1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS)...

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1 Statistics of Freeway Traffic
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Transcript of 1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS)...

Page 1: 1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS) Computer Lab Visualization of Traffic Dynamics Visualization.

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Statistics of Freeway Traffic

Page 2: 1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS) Computer Lab Visualization of Traffic Dynamics Visualization.

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Overview

• The Freeway Performance Measurement System (PeMS)

• Computer Lab

• Visualization of Traffic Dynamics

• Visualization and Data Quality

• Travel Time Prediction

• Computer Lab

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Freeway Performance Measurement System (PeMS)

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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

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•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.

Uses

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Real-Time Maps

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Flow Profiles in Space

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Flow in Space and Time

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Speed

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Speed in Space and Time

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District Summary: VMT

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Page 13: 1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS) Computer Lab Visualization of Traffic Dynamics Visualization.

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Page 14: 1 Statistics of Freeway Traffic. 2 Overview The Freeway Performance Measurement System (PeMS) Computer Lab Visualization of Traffic Dynamics Visualization.

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Delay Analysis

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Detector Health

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Visualizing Traffic Dynamics: Speed

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Bottleneck Identification

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Identifying Bad Detectors:Occupancies in Four Adjacent Lanes

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Travel Time Prediction

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Velocity Field Portrayed by Loops

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Daily Travel Time Curves

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Problem summary and notation

Data available up until time t

Forecast travel time T for trip departing at time t+

T*: the time the trip would take if current conditions persisted into the future

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T versus T*

9 am =0 3 pm =60

There is a linear relationship between T and T*, but the slope and intercept depend on time of day and on

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historical mean

current status – T*

regression

Comparison of predictors: =0

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current status – T*

historical mean

regression

Comparison: = 60