Public Bikesharing in North America: Early Operator and...
Transcript of Public Bikesharing in North America: Early Operator and...
Public Bikesharing in North America: Early Operator and User Understanding
Bicycle Urbanism Symposium Washington University
June 20, 2013
Susan Shaheen, Ph.D., Associate Adjunct Professor
Adam Cohen
Associate Researcher
Elliot Martin, Ph.D. Assistant Research Engineer
Overview • Public bikesharing: history • Study methodology
• Bikesharing operations in North America
• N. American bikesharing impacts & developments
• Summary
Bikesharing Generations • 1st Generation: Free Bikes (“White Bikes”)
– Demonstration and provided increased mobility
• 2nd Generation: Coin-Deposit Systems – Emerged from a need to deter theft and incentivize return.
• 3rd Generation: Information Technology (IT) System – Provides real-time information; employs technology to assist
in rebalancing demand.
• 4th Generation: Demand-Responsive, Multi-Modal Systems – Mobile docking stations; smartcard integration with public
transit; bike redistribution innovations; GPS tracking, touchscreen kiosks, and electric bikes.
N. America: Historical Overview • North America’s first IT-based bikesharing system, Tulsa
Townies, started operating in 2007 in Tulsa, OK • First solar-powered, fully automated docking-based system in the
world; provides service free of charge.
• In Canada, first IT-based public bikesharing system, BIXI (BIcycle-TaXI), began operating in 2009 in Montreal
Study Methodology • Operator interviews with all 19 North American IT-
based programs operational as of April 2012
• Conducted 14 interviews with transportation personnel, transit operators, policymakers, and community bike coordinators
• Completed online survey with users of early public bikesharing systems in: Montreal; Toronto; and the Twin Cities (Minneapolis and Saint Paul), Washington, D.C. allowed input to their survey and sent us the data.
• Analyzed operational data from two American operators for 2011
Bikesharing: North America As of January 2012, 19 IT-based programs:
• 216,422 users and 11,473 shared bicycles As of May 2012, there were 21 IT-based based operations. 18 more planned in 2012-2013 (NYC, Chicago, LA, SF)
Shaheen et al., 2012
Seasonal vs. Year-Round Operations
Shaheen et al., 2012
Business Models
Shaheen et al., 2012
Types of Funding/Revenue Sources
Shaheen et al., 2012
16%26%
89%95%
68%
32%26% 26%
16%
0%10%20%30%40%50%60%70%80%90%
100%
Perc
ent o
f Ope
rato
rs
Type of Funding and Revenue
n = 19
Optimum Distance Between Docking Stations
Shaheen et al., 2012
0%
10%
20%
30%
40%
50%
60%
70%
80%
Between 100 -300 yards
Between 300yards - 1/4 mile
Between 1/4mile - 1/2 mile
Between 1/2mile - 3/4 mile
More than 3/4Mile
Perc
ent o
f Ope
rato
rs b
y Co
untr
y
Distance
U.S., n = 15
Canada, n = 4
Docking Station Features
Shaheen et al., 2012
Member Survey: Overview
Fall 2011/Early 2012
Shaheen et al., 2012
Program Users Bicycles Stations Sample Size
Capital Bikeshare (D.C.) 18,000 1,200 130 5,248
Nice Ride Minnesota (Twin Cities) 3630 960 116 1238
BIXI-Montreal 40,000 5,120 411 3,322
BIXI-Toronto 4,000 1,000 80 853
Basic City Statistics of Member Survey
1
Transit Facts Washington, D.C. Toronto Montreal Minneapolis-St.Paul
Kilometers of Rail Track 341 373 122 40
Number of Buses 1,495 1,811 1,600 885
Number of Rail (or Metro) Cars 1,106 951 759 27
Unlinked trips 418,125,650 477,357,000 388,600,000 78,048,647
Population Facts Washington, D.C. Toronto Montreal Minneapolis-St.Paul
Population 601,723 2,503,281 1,620,693 667,646
Area (km2) 177 630 365 288
Population Density (pop/km2) 3,400 3,972 4,439 2,317
Year of Data 2010 2010 (transit)2006 (population)
2010 (transit)2006 (population)
2010
Distribution of Key Demographics
4%2%
4%5%
13%
19%
14% 14%12%
7% 6%
0%2%4%6%8%
10%12%14%16%18%20%
Income
0% 2%9%
42% 46%
1%0%5%
10%15%20%25%30%35%40%45%50%
Education
6% 2%
79%
4% 5% 4%0%
20%40%60%80%
100%Race/Ethnicity
0%
11%
48%
21%
10% 8%1% 0%
0%10%20%30%40%50%60%
Age
Bikesharing Trip Purpose 56%
2% 1% 1%
19%
10%3% 6%
0%
10%
20%
30%
40%
50%
60%
Montreal
38%
8% 7%1%
14% 14%9% 9%
-10%
0%
10%
20%
30%
40%
50%
60%
Minneapolis-St. PaulQuestion: What is your most common trip purpose for using Nice Ride Minnesota?
