# Adaptive Game-Theoretic Decision Making for Autonomous Vehicle Control at Roundabouts

arXiv: https://arxiv.org/abs/1810.00829 · HTML: https://mlsanity.com/paper/1810.00829/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2018.

## Built on by (most cited first, 11 of 11)

- [A Survey of Deep RL and IL for Autonomous Driving Policy Learning](https://mlsanity.com/paper/2101.01993/) (2021)
- [Cooperative Driving of Connected Autonomous Vehicles in Heterogeneous Mixed Traffic: A Game Theoretic Approach](https://mlsanity.com/paper/2305.03563/) (2023)
- [I Know You Can't See Me: Dynamic Occlusion-Aware Safety Validation of Strategic Planners for Autonomous Vehicles Using Hypergames](https://mlsanity.com/paper/2109.09807/) (2021)
- [Generalized dynamic cognitive hierarchy models for strategic driving behavior](https://mlsanity.com/paper/2109.09861/) (2021)
- [Agile Decision-Making and Safety-Critical Motion Planning for Emergency Autonomous Vehicles](https://mlsanity.com/paper/2409.08665/) (2024)
- [GTP-UDrive: Unified Game-Theoretic Trajectory Planner and Decision-Maker for Autonomous Driving in Mixed Traffic Environments](https://mlsanity.com/paper/2406.14077/) (2024)
- [A taxonomy of strategic human interactions in traffic conflicts](https://mlsanity.com/paper/2109.13367/) (2021)
- [Modeling Human Driver Interactions Using an Infinite Policy Space Through Gaussian Processes](https://mlsanity.com/paper/2201.01733/) (2022)
- [Revealed Multi-Objective Utility Aggregation in Human Driving](https://mlsanity.com/paper/2303.07435/) (2023)
- [Measuring Sociality in Driving Interaction](https://mlsanity.com/paper/2306.13992/) (2023)
- [Large Language Model based Interactive Decision-Making for Autonomous Driving](https://mlsanity.com/paper/2604.23513/) (2026)

## Abstract (arXiv)

In this paper, we propose a decision making algorithm for autonomous vehicle control at a roundabout intersection. The algorithm is based on a game-theoretic model representing the interactions between the ego vehicle and an opponent vehicle, and adapts to an online estimated driver type of the opponent vehicle. Simulation results are reported.