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Topics Survey data comparisons to “old” model Bluetooth OD data findings Freight model design Q & A.

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Presentation on theme: "Topics Survey data comparisons to “old” model Bluetooth OD data findings Freight model design Q & A."— Presentation transcript:

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2 Topics Survey data comparisons to “old” model Bluetooth OD data findings Freight model design Q & A

3 Survey Data Comparisons Survey data processing –Trip linking (removing stops for “change mode” activities) –Identification of trips with one external end –Coding trip purpose –Identification of production vs attraction end –Expansion of transit trips (trips = 1/boardings)

4 Trip Rate Comparisons

5 Trip Length Comparisons Home-Based Work

6 Trip Length Comparisons Home-Based Shop

7 Trip Length Comparisons Home-Based Other

8 Trip Length Comparisons Non-Home-Based Other

9 Mode Summaries

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11 Bluetooth Data 19 locations –10 on Seward Highway –9 within or near Mat-Su Borough Collected August 14 – August 20 th 2014 Vehicle trajectories cleaned and expanded to AADT counts at or near locations –AM period (7-9 AM), PM period (3-6 PM), Daily Some data analysis performed –More to follow during model validation Some disadvantages to Bluetooth data –Trip purpose, market segment, and ultimate origin- destination not identifiable

12 Station Locations Anchorage Mat-Su

13 Data Cleaning and Expansion Shortcomings addressed by data cleaning & expansion –Multiple trips from same Bluetooth device –Multiple recordings from same station\trip –Trajectories adjusted by probability of observation (account for short trip bias) –Expanded to traffic counts using iterative proportional fitting

14 Data Expansion Goodness-of-Fit Excellent match to counts across all expanded Bluetooth traces for each period

15 Data Analysis (so far) 62% of total internal to Anchorage 27% of total internal to Mat-Su 11% of total between Anchorage and Mat-Su Approximately 70% of trips are less than 5 miles from begin to end station

16 Commercial Vehicle Models Freight –Eight weeks of American Traffic Research Institute (ATRI) 2013 truck GPS traces purchased, processed and geocoded –To be expanded to classification counts –Trip rates and trip length frequency distributions to be calculated from data –FAF data obtained for internal\external and through flows Non-freight commercial vehicles –Three-step quick response model to be developed

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