Abstract
Congestion discrimination is the basis to effectively develop traffic control strategies. This paper takes data from sensors as the research object, based on ordered decision theory to sort the urban network traffic congestion indicators and predict traffic congestion situation based on decision tree algorithm, consequently, indicator set which can describe the performance of network links and intersections is obtained. The proposed method reveals that there is an ordered relation between indicators and traffic congestion. By eliminating redundant indicators, this algorithm can get the closely related indicator subset to determine whether traffic congestion happen or not, accordingly the effectiveness of traffic congestion discrimination is improved.
| Original language | English |
|---|---|
| Pages (from-to) | 814-820 |
| Number of pages | 7 |
| Journal | Advances in Information Sciences and Service Sciences |
| Volume | 4 |
| Issue number | 23 |
| DOIs | |
| State | Published - Dec 2012 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities
Keywords
- Indicator selection
- Ordered decision
- Partial ordered mutual information
- Traffic congestion
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