi-level parking structure. In: Proceedings - IEEE International Conference on Robotics and Automation, pp. 3395–3400 (2009)
Toibero, M., Roberti, F., Herrera, D., Amicarelli, A., Carelli, R.: Controlador Estable para Seguimiento de Caminos en Robots Car-Like basado en Espacio Nulo. In: 2015 XVI Work. Inf. Process. Control (RPIC), Co-sponsored by IEEE, no. April 2016 (2015)
Mcdonald, M., Jeffery, D., Piao Tecnalia, J., Sanchez, J.: Definition of necessary vehicle and infrastructure systems for automated driving. base.connectedautomateddriving.eu (2011)
Lenain, R., Thuilot, B., Cariou, C., Martinet, P.: Mobile robot control in presence of sliding: application to agricultural vehicle path tracking. In: Proceedings of the IEEE Conference on Decision and Control, pp. 6004–6009 (2006)
Gruyer, D., Magnier, V., Hamdi, K., Claussmann, L., Orfila, O., Rakotonirainy, A.: Perception, information processing and modeling: critical stages for autonomous driving applications. Ann. Rev. Control 44, 323–341 (2017)
Choi, J., Chun, D., Kim, H., Lee, H.-J.: Gaussian YOLOv3: an accurate and fast object detector using localization uncertainty for autonomous driving (2019)
Brumitt, B., Stentz, A., Hebert, M., Group, T.C.U.: Autonomous driving with concurrent goals and multiple vehicles: mission planning and architecture. Auton. Robots 11(2), 103–115 (2001)
Vieira, B., Severino, R., Filho, E.V., Koubaa, A., Tovar, E.: COPADRIVe - a realistic simulation framework for cooperative autonomous driving applications. In: 2019 8th IEEE International Conference on Connected Vehicles and Expo, ICCVE 2019 - Proceedings (2019)
Talpaert, V., et al.: Exploring applications of deep reinforcement learning for real-world autonomous driving systems. In: VISIGRAPP 2019 - Proceeding 14th International Jt. Conference Computer Vision, Imaging Computer Graphical Theory Application, vol. 5, pp. 564–572, January 2019
Tsugawa, S.: Automated driving systems: common ground of automobiles and robots. Int. J. Humanoid Robot. 8(1), 1–12 (2011)
Castaño, F., Beruvides, G., Villalonga, A., Haber, R.E.: Self-tuning method for increased obstacle detection reliability based on internet of things LiDAR sensor models. Sensors (Switzerland) 18(5), 1–16 (2018)
Cachumba, S.J., Briceño, P.A., Andaluz, V.H., Erazo, G.: Autonomous driver assistant for collision prevention. In: ACM International Conference Proceeding Series, pp. 327–332 (2019)
Karoui, O., et al.: Performance evaluation of vehicular platoons using Webots. IET Intell. Transp. Syst. 11(8), 441–449 (2017)
Stotsky, A., Hu, X.: Control of car-like robots using sliding observers for steering angle estimation. In: Proceeding of IEEE Conference Decision Control, vol. 4, no. December, pp. 3648–3653 (1997)
Lee, S., Kim, M., Youm, Y., Chung, W.: Control of a car-like mobile robot for parking problem. In: Proceeding - IEEE International Conference on Robotics and Automation, vol. 1, no. May, pp. 1–6 (1999)
Michel, O.: Webots: professional mobile robot simulation. Int. J. Adv. Robot. Syst. 1(1), 39–42 (2004)
Ma, X., Mu, C., Wang, X., Chen, J.: Projective geometry model for lane departure warning system in webots. In: 2019 5th International Conference on Control, Automation Robotics ICCAR 2019, pp. 689–695 (2019)
Tuncali, C.E., Fainekos, G., Prokhorov, D., Ito, H., Kapinski, J.: Requirements-driven test generation for autonomous vehicles with machine learning components. IEEE Trans. Intell. Veh. 5(2), 265–280 (2020)
colaboradores de Wikipedia, “BMW X5,” (2020)
B, C.S., Meissgeier, F., Bruegge, B., Verclas, S.: System : a cyber-physical human system, vol. 1, no. ii, pp. 267–280 (2016)
Acknowledgements
The authors would like to thank the Escuela Superior Politécnica de Chimborazo ESPOCH for the support to develop the research project “Análisis, diseño e implementación de algoritmos de control inteligente en controladores con una red de sensores IoT en vehículos para mejorar la seguridad vial”; also to Universidad de las Fuerzas Armadas ESPE and the Research Groups GITEA and ARSI, for the support for the development of this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Zea, D.J., Guevara, B.S., Recalde, L.F., Andaluz, V.H. (2021). Dynamic Simulation and Kinematic Control for Autonomous Driving in Automobile Robots. In: Botto-Tobar, M., S. Gómez, O., Rosero Miranda, R., Díaz Cadena, A. (eds) Advances in Emerging Trends and Technologies. ICAETT 2020. Advances in Intelligent Systems and Computing, vol 1302. Springer, Cham. https://doi.org/10.1007/978-3-030-63665-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-030-63665-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-63664-7
Online ISBN: 978-3-030-63665-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)