Integration of Path Optimization and Obstacle avoidance for Autonomous Precision Immobilization Technique Maneuver

Abstract

The PIT (Precision Immobilization Technique) maneuver is a pursuit tactic used by law-enforcement officials to handle dangerous vehicle pursuit situations, wherein a pursuing car can force a fleeing car to turn sideways abruptly, causing the driver to lose control and stop. Such maneuvers have pitfalls, in that they require sufficient skill on the part of the driver to be carried out. Furthermore, given the utilization of electronic stabilizing control systems in modern vehicles' manual PIT maneuvers require more precision to be carried out. However, the previous decades have also undergone significant changes, in particular the development of autonomous driving technologies, which are now available in commercial vehicles. Autonomous PIT maneuvers could be the next step in handling dangerous vehicle pursuits of fugitives. But for autonomous execution of such maneuvers, accurate path planning and obstacle avoidance must be carried out first. This work presents the implementation of path optimization technique along with obstacle avoidance in simulation environment as well as in physical environment for execution of autonomous PIT maneuvering. Path optimization ensures that the bullet vehicle arrives at the specific point where the PIT maneuver is carried out. An important path optimization method has been utilized to accomplish the goal. Furthermore, obstacle avoidance is integrated with path optimization to avoid mid-way stationary obstacles, thereby adding a more realistic scenario for the same. This paper makes a simplifying assumption that the target vehicle is stationary or moving at a constant velocity, which can be extended by future work to a more realistic scenario involving accelerated target vehicle.