152 citations · 302 across the 14 of their papers we have counts for
14 papers
Accident Impact Prediction based on a deep convolutional and recurrent neural network model
Pouyan Sajadi, Mahya Qorbani, Sobhan Moosavi +1
Traffic accidents pose a significant threat to public safety, resulting in numerous fatalities, injuries, and a substantial economic burden each year. The development of predictive…
Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques
Noushin Behboudi, Sobhan Moosavi, Rajiv Ramnath
Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities annually, with the greatest impact on individuals aged 5 to 29 years old. This paper…
CrashFormer: A Multimodal Architecture to Predict the Risk of Crash
Amin Karimi Monsefi, Pouya Shiri, Ahmad Mohammadshirazi +4
Reducing traffic accidents is a crucial global public safety concern. Accident prediction is key to improving traffic safety, enabling proactive measures to be taken before a crash…
Judge Me in Context: A Telematics-Based Driving Risk Prediction Framework in Presence of Weak Risk Labels
Sobhan Moosavi, Rajiv Ramnath
Driving risk prediction has been a topic of much research over the past few decades to minimize driving risk and increase safety. The use of demographic information in risk predict…
Will there be a construction? Predicting road constructions based on heterogeneous spatiotemporal data
Amin Karimi Monsefi, Sobhan Moosavi, Rajiv Ramnath
Road construction projects maintain transportation infrastructures. These projects range from the short-term (e.g., resurfacing or fixing potholes) to the long-term (e.g., adding a…
Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver Identification
Sobhan Moosavi, Pravar D. Mahajan, Srinivasan Parthasarathy +2
Identifying driving styles is the task of analyzing the behavior of drivers in order to capture variations that will serve to discriminate different drivers from each other. This t…