Daniel J. Dailey

564 total citations
44 papers, 446 citations indexed

About

Daniel J. Dailey is a scholar working on Building and Construction, Control and Systems Engineering and Transportation. According to data from OpenAlex, Daniel J. Dailey has authored 44 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Building and Construction, 20 papers in Control and Systems Engineering and 17 papers in Transportation. Recurrent topics in Daniel J. Dailey's work include Traffic Prediction and Management Techniques (21 papers), Traffic control and management (19 papers) and Transportation Planning and Optimization (17 papers). Daniel J. Dailey is often cited by papers focused on Traffic Prediction and Management Techniques (21 papers), Traffic control and management (19 papers) and Transportation Planning and Optimization (17 papers). Daniel J. Dailey collaborates with scholars based in United States and Denmark. Daniel J. Dailey's co-authors include Xiao‐Yun Lu, Steven E Shladover, Jiaqi Ma, Todd N. Schoepflin, Hesham Rakha, Xiaopeng Li, Ramanujan Jagannathan, F.W. Cathey, Joe Bared and Edward McCormack and has published in prestigious journals such as Accident Analysis & Prevention, Transportation Research Record Journal of the Transportation Research Board and Journal of Transportation Engineering.

In The Last Decade

Daniel J. Dailey

41 papers receiving 399 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Dailey United States 12 232 219 219 148 86 44 446
Lianyu Chu United States 12 342 1.5× 374 1.7× 402 1.8× 113 0.8× 57 0.7× 44 615
Jordi Casas Spain 10 292 1.3× 224 1.0× 312 1.4× 137 0.9× 64 0.7× 44 486
Yiguang Xuan United States 10 247 1.1× 134 0.6× 293 1.3× 175 1.2× 60 0.7× 18 397
Romain Billot France 9 245 1.1× 165 0.8× 228 1.0× 140 0.9× 59 0.7× 21 425
Fangce Guo United Kingdom 14 214 0.9× 343 1.6× 264 1.2× 119 0.8× 56 0.7× 31 520
Rob Hranac United States 5 198 0.9× 168 0.8× 191 0.9× 138 0.9× 96 1.1× 10 389
Hyoshin Park United States 9 127 0.5× 245 1.1× 207 0.9× 138 0.9× 146 1.7× 32 466
Ciprian Alecsandru Canada 8 283 1.2× 249 1.1× 239 1.1× 117 0.8× 56 0.7× 35 424
Jeffrey Taylor United States 8 233 1.0× 179 0.8× 268 1.2× 193 1.3× 60 0.7× 15 443
Shaun Quayle United States 6 344 1.5× 288 1.3× 253 1.2× 129 0.9× 111 1.3× 11 478

Countries citing papers authored by Daniel J. Dailey

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Dailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Dailey. 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 Daniel J. Dailey. The network helps show where Daniel J. Dailey may publish in the future.

Co-authorship network of co-authors of Daniel J. Dailey

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Dailey. A scholar is included among the top collaborators of Daniel J. Dailey 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 Daniel J. Dailey. Daniel J. Dailey 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.
Ma, Jiaqi, et al.. (2016). Integrated Adaptive Cruise Control Car-Following Model Based on Trajectory Data. Transportation Research Board 95th Annual MeetingTransportation Research Board. 13 indexed citations
2.
Kluger, Robert, Brian L. Smith, Hyungjun Park, & Daniel J. Dailey. (2016). Identification of safety-critical events using kinematic vehicle data and the discrete fourier transform. Accident Analysis & Prevention. 96. 162–168. 37 indexed citations
3.
Lu, Xiao‐Yun, Joyoung Lee, Danjue Chen, et al.. (2014). Freeway Micro-simulation Calibration: Case Study Using Aimsun and VISSIM with Detailed Field Data. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 25 indexed citations
4.
Al-Deek, Haitham, et al.. (2014). Living Laboratory for Freeway Operations: Case Study for Collecting Driver Behavior Data Through Freeway Work Zones. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 1 indexed citations
5.
Kronprasert, Nopadon, et al.. (2014). Determination of Mini-Roundabout Capacity in the United States. Journal of Transportation Engineering. 140(10). 9 indexed citations
6.
Kronprasert, Nopadon, et al.. (2013). Traffic Capacity Models for Mini-Roundabouts in the United States: Calibration of Driver Performance in Simulation. Transportation Research Board 92nd Annual MeetingTransportation Research Board. 3 indexed citations
7.
Lee, Joyoung, Daniel J. Dailey, Joe Bared, & Byungkyu Park. (2013). Simulation-Based Evaluations of Real-Time Variable Speed Limit for Freeway Recurring Traffic Congestion. Transportation Research Board 92nd Annual MeetingTransportation Research Board. 8 indexed citations
8.
McCormack, Edward, Wenjuan Zhao, & Daniel J. Dailey. (2012). GPS tracking of freight vehicles to identify and classify bottlenecks. 1245–1249. 3 indexed citations
9.
Dailey, Daniel J., et al.. (2006). Microscopic Traffic Simulator for Simulation-in-the-Loop Freeway Ramp Control. Transportation Research Board 85th Annual MeetingTransportation Research Board. 2 indexed citations
10.
Dailey, Daniel J., et al.. (2006). The Automated Use of Un-Calibrated CCTV Cameras As Quantitative Speed Sensors--Phase 3. 1 indexed citations
11.
Broggi, Alberto, et al.. (2004). IEEE INTELLIGENT TRANSPORTATION SYSTEMS COUNCIL.
12.
Cathey, F.W. & Daniel J. Dailey. (2003). CORRIDOR TRAVEL TIME USING TRANSIT VEHICLES AS PROBES. 1 indexed citations
13.
Schoepflin, Todd N., Yongmin Kim, & Daniel J. Dailey. (2003). Algorithms for estimating mean vehicle speed using uncalibrated traffic management cameras. 9 indexed citations
14.
Dailey, Daniel J., et al.. (2003). The Mobile Data Communications for Bus and Rail Automatic Vehicle Location Demonstration Project. 1 indexed citations
15.
Dailey, Daniel J. & F.W. Cathey. (2003). AVL-EQUIPPED VEHICLES AS SPEED PROBES : (PHASE 2). 1 indexed citations
16.
Dailey, Daniel J. & F.W. Cathey. (2003). AVL-Equipped Vehicles as Speed Probes. 2 indexed citations
17.
Dailey, Daniel J., et al.. (2003). Estimating Corridor Travel Time by Using Transit Vehicles as Probes. Transportation Research Record Journal of the Transportation Research Board. 1855(1). 60–65. 20 indexed citations
18.
Dailey, Daniel J., et al.. (2001). The Use of Uncalibrated Roadside CCTV Cameras to Estimate Mean Traffic Speed. 3 indexed citations
19.
Dailey, Daniel J. & Li Li. (2000). Algorithm for Estimating Mean Traffic Speed with Uncalibrated Cameras. Transportation Research Record Journal of the Transportation Research Board. 1719(1). 27–32. 5 indexed citations
20.
Dailey, Daniel J. & R.W. Albrecht. (1985). In-core/ex-core neutron noise measurements to examine core internal vibrations in an operating PWR. Progress in Nuclear Energy. 15. 251–260. 3 indexed citations

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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