Abstract
Autonomous vehicles on city roads and especially in pedestrian environments require agility to navigate narrow passages and turn in tight spaces, leading to the need for a real-time, robust and adaptable controller. In this paper, we present orientation and context aware controllers for autonomous vehicles that can closely track the reference path wit alh respect to the current state of the vehicle, environmental properties, and the desired target orientation at the desired target location. Our proposed controllers are derived from the widely used pure pursuit controller. We validate our proposed controllers with respect to the baseline pure pursuit controller in simulation and on a full-size autonomous vehicle in a pedestrian environment. Our experimental results suggest significant improvements in adaptability and tracking performance compared to the pure pursuit controller.