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Using GIS to Analyze ITS Traffic Count Data
Lixin Huang, PhD, GISP GIS Analyst III
Brevard County, Board of County Commissioners 2014 Esri International User Conference
July 17, 2014
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* Data are collected automatically by sensors compared to tradition traffic count collection.
* Data are available everyday. * Data are collected at high frequency, such as 5-minute
interval. * Data includes multiple items such as speed, volume,
and occupancy.
ITS Traffic Count Data
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* Analyze traffic flow patterns (AM and PM peaks). * Identify traffic incidents. * Figure out how other factors (e.g. weather) affect
traffic flow.
Why Analyze ITS Traffic Count Data
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* Categorize data by traffic direction * Group data between interchanges
Traffic Count Data Preprocessing
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Traffic Count Data Locations
East-Bound Traffic and 7 Groups
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Traffic Count Data Characteristics
Data overlap at each location Every data point at each location has different stamp
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* Data Frequency: 5-minute interval * Data Item
* FWY_SPD: Speed * FWY_VOL: Volume * FWY_OCC: Occupancy * SPD_CV: Coefficient of variation for speed * VOL_RATIO: Ratio of max volume lane to min volume
lane
Traffic Count Data Structure
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Traffic Count Data Structure (Cont’d)
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Traffic Count Data Processing
Generate Spatial Weight Matrix
Do Hot Spot Analysis
Summarize Analysis Results
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Traffic Count Data Processing Model
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* Time Interval: 60, 90, 120, 150, 180, 210 minutes * Critical Distance: Determined by tool
Generate Spatial Weight Matrix
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* Analysis is based on each Spatial Weight Matrix generated
Do Hot Spot Analysis
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* Count the number of hour in the following cold or hot spots. * Speed: Cold Spot * Volume: Hot Spot * Speed Variance: Hot Spot * Volume Ratio: Cold Hot
Summarize Analysis Results
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Summarize Analysis Results (Cont’d)
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* High z-score and small p-value: Spatial clustering of high values. * Low negative z-score and small p-value: Spatial clustering of low
values.
Summarize Analysis Results (Cont’d)
Z-score > 1.96 (95% confidence level), clustering of high values
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* Hour count based on 95% confidence level
Summarize Analysis Results (Cont’d)
Speed
Volume Speed Variance Volume Ratio
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Summarize Analysis Results (Cont’d)
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Compare Results Analysis Locations
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Compare Results (Cont’d) Speed, Volume, Speed Variance, Volume Ratio
Frequency Chart at Different time Interval
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Compare Results (Cont’d) Locations
Location 1 Location 2 Location 3
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Compare Results (Cont’d) Speed, Volume, Speed Variance, Volume Ratio Time of Day Chart @ Location 1
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Compare Results (Cont’d) Speed, Volume, Speed Variance, Volume Ratio Time of Day Chart @ Location 2
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Compare Results (Cont’d) Speed, Volume, Speed Variance, Volume Ratio Time of Day Chart @ Location 3
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* Volume is a good indicator to identify peak hour traffic.
* 120-minute is the recommended time interval to do the analysis.
Conclusion
High Frequency
High frequency
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Questions