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Travel time unreliability on freeways: Why measures based on variance tell only half the story
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Accurate freeway travel time prediction with state-space neural networks under missing data
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Monitoring and Predicting Freeway Travel Time Reliability: Using Width and Skew of Day-to-Day Travel Time Distribution
TLDR
Two reliability metrics are proposed, based on three characteristic percentiles: the 10th, 50th, and 90th percentile for a given route and TOD-DOW period, which can be used to construct so-called reliability maps, which help identify DOW-TOD periods in which congestion will likely set in (or dissolve).
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Urban link travel time estimation based on sparse probe vehicle data
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Construct support vector machine ensemble to detect traffic incident
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Link-level vulnerability indicators for real-world networks
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Localized Extended Kalman Filter for Scalable Real-Time Traffic State Estimation
TLDR
The novel localized EKF (L-EKF) is proposed, a highly scalable solution to the state estimation problem that scales much better with the network size and leads to estimates with nearly the same accuracy as the G-EkF.
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A framework for robustness analysis of road networks for short term variations in supply
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Calibration of a microscopic simulation model for emission calculation
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Modeling travel time reliability of freeways using risk assessment techniques
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