Sensing the disturbed rhythm of city mobility with chaotic measures: anomaly awareness from traffic flows
| Autor: | Daqing Zheng, Su Yang, Jun Gao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
050210 logistics & transportation
General Computer Science Computer science Anomaly (natural sciences) 05 social sciences Disequilibrium Real-time computing Chaotic 02 engineering and technology Flow network Rhythm 0502 economics and business 0202 electrical engineering electronic engineering information engineering medicine Entropy (information theory) 020201 artificial intelligence & image processing medicine.symptom Boltzmann's entropy formula Intelligent transportation system |
| Zdroj: | Journal of Ambient Intelligence and Humanized Computing. 12:4347-4362 |
| ISSN: | 1868-5145 1868-5137 |
| DOI: | 10.1007/s12652-019-01338-7 |
| Popis: | Big data-driven intelligent transportation plays an important role in smart cities. Moreover, upcoming abnormal events threatening to public safety can be altered prior to their appearance since such events break the regular rhythm of city mobility patterns. The purpose of this study is to detect and forecast abnormal events from the pulse of traffic flows. Specifically, information entropy, Boltzmann entropy, and fractal dimension are used to calculate the degree of the disequilibrium regarding how vehicles distribute on the transportation network. Then, the experiments were conducted based on simulated data and GPS traces of taxies in Shanghai, China. The results show that the proposed method can accurately indicate abnormal events to appear in reality. Finally, a comparison of the advantages and disadvantages of the three chaotic measures leads to insight into the rhythm of city mobility. |
| Databáze: | OpenAIRE |
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