N = 123238%
6% 7% 4%
21%12%
7% 5%
-10%0%
10%20%30%40%50%60%
Washington, D.C.
N = 5140
50%
8%2% 2%
11%19%
2%7%
0%
10%
20%
30%
40%
50%
60%
TorontoQuestion: What is your most common trip purpose for using BIXI?N = 843
Question: What is your most common trip purpose for using BIXI?
Question: What was the primary purpose of your MOST RECENT Capital Bikeshare trip?
N = 3299
Commute Times in the United States
2%4%
7%
14%16%
7%
22%
6% 7% 9%4%
1%
11%
32%28%
11%
6%4% 3% 1% 1% 2% 1% 0%
0%
5%
10%
15%
20%
25%
30%
35% Washington, D.C. and Arlington, VA
Washington, D.C. and Arlington VA(1-year ACS 2010)
Capital Bikeshare, N = 4342
1%7%
14%20% 22%
10%15%
2% 2% 4% 3% 1%
37%
26%
12%8% 7%
2% 1% 1% 1% 1% 2% 3%0%5%
10%15%20%25%30%35%40%
Minutes to Work
Minneapolis, MNMinneapolis (1-year ACS 2010)
Nice Ride Minnesota, N = 971
Commute Times in Canada
23%18%
13%9% 9%
2%6% 5%
3% 4%0% 0% 2% 0% 1% 2%
41%37%
0%5%
10%15%20%25%30%35%40%45%
Montreal, QC
Quebec General Social Survey
Bixi Montreal, N = 2851
20%15% 14%
10% 10%
2% 5% 6%2% 3% 0% 1% 4% 1% 1% 1%
55%
17%
0%
10%
20%
30%
40%
50%
60%
Kilometers to Work
Toronto, ON
Ontario General Social Survey
Bixi Toronto, N = 733
One-way and Round-trip
Shaheen et al., 2012
Shaheen et al., 2012
40%
15%17%
28%
17%19%
27%
38%
0%
10%
20%
30%
40%
50%
60%
Often Sometimes Rarely Never
Montreal
One-way, from station to station, N = 3227
Round Trip, back to the same station, N = 320440%
14% 13%
33%
15%18%
21%
46%
0%
10%
20%
30%
40%
50%
60%
Often Sometimes Rarely Never
Toronto
One-way, from station to station, N = 824
Round Trip, back to the same station, N = 806
53%
17%
8%
21%26%
21% 21%
32%
0%
10%
20%
30%
40%
50%
60%
Often Sometimes Rarely Never
Minneapolis-Saint Paul
One-way, from station to station, N = 1189
Round Trip, back to the same station, N = 1174
System Activity CapitalBikeshare & NiceRide Minnesota
1
2011 System Data Data Type1st Quarter
(limited data)2nd Quarter 3rd Quarter 4th Quarter Total
Total Trips 10,976† 374,203 405,450 313,001 1,103,630†
Single-Station Round-Trips
584 24,240 23,643 13,553 62,020
% of Single-Station Round-Trips
5.3% 6.5% 5.8% 4.3% 5.6%
Total Trips NA 60,785 117,219 39,526 217,530
Single-Station Round-Trips
NA 5,840 11,237 2,827 19,904
% of Single-Station Round-Trips
NA 9.6% 9.6% 7.2% 9.2%
† 1st Quarter 2011 Capital Bikeshare data released was a subset (7%) of total trips during the quarter.
Capital Bikeshare (Washington, D.C.)
Nice Ride Minnesota (Minneapolis-Saint Paul)
2011 System Data Data Type 1st Quarter (limited data) 2nd Quarter 3rd Quarter 4th Quarter Total
Capital Bikeshare (Washington,
D.C.)
Total Trips 10,976† 374,203 405,450 313,001 1,103,630†
Single-Station Round-Trips 584 24,240 23,643 13,553 62,020
% of Single-Station Round-Trips 5.3% 6.5% 5.8% 4.3% 5.6%
Nice Ride Minnesota
(Minneapolis-Saint Paul)
Total Trips NA 60,785 117,219 39,526 217,530
Single-Station Round-Trips NA 5,840 11,237 2,827 19,904
% of Single-Station Round-Trips NA 9.6% 9.6% 7.2% 9.2%
† 1st Quarter 2011 Capital Bikeshare data released was a subset (7%) of total trips during the quarter.
