Method and system of road driving optimization with decoupling of vehicle status and traffic factors

A tangible, non-transitory, machine-readable medium, comprising machine-readable instructions, that when executed by a processor, cause the processor to:

• receive personalized operator profile, external sensor data, and vehicle-state data;
• analyze the external sensor data and the vehicle-state data to determine an instant traction force, a plurality of trigger events, and an achievable speed range for each of the plurality of trigger events;
• input the plurality of determined trigger events and the determined achievable speed range for each of the plurality of trigger events into a decoupling estimator to determine a maximum free flow distance and to determine an arrival speed at the maximum free flow distance;
• input the personalized operator profile, the instant traction force, the determined maximum free flow distance, and the determined arrival speed at the maximum free flow distance into a machine learning model to predict a speed profile to arrive at the maximum free flow distance, wherein the predicted speed profile is configured to minimize a fuel consumption and a jerk motion of a host vehicle;
• and
• drive the host vehicle toward the maximum free flow distance in accordance with the predicted speed profile.

A system for driving a host vehicle, comprising:

• a data-base configured to store a retriable and updatable personalized driver profile;
• a plurality of vehicle sensors configured to collect external sensor data, vehicle-state data, and communications data;
• a control module configured to analyze the external sensor data, vehicle-state data, and communications data to detect a plurality of trigger events, an achievable speed range for each of the plurality of trigger events, and an instant traction force;
• a decoupling estimator module configured to analyze the plurality of trigger events and the achievable speed range for each of the plurality of trigger events to determine a maximum free flow distance and an arrival speed at the maximum free flow distance;
• a pretrained machine learning (ML) model configured predict a speed profile of the host vehicle approaching the maximum free flow distance based on the instant traction force, the maximum free flow distance, the determined arrival speed at the maximum free flow distance, and an updated personalized driver profile;
• and
• a cruise control system configured to implement the predicted speed profile;
• and
• wherein the predicted speed profile is configured to minimize a fuel consumption and a jerk motion of the host vehicle.