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From: Overview of traffic incident duration analysis and prediction
Challenges | Potential methods | Previous research |
---|---|---|
Combining multiple data resources | Intelligent vehicle system (for example, eCall) | |
Traffic condition detection information | ||
Crowdsourcing technology | ||
Time sequential prediction model | Based on response term’s report | |
Based information from social media | Gu et al. [61] | |
Outlier prediction | Different models for different duration ranges | |
A time sequential prediction model | ||
Improvement of prediction methods | Machine Learning | Zhan et al. [15]; Lin et al. [54]; Park et al. [57]; Ma et al. [82] et al. |
Updated HBDM | Li et al. [46] et al. | |
Combining recovery times | Combine new data resource | Hojati et al. [23] |
Influence of unobserved factors | Randomness model |