Car Chaos Visualizing Factors in Car Ownership to Predict & Mitigate Residential Parking Demand in Boston, MA

Transcription

1 Car Chaos Visualizing Factors in Car Ownership to Predict & Mitigate Residential Parking Demand in Boston, MA R Kiracofe J C Warner 1

2 Motivation Parking is controversial. Demand for residential parking is hard to assess. Data either does not exist, is not public, or is supposedly public yet the city refuses to give it out. Cities need alternate means for assessing demands A beginning to establishing such a model 2

3 How can we predict residential parking demand? What areas are more likely to see high car ownership and therefore parking demand? What other characteristics define areas with high car ownership? What variables can be used to predict demand in lieu of reliable parking data? 3

4 The Survey Area Boston * 4 *Excl. East Boston due to data storage differences

5 WHERE DO PEOPLE OWN CARS IN BOSTON? 5

6 With variables are correlated? What indicators do planners use to make residential parking policy? A start: census and demographic layers 6

7 People who own cars drive them to work 7

8 Unlike many dense cities in other countries, people who own cars in Boston USE THEM OFTEN. Most car owners commute by car. 8

9 What kinds of places are likely to have high car ownership, and therefore high parking demand? Changes to parking policy are often granted based on: 1) Proximity to transit 2) Household income 3) Household size 4) Senior citizen status It makes sense to examine these as bases for predicting parking needs. Which, if any, are truly significant? 9

10 We sorted the census blocks into quintiles based on car ownership to examine the other attributes of these groups 10

11 1...Proximity to transit First average 0.10 mi Second 0.34 mi Third 0.36mi 0.71mi Fourth Those that own fewer cars are concentrated near transit mi Fifth distance (mi)

12 2. Household Income First Second Third Lower income households are more likely to own fewer cars 12 average $35,396 $51,802 $58,979 Fourth $69,304 Fifth $87,347 median household income ($)

13 3. Household Size First average 1.90 Second Third 2.59 Fourth Smaller households more likely to own fewer cars Fifth average people per household

14 4. Senior status First average 10.2% Second 11.1% Third Differences not statistically significant, though outliers may prove interesting % Fourth 11.1% Fifth 11.9% percent of population that are seniors

15 Trends are clearly emerging 15

16 Statistical support for 3 of 4 factors Single-factor Analyses of Variances (ANOVA) tests give p < for transit proximity, household size, and income, indicating the divisions into quintiles based on car ownership were unlikely to be due to chance. p = 0.51 for senior status indicates the quintile divisions are not significant. 16

17 But large variances make vast confidence intervals not significant 17

18 Which data have predictive power? 1) 2) 3) 4) Proximity to transit PROBABLY Household income YES Household size YES Senior citizens NO 18

19 Affecting parking demand is difficult. - Challenge the perception that urban centers do not have enough parking - Lack of data is a major barrier to reform 19

20 Recommended next steps - Boston parking inventory study - Community-level studies on feasibility of parking caps/permit fees - Publicly available parking permit data - Build more in-depth demand model with expanded data set 20

21 thank you R Kiracofe (kiracofe@mit.edu) J C Warner (cwarner@mit.edu) December 2015 GIS Workshop, MIT Department of Urban Studies and Planning 21

22 Mass GIS Cartographic Model SocialExplorer, ACS and Census Mass GIS 22

23 23

24 Understanding cars per household per square mile 2 car/person/sqmi In a constant area, cars/person/sqmi is proportional to cars/person. 1 car/person/sqmi 0.5 car/person/sqmi 0.25 car/person/sqmi But when considering parking, cars are inherently an issue of space 24

25 Progressive cities should make parking decisions in relation to density. parking one car per household in the Back Bay is not the same issue as parking one car per household in West Roxbury. Traditional ideas of parking expects one car per household in the suburbs, whereas people living near transit-stations or in downtown areas are expected to have lower car ownership rates 25

26 0.25 car/person/sqmi 2 car/person/sqmi 1 person 1 car 0.5 sq mi 1 person 2 car 1 sq mi 1 person 8 car 4 sq mi Cars/person/sqmi better puts similar parking situations at the same ranking for a set using census block groups where size and population are related and indicative of density. 8 people 1 car 0.5 sq mi 4 people 1 car 1 sq mi 1 person 1 car 4 sq mi 26