Name
Abstract | ||
|---|---|---|
To support traffic authorities in the assessment of traffic signal strategies via simulation, we propose an approach that leverages on the strengths of automated planning knowledge models to generate accurate traffic simulators. By exploiting the sensors' readings of adaptive traffic control systems in operation in a region of interest, and the conciseness of planning knowledge models, the proposed approach can effectively simulate the impact that traffic signal strategies will have on the considered urban region. Our experimental analysis, performed using real-world historical data, shows that the accuracy of our simulated traffic conditions is within 10% of what was actually recorded by deployed sensors. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ITSC55140.2022.9922231 | 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) |
Keywords | DocType | ISBN |
simulated traffic conditions,traffic signal strategies,traffic authorities,automated planning knowledge models,accurate traffic simulators,adaptive traffic control systems,region of interest | Conference | 978-1-6654-6881-7 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saumya Bhatnagar | 1 | 0 | 0.34 |
| Rongge Guo | 2 | 0 | 0.34 |
| Keith McCabe | 3 | 0 | 0.34 |
| Thomas L. McCluskey | 4 | 0 | 0.34 |
| Enrico Scala | 5 | 0 | 0.34 |
| Mauro Vallati | 6 | 216 | 46.63 |