5 papers
Proactive Road Safety Intervention in Australia: Predicting Risky Driving Hotspots from Connected Vehicle Data
Adriana-Simona Mihăiţă, Clarence Cheung, Artur Grigorev +2
Road safety monitoring has historically been reactive, relying on crash-record analysis after fatalities and injuries have already occurred. Proactive identification of high-risk l…
Rapid Quantification of Outdoor Object Visibility in Urban Setting Using Connected-Vehicle Fields of View
Artur Grigorev, Adriana-Simona Mihaita
Identifying locations that offer maximum visual exposure to passing vehicular traffic is a core problem in urban analytics, with applications spanning urban design, navigation, loc…
Long Live Fine-Tuning: Task-Specific Transformers Outperform Zero-Shot LLMs for Misinformation Response Classification on Reddit
JooYoung Lee, Lin Tian, Angela Brillantes +2
As large language models (LLMs) become default tools for online information verification, an implicit assumption follows them: that scale and general capability are sufficient for…
Spatial Association Between Near-Misses and Accident Blackspots in Sydney, Australia: A Getis-Ord Analysis
Artur Grigorev, David Lillo-Trynes, Adriana-Simona Mihaita
Conventional road safety management is inherently reactive, relying on analysis of sparse and lagged historical crash data to identify hazardous locations, or crash blackspots. The…
Automated Traffic Incident Response Plans using Generative Artificial Intelligence: Part 1 -- Building the Incident Response Benchmark
Artur Grigorev, Khaled Saleh, Jiwon Kim +1
Traffic incidents remain a critical public safety concern worldwide, with Australia recording 1,300 road fatalities in 2024, which is the highest toll in 12 years. Similarly, the U…