Tom V. Mathew

3.1k total citations
68 papers, 1.7k citations indexed

About

Tom V. Mathew is a scholar working on Transportation, Control and Systems Engineering and Building and Construction. According to data from OpenAlex, Tom V. Mathew has authored 68 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Transportation, 47 papers in Control and Systems Engineering and 32 papers in Building and Construction. Recurrent topics in Tom V. Mathew's work include Transportation Planning and Optimization (48 papers), Traffic control and management (44 papers) and Traffic Prediction and Management Techniques (28 papers). Tom V. Mathew is often cited by papers focused on Transportation Planning and Optimization (48 papers), Traffic control and management (44 papers) and Traffic Prediction and Management Techniques (28 papers). Tom V. Mathew collaborates with scholars based in India, United States and Ireland. Tom V. Mathew's co-authors include Sushant Sharma, Satish V. Ukkusuri, Gaurav Sharma, S. Travis Waller, Jitendra Agrawal, Jeremy Blum, S. L. Dhingra, Nagendra R. Velaga, Gaurang Joshi and Shriniwas Arkatkar and has published in prestigious journals such as Accident Analysis & Prevention, Transportation Research Part A Policy and Practice and Transportation Research Part D Transport and Environment.

In The Last Decade

Tom V. Mathew

67 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom V. Mathew India 21 964 847 705 479 334 68 1.7k
Ning Jia China 24 878 0.9× 540 0.6× 447 0.6× 432 0.9× 148 0.4× 102 1.9k
Alexander Paz Australia 24 792 0.8× 275 0.3× 802 1.1× 393 0.8× 218 0.7× 132 1.8k
Shi An China 22 932 1.0× 611 0.7× 747 1.1× 440 0.9× 106 0.3× 112 1.8k
Francesco Viti Luxembourg 24 1.6k 1.6× 1.0k 1.2× 674 1.0× 911 1.9× 123 0.4× 181 2.1k
Tomio Miwa Japan 20 869 0.9× 280 0.3× 475 0.7× 393 0.8× 120 0.4× 122 1.3k
Shlomo Bekhor Israel 34 2.8k 2.9× 477 0.6× 893 1.3× 550 1.1× 381 1.1× 130 3.5k
José M. Viegas Portugal 20 1.4k 1.5× 353 0.4× 811 1.2× 557 1.2× 104 0.3× 72 2.0k
Marcello Montanino Italy 20 752 0.8× 1.1k 1.3× 826 1.2× 623 1.3× 369 1.1× 33 1.7k
Mark Hickman Australia 27 2.0k 2.1× 530 0.6× 889 1.3× 624 1.3× 128 0.4× 147 2.6k
Panos D. Prevedouros United States 20 658 0.7× 436 0.5× 332 0.5× 474 1.0× 385 1.2× 91 1.3k

Countries citing papers authored by Tom V. Mathew

Since Specialization
Citations

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

Fields of papers citing papers by Tom V. Mathew

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom V. Mathew. 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 Tom V. Mathew. The network helps show where Tom V. Mathew may publish in the future.

Co-authorship network of co-authors of Tom V. Mathew

This figure shows the co-authorship network connecting the top 25 collaborators of Tom V. Mathew. A scholar is included among the top collaborators of Tom V. Mathew 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 Tom V. Mathew. Tom V. Mathew 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.
Mathew, Tom V., et al.. (2024). A systematic review of studies investigating the impact of sleep deprivation on drivers’ physiology and driving performance. Transportation Research Part F Traffic Psychology and Behaviour. 109. 458–479. 1 indexed citations
2.
Mathew, Tom V., et al.. (2023). Identifying risky driving behavior: a field study using instrumented vehicles. Transportation Letters. 16(7). 688–702. 8 indexed citations
3.
Mathew, Tom V., et al.. (2019). Estimation of traffic conflicts using precise lateral position and width of vehicles for safety assessment. Accident Analysis & Prevention. 132. 105264–105264. 67 indexed citations
4.
Mathew, Tom V., et al.. (2017). Estimation of Modified Time to Collision as Surrogate for Mid-block Crashes under Mixed Traffic Conditions. Transportation Research Board 96th Annual MeetingTransportation Research Board. 3 indexed citations
5.
Gurumurthy, Krishna Murthy, et al.. (2016). Vehicle-type Dependent Car following Model Using Spring-mass-damper Dynamics for Heterogeneous Traffic. Transportation Research Board 95th Annual MeetingTransportation Research Board. 1 indexed citations
6.
Mullakkal-Babu, Freddy Antony, Peter Vortisch, & Tom V. Mathew. (2015). Modelling of motorcycle movements in mixed traffic conditions. Repository KITopen (Karlsruhe Institute of Technology). 9 indexed citations
7.
Mathew, Tom V., et al.. (2014). Adaptive Signal Coordination for Heterogeneous Traffic Using Downstream Detection. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 2 indexed citations
8.
Mathew, Tom V., et al.. (2014). Analysis and Modelling of Tactical Decisions of Vehicular Lateral Movement in Mixed Traffic Environment. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 6 indexed citations
9.
Mathew, Tom V., et al.. (2014). A Space Discretization Based Simulation Approach for Non-lane Based Traffic Conditions. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 5 indexed citations
10.
Vortisch, Peter, et al.. (2013). Methodology for the Calibration of VISSIM in Mixed Traffic. Transportation Research Board 92nd Annual MeetingTransportation Research Board. 43 indexed citations
11.
Mathew, Tom V., et al.. (2012). Strip-Based Simulation Model for Mixed Traffic Conditions. Transportation Research Board 91st Annual MeetingTransportation Research Board. 1 indexed citations
12.
Mathew, Tom V., et al.. (2011). Vehicle-Actuated Signal Controller for Heterogeneous Traffic Having Limited Lane Discipline. ITE journal. 81(5). 6 indexed citations
13.
Mathew, Tom V., et al.. (2010). Adaptive Traffic Control System for Developing Countries. 1 indexed citations
14.
Mathew, Tom V., et al.. (2007). A Single-Stage Mixed Integer Programming Model for Transit Fleet Resource Allocation. Transportation Research Board 86th Annual MeetingTransportation Research Board. 3 indexed citations
15.
Sharma, Sushant & Tom V. Mathew. (2007). Transportation Network Design with Emission Pricing as a Bilevel Optimization Problem. Transportation Research Board 86th Annual MeetingTransportation Research Board. 2 indexed citations
16.
Khasnabis, Snehamay & Tom V. Mathew. (2006). A Single-Stage Genetic Algorithm Model For Transit Fleet Resource Allocation. 2 indexed citations
17.
Mathew, Tom V. & Sushant Sharma. (2006). Continuous Network Design with Emission Pricing as a Bi-Level Optimization Problem. 804–809. 13 indexed citations
18.
Taylor, M.A., et al.. (2005). From chaotic road traffic to cooperative opportunistic percolation using cellular automata. Transport Research Forum. 28. 1 indexed citations
19.
Mathew, Tom V., et al.. (2005). Methodology for finding optimum cell size for a grid based cellular automata traffic flow model. OpenstarTs (Univeristy of Trieste https://www.units.it/). 71–79. 1 indexed citations
20.
Mathew, Tom V., et al.. (2004). Heterogeneous Traffic Flow Modelling Using Cellular Automata. 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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