Self-driving Paths for Automobile Urban Parking

Renan P. Vieira; Eduardo V. Argento; Téo C. Revoredo, IEEE Member

doi:10.20906/SBAI-SBSE-2023/3855

Renan P. Vieira Programa de Pós-Graduação em Engenharia Eletrônica, Departamento de Engenharia Eletrônica e de Telecomunicações, Universidade do Estado do Rio de Janeiro, RJ
Eduardo V. Argento Departamento de Engenharia Elétrica, Pontifícia Universidade Católica do Rio de Janeiro, RJ
Téo C. Revoredo, IEEE Member Departamento de Engenharia Eletrônica e de Telecomunicações, Universidade do Estado do Rio de Janeiro, RJ

DOI: https://doi.org/10.20906/SBAI-SBSE-2023/3855

Keywords: Car-like mobile robots, Motion planning, autonomous parking, Genectic algorithm

Abstract

This text discusses autonomous vehicles for parking in smart cities. Three path generation methods are implemented to avoid obstacles: geometric shapes, polynomial parameterization, and genetic algorithm. Tracking uses a pure pursuit algorithm. The results in a simulated 3D environment show the effectiveness of the algorithms. For example, for parallel front-in parking, the method based on genetic algorithm was the fastest (17.59 s) and shortest (1.768 m). For reverse perpendicular parking, the method with geometric shapes performed best (16.39 s and 1.645 m). This provides a basis for further investigations into autonomous parking.