Trip Duration
Shaheen et al., 2012
Shaheen et al., 2012
13%
30%
21%
13%
8%4%
2% 1% 1% 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 2%0%
5%
10%
15%
20%
25%
30%
35%
Minutes
Washington, D.C.Capital Bikeshare Operational Data
18%
30%
18%
11%7%
4%2% 1% 1% 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1%
0%5%
10%15%20%25%30%35%
Minutes
Minneapolis-Saint PaulNice Ride Minnesota Operational Data
N = 217,530 Trips in 2011
N = 1,103,598 Trips in 2011
Modal Shift Question Structure
As a result of my use of <bikesharing>, I use the bus… □ Much more often □ More often □ About the same (bikesharing has had no impact) □ Less often □ Much less often □ I did not ride the bus before and I do not ride the bus now. □ I have changed how I use the bus, but not because of Nice Ride Minnesota.
1
Change in Bicycling
33%28%
7% 6%
27%
0%
10%
20%
30%
40%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Montreal
N = 3264
26%
45%
3% 0%
26%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1218 36%
46%
1% 0%
16%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5219
29%35%
5%2%
29%
0%5%
10%15%20%25%30%35%40%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Toronto
N = 842
As a result of my use of bikesharing, I ride a bicycle (any bicycle)...
Change in Driving a Car
0% 0%
25%
12%
63%
0%10%20%30%40%50%60%70%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
MontrealN = 3284
0% 0%
44%
9%
47%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1230
0% 0%
30%
11%
59%
0%10%20%30%40%50%60%70%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5248
0% 0%
19%
6%
75%
0%10%20%30%40%50%60%70%80%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
TorontoN = 845
As a result of my use of bikesharing, I drive a car...
Change in Taxi Use
0% 2%
27%
17%
53%
0%
10%
20%
30%
40%
50%
60%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
MontrealN = 3280
0% 1%14%
5%
80%
0%10%20%30%40%50%60%70%80%90%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1222
0% 1%
36%
17%
46%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5201
0% 1%
32%
13%
54%
0%
10%
20%
30%
40%
50%
60%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
TorontoN = 842
As a result of my use of bikesharing, I use a taxi...
With Transit Impacts Minneapolis Seems Different
1
Source: Greg Benz
Change in Urban Rail
Shaheen et al., 2012
2%9%
33%
17%
38%
0%
10%
20%
30%
40%
50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
MontrealN = 3281
2%13%
3% 0%
82%
0%10%20%30%40%50%60%70%80%90%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1221
1%6%
38%
10%
46%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5210
1%8%
32%
12%
47%
0%5%
10%15%20%25%30%35%40%45%50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
TorontoN = 840
As a result of my use of bikesharing, I use urban rail...
Change in Bus
Shaheen et al., 2012
Shaheen et al., 2012
1%5%
30%
17%
46%
0%
10%
20%
30%
40%
50%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
MontrealN = 3280
1%
13% 14%3%
69%
0%10%20%30%40%50%60%70%80%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1219
1%4%
32%
7%
56%
0%
10%
20%
30%
40%
50%
60%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5217
0% 2%14%
7%
77%
0%10%20%30%40%50%60%70%80%90%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
TorontoN = 842
As a result of my use of bikesharing, I use the bus...
Change in Walking
6%
20%
34%
5%
35%
0%
10%
20%
30%
40%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
MontrealN = 3276
6%
31%
22%
1%
39%
0%5%
10%15%20%25%30%35%40%45%
Much moreoften
More often Less often Much lessoften
No Changeas a Result ofBikesharing
Twin Cities
N = 1221
2%
15%
29%
1%
52%
0%
10%
20%
30%
40%
50%
60%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
Washington, D.C.
N = 5183
4%
17%
39%
7%
33%
0%5%
10%15%20%25%30%35%40%45%
Much moreoften
More often Less often Much lessoften
No Change asa Result ofBikesharing
TorontoN = 843
As a result of my use of bikesharing, I walk...
Urban Rail Systems of Cities Surveyed Minneapolis Montreal Washington, D.C.
Toronto
Perceptions of Bikesharing as Enhancing Transit
Shaheen et al., 2012
81%
17%1% 1% 0%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I think of BIXI as an enhancement to the Montreal public transportation system.
77%
20%1% 1% 0%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I think of BIXI as an enhancement to the Toronto public transportation system.
N = 841
82%
16%1% 1% 0%
0%20%40%60%80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I think of Nice Ride Minnesota as an enhancement to the Twin Cities public transportation system.
N = 1233
N = 3291
Shaheen et al., 2012
Bikesharing with Transit instead of Car
Shaheen et al., 2012
Shaheen et al., 2012
20% 21% 19% 21% 18%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
Since joining BIXI, I have made trips with public transit and bikesharing (together) that I would have previously done with a car. [Montreal]
9%19% 22%
30%20%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
Since joining BIXI, I have made trips with public transit and bikesharing (together) that I would have previously done with a car. [Toronto]
N = 845
19%31%
21% 23%6%
0%20%40%60%80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
Since joining Nice Ride Minnesota I have made trips with public transit and bikesharing (together) that I would have previously done with a car.
