Causal Modeling of Human Drivers
Project Abstract/Statement of Work:
Autonomous vehicles (AVs) have potential for both improving safety and efficiency as well as detracting from them. In our view, both traffic flow and safety will be maximized by self-driving cars implementing what we are calling the Minimum Disruption (MD) Principle, i.e., causing the smallest change possible to the trajectories of other vehicles (and other traffic participants). Under this principle, the path planning problem can then be formulated as follows: 1) determine a set of reasonable possible actions that satisfy basic safety constraints and are consistent with the goal of the AV; 2) calculate the disruption caused to other drivers by each possible action; 3) execute the action that causes the least disruption. The goal of this research is to enable part 2) of this planning problem by developing a model of the way a human-driven vehicle responds to an action taken by a neighboring vehicle.