Feng Guo

6.3k total citations · 3 hit papers
134 papers, 4.7k citations indexed

About

Feng Guo is a scholar working on Safety, Risk, Reliability and Quality, Social Psychology and Transportation. According to data from OpenAlex, Feng Guo has authored 134 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Safety, Risk, Reliability and Quality, 38 papers in Social Psychology and 34 papers in Transportation. Recurrent topics in Feng Guo's work include Traffic and Road Safety (77 papers), Human-Automation Interaction and Safety (29 papers) and Urban Transport and Accessibility (20 papers). Feng Guo is often cited by papers focused on Traffic and Road Safety (77 papers), Human-Automation Interaction and Safety (29 papers) and Urban Transport and Accessibility (20 papers). Feng Guo collaborates with scholars based in United States, China and Canada. Feng Guo's co-authors include Thomas A. Dingus, Sheila G. Klauer, Jonathan M. Hankey, Youjia Fang, Miguel A. Pérez, Bruce G. Simons‐Morton, Jonathan F. Antin, Suzanne E. Lee, Lisa Aultman-Hall and Marie Claude Ouimet and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Advanced Materials.

In The Last Decade

Feng Guo

119 papers receiving 4.5k citations

Hit Papers

Driver crash risk factors and prevalence evaluation using... 2014 2026 2018 2022 2016 2014 2025 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Driver crash risk factors and prevalence evaluation using naturalistic driving data
    2016 729 citations Thomas A. Dingus, Feng Guo et al. profile →
  2. Distracted Driving and Risk of Road Crashes among Novice and Experienced Drivers
    2014 610 citations Sheila G. Klauer, Feng Guo et al. profile →
  3. In‐Sensor Computing with Visual‐Tactile Perception Enabled by Mechano‐Optical Artificial Synapse
    2025 22 citations Feng Guo et al. profile →

Peers

Feng Guo
Tom Brijs Belgium
George Yannis Greece
Michael Regan Australia
Michael G. Lenné Australia
David Shinar Israel
Thomas A. Dingus United States
Anne T. McCartt United States
Jonathan M. Hankey United States
Sheila G. Klauer United States
Andry Rakotonirainy Australia
Tom Brijs Belgium
Feng Guo
Citations per year, relative to Feng Guo Feng Guo (= 1×) peers Tom Brijs

Countries citing papers authored by Feng Guo

Since Specialization
Citations

This map shows the geographic impact of Feng Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Feng Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feng Guo more than expected).

Fields of papers citing papers by Feng Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Feng Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Feng Guo. The network helps show where Feng Guo may publish in the future.

Co-authorship network of co-authors of Feng Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Guo. A scholar is included among the top collaborators of Feng Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Feng Guo. Feng Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Han, Shu, et al.. (2025). Crash risk associated with eyes-off-road duration by road control type and intersection type. Journal of Safety Research. 93. 266–273. 1 indexed citations
2.
Zhou, Dawei, et al.. (2025). Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding. VTechWorks (Virginia Tech). 5972–5983.
3.
Guo, Feng, et al.. (2025). Evaluating risk factors associated with fatalities among powered two-wheeler crashes in the United States. Traffic Injury Prevention. 27(2). 172–179.
4.
Ding, Dawei, Feng Guo, Hongyan Ma, et al.. (2024). Novel insights on the setting process, hardened properties, and durability of sustainable ultra-high-performance seawater sea sand concrete. Construction and Building Materials. 447. 138092–138092. 11 indexed citations
5.
Yang, Xinyi, et al.. (2024). Colonoscopy Training on Virtual-Reality Simulators or Physical Model Simulators: A Randomized Controlled Trial. Journal of surgical education. 81(10). 1339–1345.
6.
Guo, Feng, et al.. (2024). Two-stream video-based deep learning model for crashes and near-crashes. Transportation Research Part C Emerging Technologies. 166. 104794–104794. 1 indexed citations
7.
Chen, Qian, et al.. (2024). Detecting Critical Mismatched Driver Visual Attention During Lane Change: An Embedding Kernel Algorithm. IEEE Transactions on Intelligent Transportation Systems. 25(7). 7070–7080. 2 indexed citations
8.
Guo, Feng, Qu Wei, Miao Wang, Zhaoxia Guo, & Stein W. Wallace. (2023). Deep attention models with dimension-reduction and gate mechanisms for solving practical time-dependent vehicle routing problems. Transportation Research Part E Logistics and Transportation Review. 173. 103095–103095. 11 indexed citations
9.
Guo, Feng, et al.. (2023). What factors contribute to e-scooter crashes: A first look using a naturalistic riding approach. Journal of Safety Research. 85. 182–191. 29 indexed citations
10.
Guo, Feng & Danni Lu. (2022). How many crashes does cellphone use contribute to? Population attributable risk of cellphone use while driving. Journal of Safety Research. 82. 385–391. 8 indexed citations
11.
Guo, Feng, et al.. (2022). Real-time driving risk assessment using deep learning with XGBoost. Accident Analysis & Prevention. 178. 106836–106836. 38 indexed citations
12.
Zhang, Lanfang, et al.. (2019). Effect of Using Mobile Phones on Driver’s Control Behavior Based on Naturalistic Driving Data. International Journal of Environmental Research and Public Health. 16(8). 1464–1464. 31 indexed citations
13.
Guo, Feng, et al.. (2019). Evaluate driver response to active warning system in level-2 automated vehicles. Accident Analysis & Prevention. 128. 132–138. 17 indexed citations
14.
Liu, Yi, Feng Guo, & Richard J. Hanowski. (2019). Assessing the impact of sleep time on truck driver performance using a recurrent event model. Statistics in Medicine. 38(21). 4096–4111. 9 indexed citations
15.
Guo, Feng, et al.. (2018). The driver-level crash risk associated with daily cellphone use and cellphone use while driving. Accident Analysis & Prevention. 119. 149–154. 61 indexed citations
16.
Guo, Feng, Inyoung Kim, & Sheila G. Klauer. (2017). Semiparametric Bayesian models for evaluating time‐variant driving risk factors using naturalistic driving data and case‐crossover approach. Statistics in Medicine. 38(2). 160–174. 15 indexed citations
17.
18.
Hickman, Jeffrey S., et al.. (2014). Evaluating the Potential Safety Benefits of Electronic Hours-of-Service Recorders Final Report. ROSA P. 1 indexed citations
19.
Guo, Feng, Xuesong Wang, & Mohamed Abdel‐Aty. (2009). Corridor-Level Signalized Intersection Safety Analysis Using Bayesian Spatial Models. Transportation Research Board 88th Annual MeetingTransportation Research Board. 5 indexed citations
20.
Aultman-Hall, Lisa, Antonio Comi, Feng Guo, & Francesco Russo. (2003). Towards continental freight transportation planning models.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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