N = 1227
N = 3277
Reduction of Vehicle Ownership
Shaheen et al., 2012
7135
398 5530
10002000300040005000600070008000
No Sold or donated a household vehicle
Considered selling a personal vehicle
Since you joined [public bikesharing], have you sold, donated or otherwise gotten rid of a personal household vehicle or considered selling a personal
vehicle?
82
135162
14
0
50
100
150
200
Very important Somewhat important Not at all important Don’t know
How important has your membership with [public bikesharing] been in your decision to sell or consider selling a personal vehicle?
N = 393[B]
N = 8086[A]
Shaheen et al., 2012
Impact on Local Shopping
Shaheen et al., 2012
Shaheen et al., 2012
9%
33%
0% 0%
58%
0%10%20%30%40%50%60%70%
Much more often More often Less often Much less often No Change as a Resultof Bikesharing
MontrealN =…
31%
52%
0% 0%17%
0%
20%
40%
60%
Much more likely Somewhat more likely Somewhat less likely Much less likely Not more or lesslikely, no difference
Washington, D.C.N = 5153 Question: If a business, restaurant, or shop is easily accessible
by Capital Bikeshare, does that access make you more or less likely to patronize that establishment?
7%
38%
0% 0%
54%
0%20%40%60%
Much more often More often Less often Much less often No Change as a Resultof Bikesharing
TorontoN = 841
As a result of my use of bikesharing, I shop at locations near existing bike stations...
Impact on Exercise
Shaheen et al., 2012
34% 39%
18%7% 1%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I get more exercise now that I am a member of BIXI. [Montreal]
19%
39%26%
13%3%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I get more exercise now that I am a member of BIXI. [Toronto]N = 841
21%
41%26%
10%2%
0%
20%
40%
60%
80%
100%
Strongly agree Agree Neutral (no opinion) Disagree Strongly disagree
I get more exercise now that I am a member of Nice Ride Minnesota.
N = 1229
N = 955
Helmet Use with Public Bikesharing
Shaheen et al., 2012
8%12%
8% 10%
62%
0%
10%
20%
30%
40%
50%
60%
70%
Always Most of the time
Sometimes Rarely Never
Montreal
16%20%
14%
50%
-10%
0%
10%
20%
30%
40%
50%
60%
Always Sometimes Rarely Never
Minneapolis-St Paul
Question: How often do you wear a helmet while using Nice Ride?
N = 1232
17% 19% 21%
43%
-10%
0%
10%
20%
30%
40%
50%
60%
Always Most of the time Some of the time Never
Washington, D.C.
N = 5248
11%
18%
11%15%
45%
0%5%
10%15%20%25%30%35%40%45%50%
Always Most of the time
Sometimes Rarely Never
Toronto
Question: How often do you wear a helmet when using BIXI bikes?
N = 842
Question: How often do you wear a helmet when using BIXI bikes?
Question: How often do you wear a helmet when you use Capital Bikeshare?
N = 3291
Shaheen et al., 2012
Summary • IT-based bikesharing, starting in 2007, has undergone rapid growth in North
America since 2009. – Approximately 20 planned and existing launches for 2012
• User survey indicates modal shift away from all other modes towards the use of the bicycle.
– Everyone is driving less, and bicycling more
– Most appear to be walking less, and bicycling more
– Most also appear to be using transit less, and bicycling more
– The dynamics of where and why bikesharing increases transit use and walking (such as is the case in Minneapolis) need to be better understood.
• Modal shift away from transit may have occurred due to transit congestion at peak times and shorter, faster, or more direct routing with bikesharing.
• Helmet use with bikesharing is limited, likely the result of helmet availabilty.
• Early data suggests the bikesharing may have a positive impact on nearby shopping locations.
Acknowledgements • Mineta Transportation Institute,
San Jose State University • California Department of
Transportation • Adam Cohen, Stacey Guzman,
Rachel Whyte, and Cynthia Armour, TSRC, UC Berkeley
• North American public bikesharing organizations
N. American Public Bikesharing Report
transweb.sjsu.edu/project/1029.html
www.its.berkeley.edu/sustainabilitycenter
Bikesharing Impacts Data
(Year) Trips Per
Day KM Per Day CO2 Reduction (Kg Per Day)
BIXI Montreal 2011 20,000 50,000 8,760
Trips Per
Year KM Per Year CO2 Reduction (Kg Per Year)
Boulder B-Cycle 2011 18,500 47,174
Denver B-Cycle 2011 202,731 694,942 280,339
New Balance Hubway (Boston) 2011 140,000
Madison B-Cycle 2011 18,500 46,805
San Antonio B-Cycle 2011 22,709 38,575
Shaheen et al., 2012