# A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications

arXiv: https://arxiv.org/abs/2005.13781 · HTML: https://mlsanity.com/paper/2005.13781/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2020.

## Built on by (most cited first, 8 of 8)

- [A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook](https://mlsanity.com/paper/2401.01454/) (2024)
- [Social Coordination and Altruism in Autonomous Driving](https://mlsanity.com/paper/2107.00200/) (2021)
- [Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic](https://mlsanity.com/paper/2202.00881/) (2022)
- [Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic](https://mlsanity.com/paper/2107.05664/) (2021)
- [Towards Learning Generalizable Driving Policies from Restricted Latent Representations](https://mlsanity.com/paper/2111.03688/) (2021)
- [Augmented Driver Behavior Models for High-Fidelity Simulation Study of Crash Detection Algorithms](https://mlsanity.com/paper/2208.05540/) (2022)
- [A Survey on Datasets for Decision-making of Autonomous Vehicle](https://mlsanity.com/paper/2306.16784/) (2023)
- [Learning-based social coordination to improve safety and robustness of cooperative autonomous vehicles in mixed traffic](https://mlsanity.com/paper/2211.11963/) (2022)

## Abstract (arXiv)

Short-term future of automated driving can be imagined as a hybrid scenario in which both automated and human-driven vehicles co-exist in the same environment. In order to address the needs of such road configuration, many technology solutions such as vehicular communication and predictive control for automated vehicles have been introduced in the literature. Both aforementioned solutions rely on driving data of the human driver. In this work, we investigate the currently available driving datasets and introduce a real-world maneuver-based driving dataset that is collected during our urban driving data collection campaign. We also provide a model that embeds the patterns in maneuver-specific samples. Such model can be employed for classification and prediction purposes.