# WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving

## TL;DR

WiseMove is a modular software framework designed to explore safe deep reinforcement learning techniques specifically for motion planning in autonomous driving, balancing safety, functionality, and scalability.

## Contribution

The paper introduces WiseMove, a flexible, modular framework that facilitates research on safe deep reinforcement learning for autonomous vehicle motion planning.

## Key findings

- Demonstrated WiseMove on a common traffic scenario
- Showcased its adaptability to new technologies and research questions
- Supported ongoing safe learning research in autonomous driving

## Abstract

Machine learning can provide efficient solutions to the complex problems encountered in autonomous driving, but ensuring their safety remains a challenge. A number of authors have attempted to address this issue, but there are few publicly-available tools to adequately explore the trade-offs between functionality, scalability, and safety. We thus present WiseMove, a software framework to investigate safe deep reinforcement learning in the context of motion planning for autonomous driving. WiseMove adopts a modular learning architecture that suits our current research questions and can be adapted to new technologies and new questions. We present the details of WiseMove, demonstrate its use on a common traffic scenario, and describe how we use it in our ongoing safe learning research.