22 citations · 53 across the 19 of their papers we have counts for
21 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…
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…
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…
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…
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…
An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting
Qiyuan Zhu, A. K. Qin, Hussein Dia +2
Traffic flow forecasting is a crucial task in intelligent transport systems. Deep learning offers an effective solution, capturing complex patterns in time-series traffic flow data…