A Utility Maximization Model of Pedestrian and Driver Interactions

Many models account for the traffic flow of road users, but few take the details of local interactions into consideration and how they could deteriorate into safety-critical situations. Building on an existing model of human sensorimotor control, we develop an agent-based modeling framework applying the principles of utility maximization, motor primitives, and intermittent action decisions to account for the details of interactive behaviors among road users. The framework connects the three principles to the decision theory and is tested to determine whether such an approach can reproduce the following four phenomena. Firstly, when two pedestrians travel on crossing paths, their interaction is sensitive to initial kinematic asymmetries, and secondly, based on the asymmetries, the two pedestrians rapidly resolve collision conflict by adapting their behaviors. Thirdly, when a pedestrian crosses a road while facing an approaching car, the pedestrian adapts his or her crossing behavior according to the time-to-arrival of the car, and fourthly, either the pedestrian or the driver of the car may yield to the other to resolve their conflict. We show that these phenomena emerge naturally from our modeling framework. We believe the proposed behavior model and phenomenon-centered approach of analysis offer promising tools to examine road user interactions. We conclude with a discussion on how the model can be generalized to safety-critical situations and to include other variables affecting road-user interactions.

Automated summary

This study develops an agent-based modeling framework to account for the details of interactive behaviors among road users. By testing the framework, the researchers found that it can reproduce various interaction phenomena, offering promising tools for studying road user interactions.