DC4. Road user profiling using multimodal data of naturalistic driving databases

Shi Qiu

Education
Master in Artificial Intelligence from UO University of Groningen
About
A PhD student who works on AI and Road Safety with a focus on utilizing multimodal naturalistic driving data to analyze road risk factors by creating AI software. Enjoys learning novel CV and LLM skills, achieving cool ideas in different fields with AI, making plans for future self-development and career in advance, communicating and exchanging thoughts about life, career, academia, history, politics and anything interesting. Being responsible, trustworthy, proactive and kind are the requirements I made for myself. Facing mistakes straightly and correcting them proactively are something I am proud of myself.

Hosts: UH & CARDIO

Objectives:

  • To automatically create road user profiles from naturalistic driving data
  • To create automated analysis techniques for extraction of important safety features and risk factors from road environment video data
  • To translate results of driving profiling into effective recommendation of videos and post-trip personalised coaching for improving safe driving behaviour

Expected results:

  • The creation of AI software for improved road user scoring and profiling
  • The creation of AI software for the extraction of safety features and risk factors from dashcam videos
  • The translation of driving profiles into intelligent recommendation of relevant videos and post-trip personalised coaching for improving road user behaviour

Planned secondment(s):

  • Image processing lab at the ISEL Purpose: to obtain deeper knowledge of AI techniques for automatic analysis of video data