Method and system for impact-based operation of an autonomous agent.
This invention family addresses how an autonomous agent evaluates the effect of its candidate behavior on nearby road users. The method compares simulated futures, measures the impact of ego behavior on surrounding agents, and supports policy selection that accounts for negotiation, progress, and safe interaction in complex environments. In deployed fleet contexts, this kind of impact modeling helps autonomous vehicles negotiate with other road users more predictably and navigate complex interaction scenarios where decision making is critical to safety and rider acceptance.