👉 Driver math is a mathematical framework used to analyze and optimize the performance of autonomous vehicles, particularly focusing on decision-making under uncertainty. It combines elements from game theory, probability, and control theory to model interactions between vehicles and their environment, as well as among vehicles themselves. The core idea is to represent the decision-making process of a vehicle (the "driver") as a strategic game where each move (action) has potential outcomes influenced by the actions of other vehicles and the environment. By using concepts like Nash equilibrium, driver math helps predict and determine optimal strategies that maximize safety and efficiency while minimizing risks. This approach enables autonomous vehicles to make informed, real-time decisions in complex and dynamic driving scenarios, ensuring smooth and safe navigation.
