NACTO 2013 - SFCTA Apps

Post on 29-May-2015

197 views 1 download

Tags:

description

Presentation given at the NACTO 2013 conference in Phoenix AZ.

Transcript of NACTO 2013 - SFCTA Apps

San Francisco County Transportation Authority: Our Apps

elizabeth@sfcta.org@e_lo

Who am I and Where do I come from?

27513

Who am I and Where do I come from?

94114

Participatory Planning in SF

Outreach Objectives

USEFUL

FAIR

PRACTICAL

Are all constituents able to participate?

Are benefits commiserate with costs?

Mutually beneficial exchange

Technology

1. MyStreetSF.com

2. sfbudgetczar.com

3. Cycletracks

M:\PnP\2013\Memos\01 Jan 15

mystreetsf.com

sfbudgetczar.com

All age, racial, ethnic and income groups reached, but

Over-representation of: Ages 25-40 White Higher-Income

9

sfbudgetczar.com – responses

sfbudgetczar.com – what we heard

1. Useful tool

2. Back to the basics of existing system

3. Faster, more frequent service

4. Improve cycling and walking conditions.

5. Core capacity improvements

6. Faster project delivery

7. Mixed support for congestion pricing

8. Support for more revenue

CycleTracks

Amazon EC/2 Server running Apache

mySQL

JSONPHP PHP

CycleTracks

Broad User Base• 20% (500+) users infrequent cyclists (10% of

trips)

SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 13

Less than once a month Several times per month Several times per week Daily

187 411 852 853577

2,036

9,122

13,506

Trips and Users by Cycling Frequency

Users Trips

Broad User Base• Half of users submit > 5 trips• 10% of users submitted > 20 trips• 40 users submitted >100 trips (Max = 685)

SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 14

1 2-5 6-10 11-15 16-20 21-7000

100

200

300

400

500

600

700

80031%

20%

8%

5%3%

10%

Users by Trips Submitted

Combined Reach: ~44,000 trips

SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 15http://goo.gl/maps/DuqGh

Combined Reach

Bias?

• Tradeoff between bias and quantity– But bias can be dealt with if quantity is high

enough.• Which biases are acceptable and when?

• i.e. does income affect how adverse to biking up hills you are (vs. biking around them) ?

• What biases can we undo with technology?

M:\PnP\2013\Memos\01 Jan 15

Combined Reach: ~44,000 trips

SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 17http://goo.gl/maps/DuqGh

Where does it fit in Value Chain?

Planning for Network Connectivity

Identify Potential Barriers

Before and After Analysis

Photo courtesy of Nathan Wilkes, City of Austin

Before

After

After

Represent in Regional Model

Represent in Regional Model

Value of Bike Facilities

Attribute Coef. SE t-stat. p-val.Length (mi)--1.05 0.09 --11.80 0.00

Turns per mile --0.21 0.02 --12.15 0.00Prop. wrong way --13.30 0.67 --19.87 0.00Prop. bike paths 1.89 0.31 6.17 0.00Prop. bike lanes 2.15 0.12 17.69 0.00

Cycling freq. < several per wk. 1.85 0.04 44.94 0.00Prop. bike routes 0.35 0.11 3.14 0.00

Avg. up-slope (ft/100ft) --0.50 0.08 --6.35 0.00 Female --0.96 0.22 --4.34 0.00

Commute --0.90 0.11 --8.21 0.00Log(path size) 1.07 0.04 26.38 0.00

Value of Bike Facilities

San Francisco County Transportation Authority

elizabeth@sfcta.org@e_lo