Chaozhong Wu

1.3k total citations
39 papers, 1.0k citations indexed

About

Chaozhong Wu is a scholar working on Safety, Risk, Reliability and Quality, Automotive Engineering and Control and Systems Engineering. According to data from OpenAlex, Chaozhong Wu has authored 39 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Safety, Risk, Reliability and Quality, 11 papers in Automotive Engineering and 9 papers in Control and Systems Engineering. Recurrent topics in Chaozhong Wu's work include Traffic and Road Safety (15 papers), Autonomous Vehicle Technology and Safety (8 papers) and Traffic control and management (7 papers). Chaozhong Wu is often cited by papers focused on Traffic and Road Safety (15 papers), Autonomous Vehicle Technology and Safety (8 papers) and Traffic control and management (7 papers). Chaozhong Wu collaborates with scholars based in China, Netherlands and United States. Chaozhong Wu's co-authors include Zhijun Chen, Nengchao Lyu, Yishi Zhang, Jie Xue, Pieter van Gelder, Lian Xie, Xinping Yan, Mingyang Zhang, Zhen Huang and Ming Ma and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Chaozhong Wu

38 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chaozhong Wu China 14 403 237 227 193 176 39 1.0k
Jian Lu China 18 316 0.8× 172 0.7× 253 1.1× 93 0.5× 99 0.6× 56 893
Salvatore Cafiso Italy 26 1.0k 2.5× 341 1.4× 345 1.5× 101 0.5× 203 1.2× 112 1.9k
Mohamed H. Zaki Canada 22 948 2.4× 455 1.9× 368 1.6× 200 1.0× 118 0.7× 137 1.7k
Arash Jahangiri United States 13 255 0.6× 289 1.2× 166 0.7× 62 0.3× 57 0.3× 39 688
Aliaksei Laureshyn Sweden 18 975 2.4× 451 1.9× 414 1.8× 88 0.5× 190 1.1× 52 1.3k
Sikai Chen United States 20 431 1.1× 299 1.3× 471 2.1× 41 0.2× 110 0.6× 81 1.4k
Mohammad Jalayer United States 20 713 1.8× 316 1.3× 186 0.8× 69 0.4× 173 1.0× 71 1.1k
Ou Zheng United States 17 485 1.2× 129 0.5× 354 1.6× 41 0.2× 89 0.5× 33 972
Reginald R. Souleyrette United States 18 419 1.0× 358 1.5× 220 1.0× 54 0.3× 65 0.4× 151 1.2k
Hongwei Guo China 14 361 0.9× 419 1.8× 268 1.2× 126 0.7× 104 0.6× 40 915

Countries citing papers authored by Chaozhong Wu

Since Specialization
Citations

This map shows the geographic impact of Chaozhong Wu'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 Chaozhong Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaozhong Wu more than expected).

Fields of papers citing papers by Chaozhong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chaozhong Wu. 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 Chaozhong Wu. The network helps show where Chaozhong Wu may publish in the future.

Co-authorship network of co-authors of Chaozhong Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chaozhong Wu. A scholar is included among the top collaborators of Chaozhong Wu 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 Chaozhong Wu. Chaozhong Wu 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.
He, Yi, et al.. (2024). Dynamics Modeling for Modular Distributed-Drive Vehicles With Unknown Parameters. IEEE Transactions on Intelligent Vehicles. 10(11). 4942–4961.
2.
Zhang, Yishi, et al.. (2021). Energy management strategy of intelligent plug-in split hybrid electric vehicle based on deep reinforcement learning with optimized path planning algorithm. Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering. 235(14). 3287–3298. 12 indexed citations
3.
Chu, Duanfeng, et al.. (2020). Vibrotactile Take-over Requests in Highly Automated Driving. 695–700. 2 indexed citations
4.
Chen, Zhijun, et al.. (2020). Deep learning for autonomous ship-oriented small ship detection. Safety Science. 130. 104812–104812. 152 indexed citations
5.
Xue, Jie, Pieter van Gelder, Genserik Reniers, Eleonora Papadimitriou, & Chaozhong Wu. (2019). Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships’ maneuvering decisions using grey and fuzzy theories. Safety Science. 120. 323–340. 70 indexed citations
6.
Xue, Jie, Pieter van Gelder, Eleonora Papadimitriou, Zhijun Chen, & Chaozhong Wu. (2019). Grey Relational Analysis of Environmental Influencing Factors of Autonomous Ships’ Maneuvering Decision-Making. 1447–1452. 2 indexed citations
7.
Lyu, Nengchao, Yue Cao, Chaozhong Wu, Jin Xu, & Lian Xie. (2018). The effect of gender, occupation and experience on behavior while driving on a freeway deceleration lane based on field operational test data. Accident Analysis & Prevention. 121. 82–93. 75 indexed citations
8.
Lyu, Nengchao, et al.. (2018). A field operational test in China: Exploring the effect of an advanced driver assistance system on driving performance and braking behavior. Transportation Research Part F Traffic Psychology and Behaviour. 65. 730–747. 73 indexed citations
9.
Chen, Zhijun, Chaozhong Wu, Zhen Huang, et al.. (2017). Dangerous driving behavior detection using video-extracted vehicle trajectory histograms. Journal of Intelligent Transportation Systems. 21(5). 409–421. 56 indexed citations
10.
Wu, Chaozhong, et al.. (2017). Driving style recognition method using braking characteristics based on hidden Markov model. PLoS ONE. 12(8). e0182419–e0182419. 41 indexed citations
11.
Atombo, Charles, et al.. (2016). Safety and Health Perceptions in Work-related Transport Activities in Ghanaian Industries. Safety and Health at Work. 8(2). 175–182. 31 indexed citations
12.
Chen, Zhijun, Chaozhong Wu, Ming Zhong, Nengchao Lyu, & Zhen Huang. (2015). Identification of common features of vehicle motion under drowsy/distracted driving: A case study in Wuhan, China. Accident Analysis & Prevention. 81. 251–259. 36 indexed citations
13.
Chu, Duanfeng, et al.. (2015). A design of brain-computer interface control platform for intelligent vehicle. 37. 70–74. 2 indexed citations
14.
Du, Zhigang, et al.. (2014). Safety Evaluation of Highway Tunnel-Entrance Illuminance Transition Based on Eye-Pupil Changes. PROMET - Traffic&Transportation. 26(5). 363–370. 9 indexed citations
15.
Peng, Liqun, Chaozhong Wu, Zhen Huang, & Ming Zhong. (2014). Novel Vehicle Motion Model considering Driver Behavior for Trajectory Prediction and Driving Risk Detection. Transportation Research Record Journal of the Transportation Research Board. 2434(1). 123–134. 7 indexed citations
16.
17.
Wu, Chaozhong, et al.. (2011). Real-Time Automatic Evaluation Technology in Vehicle Road Test System Based on Neural Network. 2. 386–390. 1 indexed citations
18.
Yan, Xinping, Ming Ma, Helai Huang, Mohamed Abdel‐Aty, & Chaozhong Wu. (2011). Motor vehicle–bicycle crashes in Beijing: Irregular maneuvers, crash patterns, and injury severity. Accident Analysis & Prevention. 43(5). 1751–1758. 124 indexed citations
19.
Yan, Xinping, et al.. (2010). Bi‐level programming based contra flow optimization for evacuation events. Kybernetes. 39(8). 1227–1234. 10 indexed citations
20.

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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