# A Grouping Based Cooperative Driving Strategy for CAVs Merging Problems

arXiv: https://arxiv.org/abs/1804.01250 · HTML: https://mlsanity.com/paper/1804.01250/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Apr 2018.

## Built on by (most cited first, 2 of 2)

- [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)

In general, there are two kinds of cooperative driving strategies, planning based strategy and ad hoc negotiation based strategy, for connected and automated vehicles (CAVs) merging problems. The planning based strategy aims to find the global optimal passing order, but it is time-consuming when the number of considered vehicles is large. In contrast, the ad hoc negotiation based strategy runs fast, but it always finds a local optimal solution. In this paper, we propose a grouping based cooperative driving strategy to make a good tradeoff between time consumption and coordination performance. The key idea is to fix the passing orders for some vehicles whose inter-vehicle headways are small enough (e.g., smaller than the pre-selected grouping threshold). From the viewpoint of optimization, this method reduces the size of the solution space. A brief analysis shows that the sub-optimal passing order found by the grouping based strategy has a high probability to be close to the global optimal passing order, if the grouping threshold is appropriately chosen. A series of simulation experiments are carried out to validate that the proposed strategy can yield a satisfied coordination performance with less time consumption and is promising to be used in practice.