The Return of the Bike:
UWEC Bike Rack Assessment Project
December 20, 2012
Introduction
Adam King
Michaela Leach
Taren Leitzke
Welcome
• Class Introduction:
– Name
– Major
• Guest Introduction:
– Name
– Profession/Background/Area of Study
– When was the last time you biked?
Cars, Culture, and Environment
“[To] examine the breadth and depth to which
the car shapes and is shaped by our physical and
social environments.”
Why Bike?
• Cost efficient
• Decreases congestion
• Improves
– Heart health
– Coordination
– Stamina
– Muscle tone
– Air quality
Source: http://www.healthcaremanagementdegree.com/biking-and-health/
Bikes on the Rise
• In the last ten years:
– Bicycle commuting
increased 63% in 70
largest US cities
• 54% of bicycle trips for
transportation
Bikes on the Rise
Why Infrastructure is Important
• 1.5 million bikes stolen
per year
– Lack of proper
infrastructure
• Infrastructure needs to:
– Be visible, accessible and
convenient
– Support the entire frame
of the bike
– Meet space demands
5 E’s of Bicycle Planning and Support
• Engineering
– Bike paths/trail
– BIKE PARKING!!
•
•
•
•
Education
Encouragement
Enforcement
Evaluation and Planning
League of American Bicyclists, http://www.bikeleague.org/programs/bicyclefriendlyamerica/bicyclefriendlyuniversity/bfu_five_e_s.php
Overview of Bike Rack Study
• Purposes:
– Test the feasibility of a campus bike rack
assessment
– Determine the location and usage of bike
racks
– Create a photo-map of bike parking areas
using GPS-labeled pictures and Google
Maps
Methods
David Cifaldi
Justin Kohlbeck
Rachel Olson
Methods: Data collection
• Student teams
• 5 x 75 minute shifts to
capture use during
the day
• 7:30 a.m. – 3:30 p.m.
• Lower campus only
Recorded observations
on data sheet adapted
from University of
Washington bike rack
assessment study
Data collection form
Name: ________________________________________
Shift: ________________________________________
Date
Time
Bike rack
site
number
Total No.
of bike
racks in
area
Bike rack
type:
WB or IU
P or other
Rack
condition
Good
Adequate
Poor
Rack
surface
No.
bike
slots
No. of
bikes
in
slots
No.
bikes
poorly
parked in
rack
No. bikes
tipped/
fallen
over
Number
illegally
parked
bikes (not
in rack)
What are
Illegal
bikes
parked
to?
Observations/notes
Types of Bike Racks
Wave
Inverted U
Grid-type
Post
Bike Rack Surfaces
Concrete
Grass
Brick
Gravel/dirt
Bike Rack Conditions
• Good: usable, little no wear, rusting, or
damage
• Adequate: some rust or damage (e.g. bent
tines) but still usable
• Poor: conditions make bike racks unusable
Counts
• Number of bike racks per site
• Number of parking slots per site
• Number of bikes parked in racks/site
– Number of poorly parked bikes
– Number of tipped bikes
– Number of illegally parked bikes
• Object to which illegally parked bike is parked
Poorly Parked
Illegally Parked
Tipped
Photomapping
• Used GPS camera to photograph bikes and racks at
each site and to link to Google Maps using
latitude/longitude coordinates
• Allows quick link of photo to map to visually compare
bikes and racks at different sites
Photo
+
GPS Camera
UWEC
Google Maps
Data entry and processing
• Each student entered their findings into a
web-based Excel spreadsheet
• The data was reviewed for errors and
inconsistencies between paired observers
Data and Analysis
Kevin Brooks
Lucy Pepin
Megan Place
What we observed:
Bike racks serve different purposes
Commuter racks
in front of Nursing
Storage racks in
front of Putnam Hall
What we observed:
New Davies Inverted-U bike parking:
(1) Aesthetically appealing
(2) Does not visually interfere with newly
landscaped mall
What we observed:
Some parking areas are under-utilized
Underground
library parking
Parking behind
Hibbard
What we observed:
Some parking areas are heavilyutilized or overcrowded.
