Cooperative artificial intelligent assisted driving

A system comprising:

• one or more processors;
• and
• memory operatively connected to the one or more processors and including computer code, that when executed by the one or more processors, causes the system to:
• use a machine learning model to group vehicles into clusters based on traffic-related behavior, wherein the traffic-related behavior for each cluster is associated with different agility levels of the vehicles;
• define one or more traffic roles based on the agility level of the vehicles;
• assign a traffic role to a connected vehicle within a traffic segment;
• execute a driving maneuver for the connected vehicle according to a driving policy associated with the connected vehicle's traffic role;
• and
• refine the driving policy based on reinforcement learning.

A vehicle-comprising:

• one or more processors;
• and
• memory operatively connected to the one or more processors and including computer code, that when executed, causes the one or more processors to:
• use a machine learning model to group vehicles into clusters based on traffic-related behavior, wherein the traffic-related behavior for each cluster is associated with different agility levels of the vehicles;
• define one or more traffic roles based on the agility level of the vehicles;
• determine a traffic state for a traffic segment, the traffic state comprising information associated with one or more vehicles within the traffic segment;
• assign a traffic role to a second vehicle within the traffic segment;
• execute a driving maneuver for the second vehicle according to a driving policy associated with the second vehicle's traffic role;
• and
• refine the driving policy based on reinforcement learning.