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Estimating Travel Patterns on I‐95 with Automated Technology

Estimating Travel Patterns on I‐95 with Automated Technology. Taruna Tayal (M/A/B) Brian Wert (M/A/B) Bill Thomas (Baker). NCAMPO Conference - Asheville, NC May 3, 2012. What are we talking about?. Purpose of the study Unique Features of the study Design and Data Collection

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Estimating Travel Patterns on I‐95 with Automated Technology

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  1. Estimating Travel Patterns on I‐95 with Automated Technology • Taruna Tayal (M/A/B) • Brian Wert (M/A/B) • Bill Thomas (Baker) • NCAMPO Conference - Asheville, NC • May 3, 2012

  2. What are we talking about? • Purpose of the study • Unique Features of the study • Design and Data Collection • Data Analysis and Summary • Findings and Results • ALPR to trip table

  3. Purpose of the study • Understand travel patterns on I-95 in NC • Origin Destination study using Automated License Plate Recognition technology (ALPR) • O-D flow table providing volume and percentage of trips by vehicle class between each station

  4. Unique Features of the study • Length of the corridor – 180 miles • First study of this magnitude in US • Data collected for two vehicle class • Passenger Cars • Trucks

  5. Unique Features of the study • Based on trip distance, studied 3 trip patterns: • External-External • External-Internal • Internal-Internal

  6. Design & Data Collection 1 • Data collected at 10 locations • Eight on I-95 • One each on: • I-40 , and • US-64 • 48-hour tube class counts collected at each location 2 10 3 9 4 5 6 7 8 #

  7. What is ALPR? • Automatic License Plate Recognition • Camera mounted on overhead bridge to capture license plate image

  8. Data Collection • 1 camera/lane/direction = 4 cameras/location • 40 cameras for the entire study corridor

  9. Data Collection Data collected for 30-hour period, capturing entire 24-hour day of movement for length of corridor.

  10. RAW Data from Survey • 40 x 40 OD matrix with plate matching at each site for PC and HV by hour • 48-hour class tube counts at each site by direction by lane • Table of total captured records at each site by lane by direction by hour.

  11. Expansion Procedure • Expanded captures to more closely match counts • Utilized methodology from similar study • Methodology combines: • Average of origin and destination capture rate • Product of origin and destination capture rate • Augmented to use single factor along identity

  12. ALPR Summary

  13. Findings and Results • Captured License plates for 65% of vehicles • 180,000 passenger vehicles • 47,000 heavy vehicles (20%) • 75% of observations in central & southern corridor • 35% of all “captured” vehicles observed at more than one location

  14. Findings and Results • 15 - 20% vehicles observed in the vicinity of the state lines traveled through survey area • 35% of travel from internal/external of survey area • Heavy vehicle usage similar to passenger cars • 58% of surveyed vehicles registered out-of-state

  15. Interesting results

  16. ALPR to Trip Table • Expanded ALPR converted to trip table • Associate each loading point with an interchange along I-95 • Use local knowledge to establish weights for each loading point based on neighboring AADT and associated interchange volumes • Calculate 71 by 71 seed matrix by applying weights to 20 x 20 ALPR OD Matrix

  17. ALPR to seed matrix

  18. CONTACT tarunatayal@mabtrans.com brianwert@mabtrans.com BThomas@mbakercorp.com 410-689-3450 919-829-0328

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