Summary of Learning a Stable, Safe, Distributed Feedback Controller For a Heterogeneous Platoon Of Autonomous Vehicles, by Michael H. Shaham and Taskin Padir
Learning a Stable, Safe, Distributed Feedback Controller for a Heterogeneous Platoon of Autonomous Vehicles
by Michael H. Shaham, Taskin Padir
First submitted to arxiv on: 18 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA); Robotics (cs.RO); Systems and Control (eess.SY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents an algorithm for learning a stable, safe, and distributed controller for heterogeneous platooning of autonomous vehicles. The goal is to enable each vehicle to maintain a safe distance from its neighbors while following a specified speed set by the leader. Building on recent advancements in neural network stability certificates, our proposed algorithm trains a controller for autonomous platooning in simulation and evaluates its performance on hardware with a platoon of four F1Tenth vehicles. We also conduct further analysis in simulation with a larger platoon of 100 vehicles. Compared to existing controllers like linear feedback and distributed model predictive controllers, the neural network controller demonstrates practicality and effectiveness in increasing safety and fuel efficiency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper is about making self-driving cars travel together safely on highways. The idea is called “platooning,” where each car follows a leader’s speed while keeping a safe distance from others. The team created an algorithm to control these self-driving cars, which they tested in simulation and with real vehicles. They compared their new controller to other methods and showed that it works well for both small and large groups of cars. This could lead to safer and more efficient travel on highways. |
Keywords
* Artificial intelligence * Neural network
