Richard Mounce

1.1k total citations
29 papers, 839 citations indexed

About

Richard Mounce is a scholar working on Transportation, Control and Systems Engineering and Automotive Engineering. According to data from OpenAlex, Richard Mounce has authored 29 papers receiving a total of 839 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Transportation, 16 papers in Control and Systems Engineering and 8 papers in Automotive Engineering. Recurrent topics in Richard Mounce's work include Transportation Planning and Optimization (17 papers), Traffic control and management (15 papers) and Transportation and Mobility Innovations (8 papers). Richard Mounce is often cited by papers focused on Transportation Planning and Optimization (17 papers), Traffic control and management (15 papers) and Transportation and Mobility Innovations (8 papers). Richard Mounce collaborates with scholars based in United Kingdom, Luxembourg and China. Richard Mounce's co-authors include John D. Nelson, Mike Smith, S. R. Mounce, Joby Boxall, Malachy Carey, Mike Smith, Ronghui Liu, Mark Beecroft, Tom Jackson and J. Austin and has published in prestigious journals such as Transportation Research Part C Emerging Technologies, Transportation Research Part B Methodological and Transportation Research Part A Policy and Practice.

In The Last Decade

Richard Mounce

28 papers receiving 813 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard Mounce United Kingdom 15 473 302 277 223 135 29 839
Maaike Snelder Netherlands 15 530 1.1× 303 1.0× 468 1.7× 184 0.8× 199 1.5× 70 979
Zhenliang Ma Sweden 21 834 1.8× 174 0.6× 302 1.1× 19 0.1× 542 4.0× 95 1.2k
Zhenzhou Yuan China 20 620 1.3× 454 1.5× 275 1.0× 77 0.3× 529 3.9× 77 1.2k
Mariano Gallo Italy 18 774 1.6× 295 1.0× 391 1.4× 45 0.2× 405 3.0× 79 1.2k
M G Karlaftis Greece 9 505 1.1× 306 1.0× 113 0.4× 126 0.6× 611 4.5× 22 938
Shukai Chen China 17 326 0.7× 246 0.8× 364 1.3× 12 0.1× 212 1.6× 39 762
Ghassan Abu–Lebdeh United States 14 368 0.8× 404 1.3× 84 0.3× 115 0.5× 374 2.8× 55 765
Mahmoud Masoud Australia 17 125 0.3× 137 0.5× 153 0.6× 28 0.1× 114 0.8× 77 758
Prakash Ranjitkar New Zealand 21 559 1.2× 515 1.7× 369 1.3× 122 0.5× 411 3.0× 81 1.2k
Xiaojian Hu China 17 400 0.8× 351 1.2× 167 0.6× 24 0.1× 230 1.7× 66 716

Countries citing papers authored by Richard Mounce

Since Specialization
Citations

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

Fields of papers citing papers by Richard Mounce

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Mounce

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Mounce. A scholar is included among the top collaborators of Richard Mounce 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 Richard Mounce. Richard Mounce 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.
Mounce, S. R., Richard Mounce, & Joby Boxall. (2025). AI-Augmented Water Quality Event Response: The Role of Generative Models for Decision Support. Water. 17(22). 3260–3260.
2.
Smith, Mike & Richard Mounce. (2024). Backpressure or no backpressure? Two simple examples. Transportation Research Part C Emerging Technologies. 161. 104515–104515. 1 indexed citations
3.
Smith, Mike, et al.. (2023). With spatial queueing, the P0 responsive traffic signal control policy may fail to maximise network capacity even if queue storage capacities are very large. Transportation Research Part B Methodological. 177. 102814–102814. 3 indexed citations
4.
Smith, Mike, Francesco Viti, Wei Huang, & Richard Mounce. (2023). Upstream-gating merge-control for maximising network capacity: With an application to urban traffic management. Transportation Research Part C Emerging Technologies. 155. 104287–104287. 2 indexed citations
5.
Smith, Mike, et al.. (2022). Zero-queue traffic control, using green-times and prices together. Transportation Research Part C Emerging Technologies. 138. 103630–103630. 7 indexed citations
6.
Mounce, Richard, Mark Beecroft, & John D. Nelson. (2020). On the role of frameworks and smart mobility in addressing the rural mobility problem. Research in Transportation Economics. 83. 100956–100956. 39 indexed citations
7.
Smith, Mike, Takamasa Iryo, Richard Mounce, Marco Rinaldi, & Francesco Viti. (2019). Traffic control which maximises network throughput: Some simple examples. Transportation Research Part C Emerging Technologies. 107. 211–228. 16 indexed citations
8.
Mounce, Richard & John D. Nelson. (2018). On the potential for one-way electric vehicle car-sharing in future mobility systems. Transportation Research Part A Policy and Practice. 120. 17–30. 155 indexed citations
9.
Smith, Mike, Ronghui Liu, & Richard Mounce. (2015). Traffic Control and Route Choice; Capacity Maximization and Stability. Transportation research procedia. 7. 556–577. 22 indexed citations
10.
Mounce, S. R., Richard Mounce, & Joby Boxall. (2015). Case-based reasoning to support decision making for managing drinking water quality events in distribution systems. Urban Water Journal. 13(7). 727–738. 8 indexed citations
11.
Mounce, S. R., Richard Mounce, & Joby Boxall. (2014). Case-Based Reasoning Approach For Managing Water Quality Incidents In Distribution Systems. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 1 indexed citations
12.
Mounce, S. R., Richard Mounce, Tom Jackson, J. Austin, & Joby Boxall. (2013). Pattern matching and associative artificial neural networks for water distribution system time series data analysis. Journal of Hydroinformatics. 16(3). 617–632. 46 indexed citations
13.
Smith, Mike & Richard Mounce. (2011). A splitting rate model of traffic re-routeing and traffic control. Procedia - Social and Behavioral Sciences. 17. 316–340. 55 indexed citations
14.
Mounce, S. R., Richard Mounce, & Joby Boxall. (2011). Identifying Sampling Interval for Event Detection in Water Distribution Networks. Journal of Water Resources Planning and Management. 138(2). 187–191. 24 indexed citations
15.
Mounce, S. R., et al.. (2010). Field testing of optimal sensor placement and data analysis methodologies for burst detection and location in an urban water network. 1258–1265. 6 indexed citations
16.
Mounce, Richard & Malachy Carey. (2010). Route swapping in dynamic traffic networks. Transportation Research Part B Methodological. 45(1). 102–111. 56 indexed citations
17.
Mounce, S. R., Richard Mounce, & Joby Boxall. (2010). Novelty detection for time series data analysis in water distribution systems using support vector machines. Journal of Hydroinformatics. 13(4). 672–686. 150 indexed citations
18.
Mounce, Richard & Mike Smith. (2007). Uniqueness of Equilibrium in Steady State and Dynamic Traffic Networks. 19 indexed citations
19.
Mounce, Richard. (2002). Non-convergence in dynamic assignment networks?. 17. 569–572. 2 indexed citations
20.
Mounce, Richard. (2001). NON-MONOTONICITY IN DYNAMIC TRAFFIC ASSIGNMENT NETWORKS. 8 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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