Computing a multi-dimensional personalized adaptive cruise control parameter

A vehicle comprising:

• one or more processors;
• and
• memory storing instructions, which when executed by the one or more processors, cause the vehicle to perform operations, the operations comprising:
• computing an Adaptive Cruise Control (ACC) parameter personalized for a driver of the vehicle, wherein the personalized ACC parameter comprises a multi-dimensional vector reflecting preferred following gaps for the driver across different human contexts and environmental contexts;
• during at least a portion of ACC operation of the vehicle, using the personalized ACC parameter to compute a target following gap for following a second vehicle;
• and
• controlling speed of the vehicle in accordance with the target following gap.

A vehicle comprising:

• one or more in-cabin sensors;
• one or more processors;
• and
• memory storing instructions, which when executed by the one or more processors, cause the vehicle to perform operations, the operations comprising:
• during operation of adaptive cruise control (ACC) in the vehicle, dynamically receiving:
• (a) real-time biometric data of a driver of the vehicle from the one or more in-cabin sensors,
• (b) real-time environmental condition data,
• (c) real-time data indicating speeds of the vehicle and following gaps following other vehicles, and
• (d) real-time driving inputs provided by the driver;
• correlating (a)-(d) to generate time series data reflecting preferred following gaps for the driver at different vehicle speeds across different human contexts and environmental contexts;
• and
• based on the time series data, dynamically computing an ACC parameter personalized for the driver, wherein the personalized ACC parameter comprises a multi-dimensional vector reflecting the preferred following gaps for the driver at different vehicle speeds across different human contexts and environmental contexts.