Collision-Cones-Based Nonlinear-Controller for Obstacle-Avoidance with Improved Control Gains

Recent studies on autonomous vehicles have shown that collision avoidance control strategies, based on collision cones techniques, present favorable results when ensuring driving safety in controlled scenarios. In this paper, authors present a collision avoidance control method, based on the strategy of collision cones, in which the control gains of the nonlinear Lyapunov candidate functions are dynamically determined according to the ‘time-till-collision-occurs’, ensuring the avoiding maneuver to converge in a specific laps time. Moreover, the nonlinear vehicle plant model, introduced making use of a rotational transformation from inertial to non-inertial reference frame, considers the non-negligible gyroscopic term. Quality and performances of both braking and steering avoidance maneuvers are tested by using a vehicle dynamics simulator, CarSim<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup>, with an extended ADAS sensors package, to validate the proposed control approach on a full-scale and unknown mathematical model, even in presence of unmodelled dynamics.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/isem62699.2024.10786771
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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article

Collision-Cones-Based Nonlinear-Controller for Obstacle-Avoidance with Improved Control Gains

Riccardo Cespi, S. Di Gennaro
1 citations
Robotic Path Planning Algorithms
0.25
article

Collision-Cones-Based Nonlinear-Controller for Obstacle-Avoidance with Improved Control Gains

Riccardo Cespi, S. Di Gennaro
article en
1 citations

Abstract

Recent studies on autonomous vehicles have shown that collision avoidance control strategies, based on collision cones techniques, present favorable results when ensuring driving safety in controlled scenarios. In this paper, authors present a collision avoidance control method, based on the strategy of collision cones, in which the control gains of the nonlinear Lyapunov candidate functions are dynamically determined according to the ‘time-till-collision-occurs’, ensuring the avoiding maneuver to converge in a specific laps time. Moreover, the nonlinear vehicle plant model, introduced making use of a rotational transformation from inertial to non-inertial reference frame, considers the non-negligible gyroscopic term. Quality and performances of both braking and steering avoidance maneuvers are tested by using a vehicle dynamics simulator, CarSim<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup>, with an extended ADAS sensors package, to validate the proposed control approach on a full-scale and unknown mathematical model, even in presence of unmodelled dynamics.

University of L'Aquila (IT), Tecnológico de Monterrey (MX)
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Openalex Percentile: Top 44%
Robotic Path Planning Algorithms
0.25
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