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Conference Papers Year : 2016

Optimized trajectory planning for Cybernetic Transportation Systems


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.
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Dates and versions

hal-01356691 , version 1 (26-08-2016)


  • HAL Id : hal-01356691 , version 1


Fernando Garrido, David Gonzalez Bautista, Vicente Milanés, Joshué Pérez, Fawzi Nashashibi. Optimized trajectory planning for Cybernetic Transportation Systems. 9th IFAC Symposium on Intelligent Autonomous Vehicles IAV 2016, Jun 2016, Leipzig, Germany. pp.1-6. ⟨hal-01356691⟩


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