Abstract
<jats:p>The integration of Artificial Intelligence and Natural Language Processing (NLP) is transforming transportation safety by enabling real-time, automated incident reporting and response. NLP techniques such as entity recognition, sentiment analysis, and event classification allow for efficient extraction of critical data from unstructured sources like driver reports, emergency calls, and social media. This enhances operational awareness, reduces response times, and supports proactive safety strategies. By merging NLP with systems like GIS, IoT, and generative AI, transportation agencies can optimize dispatching, improve decision-making, and foster data-driven safety cultures. In multilingual, data-rich environments - especially in Southeast Asia - tailored NLP solutions further address communication barriers and reporting gaps. The future of transportation safety lies in leveraging advanced, ethically governed NLP models for adaptive and inclusive urban mobility systems.</jats:p>