1. RTC DVRPC 2012-2013 Household Travel Survey TMIP Peer-Review October 29, 2014 Ben Gruswitz, AICP Office of Modeling & Analysis Sarah Moran Office of Modeling & Analysis Delaware Valley Regional Planning Commission

2. SURVEY BACKGROUND 1-day paper diary survey 10,000 households goal, 9,384 actual complete good surveys (almost 900,000 HHs contacted) 3 day GPS sub-sample (500 HH goal, 380 actual) Address based sampling frame 12 month roughly equal sample, weekdays State, area-type, HH-size x income, and HH-size x auto ownership as control variables Diary data retrieved by either phone, web, or mail

3. Stratified random sample by State & Area Type (CBD, urban, suburban, rural, etc.) Oversample with higher transit propensity Transit Score - population density, employment density, & carless households Quintile Approach – oversample tracts by an individual county’s top scoring tracts (top 20%) Incentive program: 0-vehicle; Low income (<$35,000); and Spanish speaking SAMPLING PLAN

5. GPS data was originally desired to correct for under-reporting Conclusions so far: Data is interesting Can be good check against diary data Has it’s own flaws DATA QUALITY - GPS

6. GPS SAMPLE 6 Income Range GPS Sample $0 to $9,99910 $10,000 to $24,99937 $25,000 to $34,99926 $35,000 to $49,99947 $50,000 to $74,99992 $75,000 to $99,99971 $100,000 to $149,99974 $150,000 to $199,99937 $200,000 to $249,99914 $250,000 or more18 Don't know1 Refused44 Total471 Household Size GPS Sample 1118 2199 376 457 514 66 101 Total471 Area Type GPS Sample CBD9 CBD Fringe1 Urban93 Suburban260 Rural95 Open Rural13 Total471

7. Transponders not always on (take a while to connect) DATA QUALITY - GPS

8. Data processing can under-report trips DATA QUALITY - GPS

9. DATA PROCESSING Data Quality Assurance & Control Verbatim response recoding Geocoding Tour identification and classification Missing data and trip imputation Formatting Misaligned fields Weighting Data weighted and expanded to reflect demographics by county and area type Household and Person weights 9

10. QUERY SUMMARY

11. WHAT’S AN “OTHER” RESPONSE? Work Status Codes & Categories 1.Retired 2.Disabled/on disability status 3.Homemaker 4.Unemployed but looking for work 5.Unemployed and not looking for work 6.Student 7.Volunteer 97.Other 98.Don't know 99.Refused Person ID Work Status Work Status - Other UUUUU6 WWWWW3 XXXXX97Elderly YYYYY1 ZZZZZ1

12. COMPARING RESULTS ArcGIS Model Output “XY to Line” tool gives point to point distance Model created fields to flag records where Google/Bing geographies disagree Google Bing

13. CHANGE IN PERSON TRIP RATE 13 Household Trip Rate Person Trip Rate County Households Population Trip Rate Trips (HHRate*HH) Trip Rate Trips (PRate*P) Burlington 165,620 449,1177.70 1,274,8342.73958 1,230,391 Camden 188,861 513,6607.90 1,491,7322.92433 1,502,110 Gloucester 104,091 288,1877.52 783,1762.93160 844,848 Mercer 130,292 366,4427.98 1,040,0443.43389 1,258,322 NJ Counties588,864 1,617,4067.79 4,589,7862.989774,835,671 Bucks 229,933 625,4857.57 1,739,9283.01902 1,888,352 Chester 183,793 499,5487.81 1,436,1692.82283 1,410,137 Delaware 206,021 558,8747.53 1,550,5532.91042 1,626,561 Montgomery 308,083 799,8867.58 2,334,5222.88910 2,310,950 Philadelphia 580,509 1,525,8116.29 3,653,7572.71217 4,138,252 PA Counties 1,508,339 4,009,6047.10 10,714,9292.83675 11,374,252 DVRPC Total 2,097,203 5,627,0107.30 15,304,7152.88073 16,209,923

14. CHANGE IN PERSON TRIP RATE 14

15. CHANGE IN MODE SHARE 15