Integrating Data Into the Public Planning and Policymaking Process - - PowerPoint PPT Presentation

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Integrating Data Into the Public Planning and Policymaking Process

Integrating Locational Data into Transit Planning

California Transit Association's 50th Annual Fall Conference & Expo

November 19, 2015 Christopher Wornum

Big data is like teenage sex…

Everyone talks about it, Nobody really knows how to do it, Everyone thinks everyone else is doing it, ….so everyone claims they are doing it.

Can Cell Phone Data Replace Travel Diary Survey

Significant Challenges Remain, but May Be Resolved Expanding survey data to represent population

» Vender expansion methods are proprietary & very much a black box » Android phones over represented in low income population, Manhattan is 70%-plus Apple, other boroughs are opposite distribution

Lack individual socioeconomic data

» Must rely only on aggregate socioeconomic data based on the imputed household location. » Must expand based on individual rather than household

Trip-Making Bias

» Incorrect stop determination, » Cell phone owners not carrying their devices, or » Multiple devices assigned to each owner.

Temporal Bias

» Home & work location determined by time of day » Inaccurate for 24/7 shift-based industrial and service industries.

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Spatial Bias

Key benefits of GPS compared to cellular

4 250 m 2,000 m 5 m

Locational Bias

Key benefits of GPS compared to cellular

5 10 time per day 2.4 hours 30 times per minute 144 minutes I minute

Major Providers and Public Validation Sources

Proprietary Data Providers AirSage Streetlight HERE INRIX TomTom Nokia (NEXT) Strava TRANSEARCH

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Publicly Available Data

Census Transportation Planning Package (CTPP), National Household Travel Survey (NHTS),

Highway Performance Monitoring System (HPMS)

Freight Analysis Framework (FAF).

GPS vs. Cellular Data

Key benefits of GPS compared to cellular:

» High spatial precision, incl. for road segments (5m vs. 250-2000m). » High frequency rate (30x/min vs. 10x/day) » Ability to separate personal from commercial travel » Non-motorized modes (walk, bike) from Strava » Calibration tests using license plate scanner data » Data set growing and improving every day.

Key detriments of GPS compared to cellular:

» More sampling skews, especially towards wealthier and unfamiliar trips (more on how we correct later). » No differentiations between transit and auto. » No long-time patterning, meaning we can’t identify what ‘tourists’ do when they’re visiting.

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Cost

AirSage Example

8 1 Day Year(s) Small city State(s) Zip code Census block group) No distinction 9 trip purposes Weekly average Individual daily totals Daily total 5 day parts None Income, age $10,000 None Resident, visitor, commuter

Number of days Geographic coverage Granularity Trip purposes Data totaled or averaged Time of day/periods Census information Type of travel Price Range

0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 2011 Air Sage 2013 ACTC 2013 ACTC before Adjustments

Model Validation on Trip Distribution

Distribution of Trips from San Joaquin County

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Understanding Travel Markets for Transit

Three Travel Markets through Tri-Valley

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Destinations Origins

< ½ < ½ mile ile ½ to 5

• 5 mile

iles > 5 5 m miles BART & Amtrak Stations San Joaquin Valley ~60% ~30% ~10%

Regional Transit Markets Limited

First Mile/Last Mile Passenger Collection & Distribution

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US 101 South Speeds, Evening Rush Hour

Without HOV Lane New HOV Lane

8 PM 6 PM 4 PM 2 PM

(detectors down, I-280 to I-80)

8 PM 6 PM 4 PM 2 PM

(detectors down, I-280 to I-80)

Direction of Travel