F
Feng Guo
Researcher at Virginia Tech
Publications - 103
Citations - 4582
Feng Guo is an academic researcher from Virginia Tech. The author has contributed to research in topics: Poison control & Crash. The author has an hindex of 28, co-authored 96 publications receiving 3728 citations. Previous affiliations of Feng Guo include National Institutes of Health & University of Connecticut.
Papers
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Journal ArticleDOI
Driver crash risk factors and prevalence evaluation using naturalistic driving data.
Thomas A. Dingus,Feng Guo,Suzie Lee,Jonathan F. Antin,Miguel A. Perez,Mindy Buchanan-King,Jonathan M. Hankey +6 more
TL;DR: The results show that crash causation has shifted dramatically in recent years, with driver-related factors present in almost 90% of crashes, and definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.
Journal ArticleDOI
Distracted driving and risk of road crashes among novice and experienced drivers
Sheila G. Klauer,Feng Guo,Bruce G. Simons-Morton,Marie Claude Ouimet,Suzanne E. Lee,Thomas A. Dingus +5 more
TL;DR: The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones, and among experienced drivers, the prevalence of high-risk attention to secondary tasks increased over time.
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Network Robustness Index : a new method for identifying critical links and evaluating the performance of transportation networks
TL;DR: In this paper, the authors present a new, comprehensive, system-wide approach to identify critical links and evaluate network performance, which considers network flows, link capacity and network topology.
Journal ArticleDOI
Near Crashes as Crash Surrogate for Naturalistic Driving Studies
TL;DR: In this article, the authors evaluated the use of near crashes as a surrogate measure for assessment of the safety impact of driver behaviors and other risk factors, and concluded that using near crash as a crash surrogate provides definite benefit when naturalistic studies are not large enough to generate sufficient numbers of crashes for statistical analysis.
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Modeling signalized intersection safety with corridor-level spatial correlations.
TL;DR: In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida and the safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated.