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DOI: 10.4230/LIPIcs.COSIT.2022.22

Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks (Short Paper)

Authors: Yadi Wang, Yicheng Pan, Meng Ma, and Ping Wang

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract

Various participants in urban traffic systems intertwine a highly complicated coupling network. An interpretable analysis of underlying correlations is one of the keys to understanding traffic anomalies. Unfortunately, abnormal situation analysis in real scenarios faces severe limitations in negative sample deficiency, data integrity, and verifiability. In view of this, we developed a simulation tool - the Traffic Anomaly Situation Simulator (TASS). Through configurable scripts, TASS simulates real traffic networks by road editing, data collection, and fault injection. Given the generated cases, we designed a dynamic causal discovery algorithm, Dycause-Traffic, to demonstrate the features of causality in traffic anomalies.

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Yadi Wang, Yicheng Pan, Meng Ma, and Ping Wang. Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 22:1-22:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{wang_et_al:LIPIcs.COSIT.2022.22,
  author =	{Wang, Yadi and Pan, Yicheng and Ma, Meng and Wang, Ping},
  title =	{{Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{22:1--22:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.22},
  URN =		{urn:nbn:de:0030-drops-169077},
  doi =		{10.4230/LIPIcs.COSIT.2022.22},
  annote =	{Keywords: SUMO simulation, dynamic causality discovery, congestion propagation}
}

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Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks (Short Paper)

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