M
Mohsen Kamrani
Researcher at University of Tennessee
Publications - 23
Citations - 611
Mohsen Kamrani is an academic researcher from University of Tennessee. The author has contributed to research in topics: Crash & Volatility (finance). The author has an hindex of 10, co-authored 20 publications receiving 391 citations. Previous affiliations of Mohsen Kamrani include University of South Florida & Universiti Teknologi Malaysia.
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How instantaneous driving behavior contributes to crashes at intersections: Extracting useful information from connected vehicle message data.
TL;DR: A methodology to quantify variations in vehicular movements utilizing longitudinal and lateral volatilities and proactively studies the impact of instantaneous driving behavior on type of crashes at intersections to identify hotspot intersections where the frequency of crashes is low, but the longitudinal/lateral driving volatility is high.
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Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections
TL;DR: System improvements due to automation and connectivity across varying CAV market penetration scenarios are explored and ACC/CACC vehicles were found to improve mobility performance in terms of average speed and travel time at intersections.
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Extracting Useful Information from Basic Safety Message Data: An Empirical Study of Driving Volatility Measures and Crash Frequency at Intersections:
TL;DR: In this paper, the concept of driving volatility is defined and explored in the context of high-frequency connected and automated vehicle data, where analysts can extract useful information from them and explore the driving volatility.
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How is driving volatility related to intersection safety? A Bayesian heterogeneity-based analysis of instrumented vehicles data
TL;DR: This study develops a fundamental understanding of microscopic driving volatility and how it relates to unsafe outcomes at intersections and presents a methodology to quantify driving volatility at 116 intersections by analyzing more than 230 million real-world Basic Safety Messages.
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The role of pre-crash driving instability in contributing to crash intensity using naturalistic driving data.
TL;DR: With volatile driving serving as a leading indicator of crash intensity, given the crashes analyzed in this study, early warnings and alerts for the subject vehicle driver and proximate vehicles can be helpful when volatile behavior is observed.