Prioritizing collision avoidance and vehicle stabilization for autonomous vehicles

One approach to autonomous vehicle control is to generate and then track a desired trajectory without explicit consideration of vehicle stability. Stabilization is then entrusted to the vehicle's built-in production systems, such as electronic stability control, which constantly augment driving inputs to ensure stability. Other approaches explicitly consider stabilization criteria and implement permanently active constraints on the vehicle's actions. Situations exist, however, where enforcing stability constraints could lead to an otherwise avoidable collision. This paper presents an alternative paradigm for autonomous vehicle control that explicitly considers vehicle stability and environmental boundaries as it attempts to track a trajectory; such a mediator can choose to violate short term stability constraints in order to avoid a collision. Model predictive control provides an implementation framework, and an autonomous vehicle demonstrates the viability of the controller as it performs aggressive maneuvers. Driving around a turn at the vehicle's limits exhibits the importance of vehicle stability for autonomous vehicle control. Performing an emergency double lane change, however, highlights a situation where stability criteria must be temporarily violated to avoid a collision.