Path Planning and Control Strategies for a Semi-Autonomous Light Commercial Vehicle Navigating and Avoiding Static Obstacles in Urban Environments

<div class="section abstract"><div class="htmlview paragraph">This paper presents the design and implementation of a Semi-Autonomous Light Commercial Vehicle (LCV) capable of following a person while performing obstacle avoidance in urban and controlled environments. The LCV leverages its onboard 360-degree view camera, RTK-GNSS, Ultrasonic sensors, and algorithms to independently navigate the environment, avoiding obstacles and maintaining a safe distance from the person it is following. The path planning algorithm described here generates a secondary lateral path originating from the primary driving path to navigate around static obstacles. A Behavior Planner is utilized to decide when to generate the path and avoid obstacles. The primary objective is to ensure safe navigation in environments where static obstacles are prevalent. The LCV's path tracking is achieved using a combination of Pure Pursuit and Proportional-Integral (PI) controllers. The Pure Pursuit controller is utilized as lateral control to follow the generated path, ensuring smooth and accurate path tracking. Additionally, a PI controller is utilized for speed control, maintaining a consistent and safe speed. Multiple tests were conducted in various urban and controlled environments, especially densely-parked city roads, ramps, residential streets to evaluate the LCV's performance. The results demonstrate the LCV's ability to safely avoid parked vehicles showing human-like decision making and motion control, also maintaining a consistent following distance with the lead-person. The solution focuses on slow-speed applications where precision is of utmost priority. Additionally, the application of ultrasonic sensors helped in achieving immediate stops in close proximity scenarios. This system has significant potential for applications in last-mile delivery, logistics, waste management, and urban mobility, offering a versatile solution for safe and efficient navigation in complex environments and narrow roads.</div></div>