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Traffic Data Visualization and Analysis at University of Minnesota

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Explore traffic data visualization techniques using various dimensions and subsets. Discover trends, outliers, and clustering patterns for different traffic parameters. Utilize spatial database for in-depth analysis.

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Traffic Data Visualization and Analysis at University of Minnesota

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  1. Traffic Data Visualization Shashi Shekhar Spatial Database Lab Department of Computer Science University of Minnesota shekhar@cs.umn.edu Http://www.cs.umn.edu/research/shashi-group/

  2. Dimensions • Available • TTD : Time of Day • TDW : Day of Week • TMY : Month of Year • S : Station, Highway, All Stations • Others • Weather, Seasons, Event types, …

  3. Traffic Dimensions

  4. Subsets of Dimensions TTDTDWTMYS TTDTDWS TTDTDW TDWS STTD S TTD TDW

  5. Singleton Subset TTD Configuration: • X-axis: time of day; Y-axis: volume • For stations sid 138, sid 139, sid 140, on 1/12/1997 Trends: • Station sid 139: rush hour all day long • Station sid 139 is an S-outlier

  6. Singleton Subset: TDW • Configuration: • X axis: Day of week; Y axis: Avg. volume. • For stations 4, 8, 577 • Avg. volume for Jan 1997 Trends: • Friday is the busiest day of week • Tuesday is the second busiest day of week

  7. Singleton Subset: S • X-axis: I-35W South; Y-axis: Avg. traffic volume • Avg. 5–min traffic volume for January 12,1997 Configuration: Trends: • High avg. traffic volume from Franklin Ave to Nicollet Ave • Two outliers: 35W/26S(sid 576) and 35W/TH55S(sid 585)

  8. Dimension Pair: TTD-TDW • X-axis: Time of day; Y-axis: Day of week • f(x,y): Avg. volume over all stations for Jan 1997 Configuration: • Evening rush hour broader than morning rush hour • Rush hour starts early on Friday. • Wednesday - narrower rush hour Trends:

  9. Dimension Pair: S-TTD Configuration: • X-axis: Time of day • Y-axis: Highway I-35W North Bound • f(x,y): Avg. volume over all stations for 1/15, 1997 Trends: • 3-Cluster • North section: Evening rush hour • Downtown area: All day rush hour • South section: Morning rush hour • S-Outliers • station ranked 9th • Time: 2:35pm • Missing Data

  10. Post Processing of Cluster Patterns • Clustering Based Classification: • Class 1: Stations with morning rush hour • Class 2: Stations with morning + evening rush hour • Class 3: Stations with evening rush hour

  11. Dimension Pair: TDW-S • X-axis: stations on I35W South; Y-axis: day of week • f(x,y): Avg. volume over all stations for Jan-Mar 1997 • Busiest segment of I-35W South is b/w Downtown MPLS & I-62 • Saturday has more traffic than Sunday • Outliers – highway branch Configuration: Trends:

  12. TTDTDWS: Comparison of Traffic Video Configuration: Traffic volume on Jan 9 (Th) and 10 (F), 1997 • Evening rush hour starts earlier on Friday • Congested segments: I-35W (downtown MPLS – I-62); I-94 (MPLS – St. Paul); I-494 (intersection I-35W) Trends:

  13. TTDTDWTMYS(Album) • Outer: X-axis (month of year); Y-axis (highway) • Inner: X-axis (time of day); Y-axis (day of week) Configuration: Trends: • Morning rush hour: I-94 East longer than I-35 W North • Evening rush hour: I-35W North longer than I-94 East • Evening rush hour on I-94 East: Jan longer than Feb

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