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Statistics of Freeway Traffic

Statistics of Freeway Traffic. Overview. The Freeway Performance Measurement System (PeMS) Computer Lab Visualization of Traffic Dynamics Visualization and Data Quality Travel Time Prediction Computer Lab. Freeway Performance Measurement System (PeMS). Data Source: Loop Detectors.

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Statistics of Freeway Traffic

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  1. Statistics of Freeway Traffic

  2. Overview • The Freeway Performance Measurement System (PeMS) • Computer Lab • Visualization of Traffic Dynamics • Visualization and Data Quality • Travel Time Prediction • Computer Lab

  3. Freeway Performance Measurement System (PeMS)

  4. Data Source: Loop Detectors Measure: Flow, Occupancy, (Velocity) The PeMS system receives flow and occupancy from approximately 22,000 loops across the state every 30 seconds: 2 GB per day. Currently store 4 TB of data

  5. Uses • Managers at any time can have a uniform, and comprehensive assessment of freeway performance. • Traffic engineers can base their operational decisions on knowledge of the current state of the freeway network. • Planners can determine whether congestion bottlenecks can be alleviated by improving operations or by minor capital improvements. • Travelers can obtain the current shortest route and travel time estimates. • Researchers can validate their theories and calibrate simulation models.

  6. Real-Time Maps

  7. Flow Profiles in Space

  8. Flow in Space and Time

  9. Speed

  10. Speed in Space and Time

  11. District Summary: VMT

  12. Delay Analysis

  13. Detector Health

  14. Visualizing Traffic Dynamics: Speed

  15. Bottleneck Identification

  16. Identifying Bad Detectors:Occupancies in Four Adjacent Lanes

  17. Travel Time Prediction

  18. Velocity Field Portrayed by Loops

  19. Daily Travel Time Curves

  20. Problem summary and notation Data available up until time t Forecast travel time T for trip departing at time t+D T*: the time the trip would take if current conditions persisted into the future

  21. T versus T* 9 am D=0 3 pm D=60 There is a linear relationship between T and T*, but the slope and intercept depend on time of day and on D

  22. Comparison of predictors: D=0 historical mean current status – T* regression

  23. Comparison: D = 60 current status – T* historical mean regression

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