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Optimized trajectory planning for Cybernetic Transportation Systems

  • Fernando Garrido
  • , David González
  • , Vicente Milanés
  • , Joshué Pérez
  • , Fawzi Nashashibi
  • Institut national de recherche en informatique et en automatique
  • VeDeCoM institute

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper describes the development of an optimized path planning algorithm for automated vehicles in urban environments. This path planning is developed on the basis of urban environments, where Cybernetic Transportation Systems (CTS) will operate. Our approach is mainly affected by vehicle's kinematics and physical road constraints. Based on this assumptions, computational time for path planning can be significantly reduced by creating an off-line database that already optimized all the potential trajectories in each curve the CTS can carry out. Therefore, this algorithm generates a database of smooth and continuous curves considering a big set of different intersection scenarios, taking into account the constraints of the infrastructure and the physical limitations of the vehicle. According to the real scenario, the local planner selects from the database the appropriate curves from searching for the ones that fit with the intersections defined on it. The path planning algorithm has been tested in simulation using the previous control architecture. The results obtained show path generation improvements in terms of smoothness and continuity. Finally, the proposed algorithm was compared with previous path planning algorithms for its assessment.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalIFAC-PapersOnLine
Volume49
Issue number15
DOIs
Publication statusPublished - 2016
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Path planning
  • cost function
  • database
  • intelligent algorithm
  • optimization

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