# Distributed Cooperative Driving in Multi-Intersection Road Networks

arXiv: https://arxiv.org/abs/2104.10313 · HTML: https://mlsanity.com/paper/2104.10313/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Apr 2021.

## Built on by (most cited first, 4 of 4)

- [Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks](https://mlsanity.com/paper/2106.13052/) (2021)
- [Roadside Units Assisted Localized Automated Vehicle Maneuvering: An Offline Reinforcement Learning Approach](https://mlsanity.com/paper/2405.03935/) (2024)
- [Coordinating CAV Swarms at Intersections with a Deep Learning Model](https://mlsanity.com/paper/2211.05297/) (2022)
- [Fault-Tolerant MARL for CAVs under Observation Perturbations for Highway On-Ramp Merging](https://mlsanity.com/paper/2511.23193/) (2025)

## Abstract (arXiv)

Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years. However, cooperative driving in multi-intersection road networks remains to be further investigated, because many algorithms for isolated intersection cannot be directly adopted for road networks. In this paper, we propose a distributed strategy to appropriately decompose the problem into small-scale sub-problems that address vehicle cooperation within limited temporal-spatial areas and meanwhile assure appropriate coordination between adjacent areas by specially designed information exchange. Simulation results demonstrate the efficiency-complexity balanced advantage of the proposed strategy under various traffic demand settings.