# Decentralized Cooperative Merging of Platoons of Connected and Automated Vehicles at Highway On-Ramps

arXiv: https://arxiv.org/abs/2002.04826 · HTML: https://mlsanity.com/paper/2002.04826/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning](https://mlsanity.com/paper/2111.13966/) (2021)

## Abstract (arXiv)

In this paper, we propose an optimization framework for cooperative merging of platoons of connected and automated vehicles at highway on-ramps. The framework includes (1) an optimal scheduling algorithm, through which, each platoon derives the sequence and time to enter the highway safely, and (2) an optimal control algorithm that allows each platoon to derive its optimal control input (acceleration/deceleration) in terms of fuel consumption. We evaluate the efficacy of the proposed optimization framework through VISSIM-MATLAB simulation environment. The proposed framework significantly reduces the crossing time and fuel consumption of platoons at the highway on-ramps.