ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?

TL;DR

This paper explores the potential of large language models like ChatGPT to revolutionize intelligent traffic safety research and applications, discussing their capabilities, challenges, and future directions.

Contribution

It introduces the application of ChatGPT in traffic safety, discusses associated controversies, and proposes multi-modality learning for enhanced decision-making.

Findings

ChatGPT can address key traffic safety issues.

LLMs have potential to shape traffic safety research.

Open questions remain for application improvements.

Abstract

ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction about the development of large language models (LLMs). Next, we exemplify using ChatGPT to address key traffic safety issues. Furthermore, we discuss the controversies surrounding LLMs, raise critical questions for their deployment, and provide our solutions. Moreover, we propose an idea of multi-modality representation learning for smarter traffic safety decision-making and open more questions for application improvement. We believe that LLM will both shape and potentially facilitate components of traffic safety research.