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Performance Guarantees for Collision Avoidance Eric Rossetter Group Talk 5/17/02
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Outline Motivation Recap of linear results Lyapunov function for linear system Simulation results Conclusions/Future Work
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Motivation and Goals Potential field framework for collision avoidance How do we guarantee collision avoidance?
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Potential Field Summary Incorporate collision avoidance into driver assistance systems Control forces are derived from potential functions Vehicle handling characteristics are not changed
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Bounding Lateral Motion Given initial vehicle states how far will it move laterally Lyapunov Approach: –Create and energy like function of the states –Show that the derivative of this function is negative semi-definite
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Hurdles in Finding Lyap. Functions Lateral motion is non-linear Total Energy is not a good bound for lateral motion The sum of kinetic and ‘artificial’ potential energy in the lateral and yaw directions is not a Lyap. Function We know that one exists from the linear analysis!
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Linear System F
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Linear Stability Results 1.Control force must be applied in front of Neutral Steer Point 2.Control Force must come from a projection into the potential function
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Candidate Lyapunov Function In order to be a Lyapunov function it must be positive definite The condition on the last term is: Potential Energy Kinetic Energy Other Stuff
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Lyapunov Function Derivative where,
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Lyapunov Function Derivative Given a quadratic potential function If we choose the lookahead distance to be Using Sylvester’s Criterion
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Non-linear Lyapunov Function Bounds the non-linear system Given knowledge of the states a potential function gain can be chosen to avoid a lateral obstacle
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Simulation Potential Function Gain Chosen to Avoid Obstacle 0.75m away with initial conditions: V=40 m/s Degrees
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Conclusions/Future Work The presented Lyapunov function bounds the lateral motion of a vehicle Guarantees collision avoidance with fixed lateral obstacles Inclusion of road curvature and external disturbances
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