Intent-Aware Autonomous Driving: A Case Study on Highway Merging Scenarios
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Abstract (arXiv)
In this work, we use the communication of intent as a means to facilitate cooperation between autonomous vehicle agents. Generally speaking, intents can be any reliable information about its future behavior that a vehicle communicates with another vehicle. We implement this as an intent-sharing task atop the merging environment in the simulator of highway-env, which provides a collection of environments for learning decision-making strategies for autonomous vehicles. Under a simple setting between two agents, we carefully investigate how intent-sharing can aid the receiving vehicle in adjusting its behavior in highway merging scenarios.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 22 Sep 2023.
Builds on
8 of 17 references.
References · 8
- 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
- 2021Social Coordination and Altruism in Autonomous Drivingcited by 28
- 2019Cooperation-Aware Reinforcement Learning for Merging in Dense Trafficcited by 20
- 2020Towards Learning Multi-agent Negotiations via Self-Playcited by 17
- 2018Intent-aware Multi-agent Reinforcement Learningcited by 12
- 2021Spatial Intention Maps for Multi-Agent Mobile Manipulationcited by 11
- 2022Autonomous Highway Merging in Mixed Traffic Using Reinforcement Learning and Motion Predictive Safety Controllercited by 7
- 2017Intent Communication between Autonomous Vehicles and Pedestrianscited by 2
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.