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Research Papers

Simple Clothoid Lane Change Trajectories for Automated Vehicles Incorporating Friction Constraints

[+] Author and Article Information
Joseph Funke

Dynamic Design Laboratory,
Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305
e-mail: jfunke@stanford.edu

J. Christian Gerdes

Dynamic Design Laboratory,
Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305
e-mail: gerdes@stanford.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 1, 2013; final manuscript received November 15, 2015; published online December 11, 2015. Editor: Joseph Beaman.

J. Dyn. Sys., Meas., Control 138(2), 021002 (Dec 11, 2015) (9 pages) Paper No: DS-13-1256; doi: 10.1115/1.4032033 History: Received July 01, 2013; Revised November 15, 2015

This paper demonstrates that an autonomous vehicle can perform emergency lane changes up to the friction limits through real-time generation and evaluation of bi-elementary paths. Path curvature and friction determine the maximum possible speed along the path and, consequently, the feasibility of the path. This approach incorporates both steering inputs and changes in speed during the maneuver. As a result, varying path parameters and observing the maximum possible entry speed of resulting paths give insight about when and to what extent a vehicle should brake and turn during emergency lane change maneuvers. Tests on an autonomous vehicle validate this approach for lane changes near the limits of friction.

Copyright © 2016 by ASME
Topics: Friction , Vehicles , Braking
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References

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Figures

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Fig. 1

Acceleration limits based on a friction circle model

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Fig. 2

Lane change and path parameters

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Fig. 3

Generalized elementary path curvature profile

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Fig. 4

Symmetry of generalized elementary path

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Fig. 5

Determining a speed profile for a path

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Fig. 6

Varying γ for a lane change path

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Fig. 7

γ maximizing entry speed as X varies

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Fig. 8

Varying β for a lane change path

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Fig. 9

β maximizing entry speed as X varies

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Fig. 10

Varying λ for a lane change path

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Fig. 11

λ maximizing entry speed as X varies

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Fig. 12

Autonomous Audi TTS

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Fig. 13

Lane change paths traveled by vehicle

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Fig. 14

Speed profile and actual vehicle speed

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Fig. 15

Acceleration limits and experimental results

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