A longitudinal inter-vehicle distance controller application for autonomous vehicle platoons

Area of Science:

• Robotics and Control Systems
• Transportation Engineering
• Artificial Intelligence

Background:

• Autonomous vehicle platoons offer solutions for road safety, efficiency, and emission reduction.
• Maintaining consistent inter-vehicle distances is a critical challenge for platoon stability and safety.

Purpose of the Study:

• To propose a cost-efficient algorithm for controlling longitudinal inter-vehicle distance in autonomous vehicle platoons.
• To ensure precise distance control and safe platoon formation using a decentralized approach.

Main Methods:

• A proportional-integral-derivative (PID)-based control algorithm was developed.
• Decentralized calculations and single-sensor data per vehicle were utilized for cost-efficiency.
• The algorithm was implemented in the Robot Operating System (ROS) and tested on 3D vehicle models in simulated environments using the Gazebo platform.

Main Results:

• The proposed algorithm successfully maintained the desired inter-vehicle distance with a maximum absolute error of 5 m.
• Platoon formation was consistently maintained throughout the simulations.
• No collisions occurred among platoon members under various simulated scenarios.

Conclusions:

• The PID-based decentralized algorithm is a viable and cost-efficient solution for controlling inter-vehicle distances in autonomous platoons.
• The simulation results demonstrate the algorithm's effectiveness in demanding scenarios, ensuring safety and formation integrity.