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Learning Algorithm for Tuning Driving Calibrations

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The present invention provides a system to automatically adjust the driving characteristics of an autonomous/semi-autonomous vehicle in order to better suit customer preferences. This can also be applied to automatically adjustable speed cruise controls and all other levels of automation. By measuring and adjusting driver inputs such as accelerator pedal taps, steering input, manual driving vehicle following habits, comparison to posted speed limits, and other factors, a driver preference can be asserted to make the vehicle's automated performance perform like the driver's desired system. Potential Measurements of the Driver could include: 1.Following distance 2.Maximum non-emergency brake force 3.Maximum lateral acceleration in curves 4.Driving lines (center vs apex) in curves 5. Variance in Speed (eco driving vs steady state speed) 6.Maximum/minimum acceleration.

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    《Research Disclosure》 |2021年第692期|2459-2459|共1页
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