ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?
It investigates how LLMs could revolutionize intelligent traffic safety systems, though it appears incremental as it builds on existing models without presenting new empirical results.
The paper explores the potential of large language models like ChatGPT to address key traffic safety issues, proposing multi-modality representation learning for smarter decision-making and raising critical questions for deployment.
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.