Library entrance
parking
Schofield parking
What we observed:
Some parking areas are mis-utilized
Library entrance
parking
Long-term storage
under library
Bike parking and use by the numbers
• Number of bike racks: 80
• Number of bike parking spaces: 1549
Percent of bike racks by type
60%
50%
40%
35%
31%
30%
23%
20%
12%
10%
0%
Inverted U
Grid
Post
Wave
Percent bike racks by type and
by parking spaces per rack type
60%
51%
50%
40%
35%
31%
30%
% rack
26%
23%
20%
14%
12%
8%
10%
0%
Inverted U
Grid
Post
Wave
% slots
Rating of bike rack conditions (%)
31%
Good
Adequate
69%
Percent of bike rack parking by
surface material
8%
4%
Concrete
Brick
11%
Dirt/gravel
Grass
77%
Mean number of bikes per shift
800
659
640
639
590
Number of Bikes
600
498
400
200
0
7:45-9:00
9:15-10:30
10:45-12:15
Shift
12:30-1:45
2:00-3:15
Mean number of bikes and usage rate
for all racks per shift
800
659
640
639
590
40%
498
43%
41%
600
41%
38%
400
32%
20%
200
0%
0
7:45-9:00
9:15-10:30
10:45-12:15
Shift
12:30-1:45
2:00-3:15
Number of bikes
Usage Rate (#bikes/#parking slots)
60%
15/115
11/111 Library (UB)
11/111
15/115 Schofield
High use
High parking
15/115
11/111 Library (UB)
11/111
15/115 Schofield
Low use
Low parking
15/115
11/111 Library (UB)
11/111
15/115 Schofield
High Use
Low parking
15/115
11/111 Library (UB)
11/111
15/115 Schofield
Low Use
High Parking
15/115
11/111 Library (UB)
11/111
15/115 Schofield
Mean number of tipped, poorly or
illegally parked bikes per shift
120
102
Number of bikes
100
89
80
80
80
74
60
40
7:45-9:00
9:15-10:30
10:45-12:15
12:30-1:45
2:00-3:15
Percent of total illegally and poorly parked
bikes and tipped bikes by rack type
100%
80%
72%
60%
40%
18%
20%
7%
3%
0%
Grid
Wave
Post
Inverted-U
Percent of illegally and poorly parked bikes and tipped
bikes by rack type and parking spaces per rack type
100%
80%
72%
60%
Rack type
51%
Slots per rack
type
40%
26%
18%
20%
7%
14%
8%
3%
0%
Grid
Wave
Post
Inverted-U
photo map
Implications, Recommendations, and Limitations
Erin Hanegraaf
Phil Schumacher
Chris Reinoos
A practical assessment approach
• Data collection is “doable” in a relatively short
amount of time
• Additional training and a published guide can
improve reliability
• Real data from real users
– Prevents unsupported speculation about bike
parking
• Can track changes in bike travel over time
based on bike parking
Recommendation #1
• Facilities staff should conduct bike rack
assessment two times every year
– ½ day in early fall (10AM-2PM)
– ½ day in late spring (10AM-2PM)
– Choose good weather and high use times to
ensure measurement of peak use
Rack type matters
• Larger proportion of illegally or poorly parked
bikes and tipped bikes occur in grid-type bike
rack
• In areas with multiple rack types, Inverted-U’s
appear to be preferred
Recommendation # 2
• Consider purchasing more rack types that
protect bikes from tipping or being stolen
• Smaller strategically placed sets of racks may
meet biker needs without impairing campus
aesthetics
– Inverted U’s easily accommodate this design
Signage and biker behaviors
• Few areas on lower campus provide bike rack
signage, specifically
– No updated bike rack signs or maps are available
to indicate where other racks are located
• This could reduce illegal parking and highlight available
parking capacity
– No signage exists to explain how to properly use
the various types of bike racks
• This could also reduce illegal or poor parking practices,
as well as reduce bike loss and damage
Recommendation #3
• Convene a campus committee or work with
the current campus bicycle committee to
design and implement updated signage
throughout campus
• Include educational information about proper
use of bike racks
• Determine potential funding sources for
signage
– Facilities, Student Office for Sustainability, etc.
Rack demand and usage
• Methods allowed identification of over- and
under-utilized parking
• Identification of poorly or illegally parked and
tipped bikes—areas where educational
signage could help
• Actual behaviors of bikers could inform
strategic location for future racks, rack types,
and signage
Study limitations
• Data were collected during a single day
• Study was conducted during cooler weather in
late fall—likely missed high use time
• Bike rack use was obstructed by campus
construction
• Bikers were not yet aware of newer racks
(such as inverted U’s between Phillips and
Davies)
Inter-observer variability
• Variability in counts among paired observers
indicates that reliability of the assessment
survey needs to be improved
– Highest variability occurred when counting poorly
parked versus tipped bikes
Study limitations
• Due to class time constraints, data were not
collected across the entire campus
– Omitted across the river and upper campus
Acknowledgements
• University Campus Community
• Bob Eierman, Director, Center for Excellence in
Teaching and Learning, Eau Claire Bicycle
Pedestrian Advisory Committee
• Martin Goettl, Geospatial Technology
Facilitator
• Dani Bronshteyn, Honors TA
Thank you!!
Questions