Post on 10-Jul-2015
We are Traffic: Creating Robust Bicycle and Pedestrian Count Programs
Krista Nordback, Ph.D., P.E.Oregon Transportation Research and Education Consortium
(OTREC)
Overview
• Introduction
• Traffic Monitoring Programs
• Non-Motorized Count Programs
• Conclusions & Recommendations
INTRODUCTION
Why measure walking & biking?
Why measure walking & biking?
Why measure walking & biking?
• Funding & policy decisions
• To show change over time
• Facility design
• Planning (short-term, long-term, regional…)
• Economic impact
• Public health
• Safety
How many bike and walk?
• Surveys
– National
– Regional
– Local
• Counts
– Permanent
– Short duration
What good are counts?
• Funding!
• Facility Level– Change Over Time
– Planning and Design
– Safety Analysis
• Validate Regional Models
• Prioritize Projects
• Bicycle Miles Traveled (BMT)
Signal Timing
Vehicle Delay
Kothuri, S. M., Reynolds, T., Monsere, C. M., & Koonce, P. (2013). Testing Strategies to Reduce Pedestrian Delay at Signalized Intersections. A Pilot Study in Portland, OR. Paper presented at the 92nd Annual Meeting of the Transportation Research Board, Washington, D.C.
Signal Timing
Vehicle Delay
Kothuri, S. M., Reynolds, T., Monsere, C. M., & Koonce, P. (2013). Testing Strategies to Reduce Pedestrian Delay at Signalized Intersections. A Pilot Study in Portland, OR. Paper presented at the 92nd Annual Meeting of the Transportation Research Board, Washington, D.C.
Pedestrian
What?
People actually bike here?
Yes! 200 per day
What?People actually walk here?
Yes!
400 per day
TRAFFIC MONITORINGPROGRAMS
State Traffic Monitoring
Metro Count Accessed 6/13/13 http://mtehelp.tech-metrocount.com/article.aspx?key=mc5805
Commonly inductive loops
Permanent Counters
Short Duration Counters
Commonly pneumatic tubes
Colorado’s Permanent Counters
Annual Average Daily Traffic (AADT)
Colorado’s Short Duration Traffic Counts
CDOT OTIS Accessed 6/18/13 http://dtdapps.coloradodot.info/Otis/HighwayData#/ui/0/1/criteria/~/184.667/210.864
AADT
AADT
AADT
AADT
Use AADT to Estimate VMT
Sum (AADT X Segment Length) over network to compute Vehicle Miles Traveled (VMT)
COLORADO HIGHWAYS
Can we apply these methods to biking and
walking?
AADB: Annual Average Daily Bicyclists
AADT for bicyclists!
Traffic Monitoring Guide 2013:
Chapter 4 for Non-motorized Traffic
NON-MOTORIZED COUNT PROGRAMS
The TMG 2013 Approach
The TMG 2013 Approach
National Bicycle and Pedestrian Documentation Project
Manual Counts:
2 hours
5 to 7pm
Tues, Wed, or Thurs in
mid-September
http://bikepeddocumentation.org/
Passive Infrared Counters
Inductive loop counters in bike lanes
Combined Bicycle and Pedestrian Continuous Counter
The TMG 2013 Approach
Permanent Count
Program
Permanent Count
Program
Geographic/Climate Zones
Urban vs. Rural
Annual Average Daily Bicyclists (AADB)
Volume
Categories
0 500 1,000
AADB
Co
nti
nu
ou
s C
ou
nt
Stat
ion
s
Medium
High
600
200
Low
Traffic Monitoring Guide 2013 Update, Chapter 4.
Permanent Count
Program
Daily Patterns
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
% o
f A
AD
B
Colorado Example (Bikes only)
Hourly Commute Pattern
0%
5%
10%
15%
20%
25%1
2:0
0 A
M
1:0
0 A
M
2:0
0 A
M
3:0
0 A
M
4:0
0 A
M
5:0
0 A
M
6:0
0 A
M
7:0
0 A
M
8:0
0 A
M
9:0
0 A
M
10
:00
AM
11
:00
AM
12
:00
PM
1:0
0 P
M
2:0
0 P
M
3:0
0 P
M
4:0
0 P
M
5:0
0 P
M
6:0
0 P
M
7:0
0 P
M
8:0
0 P
M
9:0
0 P
M
10
:00
PM
11
:00
PM
% o
f A
AD
B
City of Boulder Example (Bikes only)
Hourly Non-commute Pattern
0
50
100
150
200
250
300
350
400
0:0
0
1:0
0
2:0
0
3:0
0
4:0
0
5:0
0
6:0
0
7:0
0
8:0
0
9:0
0
10
:00
11
:00
12
:00
13
:00
14
:00
15
:00
16
:00
17
:00
18
:00
19
:00
20
:00
21
:00
22
:00
23
:00
Ave
rage
Ho
url
y V
olu
me
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Source: Pam Johnson, PSU
Permanent Count
Program
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns 2 Weekly Patterns
Commute
Non-Commute
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns 2 Weekly Patterns
Commute
Non-Commute
2 Annual Patterns
Commute
Non-Commute
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns 2 Weekly Patterns
Commute
Non-Commute
2 Annual Patterns
Commute
Non-Commute
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns 2 Weekly Patterns
Commute
Non-Commute
2 Annual Patterns
Commute
Non-Commute
12 Possible groups
Commute
Non-Commute
In Between
3 Daily Patterns 2 Weekly Patterns
Commute
Non-Commute
2 Annual Patterns
Commute
Non-Commute
Commute
Urban PlainsNon-commute
Mountain Non-commuteHigher
Week-ends?
Rural MtnTrail?
Weekly Pattern
Location
YesYes
NoNo
Permanent Count
Program
Factoring Method
Adapted from Traffic Monitoring Guide
AADB = Cknown* D * M
Cknown = 24-hour count
D = Daily Factor
M = Monthly Factor
Factoring Method
Adapted from Traffic Monitoring Guide
AADB = Cknown* D * M
Cknown = 24-hour count
D = Daily Factor
M = Monthly Factor
Monthly Factor
M = AADB
MADB
where
MADB = Ave daily bike count in that month
Monthly Factor
M = AADB
MADB
where
MADB = Ave daily bike count in that month
June
= 5001,000
Monthly Factor
M = AADB
MADB
where
MADB = Ave daily bike count in that month
June
= 5001,000
= 0.5
Monthly Factor
M = AADB
MADB
where
MADB = Ave daily bike count in that month
June
= 5001,000
= 0.5
Daily counts in June are twice AADB.
Groups:
MountainNon-
Commute
Front RangeNon-
Commute Commute
January 3.9 1.5
February 3.2 2.0
March 1.3 1.2
April 2.2 1.1 1.1
May 1.0 0.8 0.9
June 0.5 0.8 0.7
July 0.4 0.8 0.8
August 0.5 0.7 0.7
September 0.7 0.8 0.8
October 1.7 1.0 1.0
November 1.5 1.4
December 2.5 2.3
Colorado Monthly Factors
Permanent Count
Program
How many counters/group?
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 1011121314
Pre
cisi
on
of
Mo
nth
ly F
acto
rs
Number of Counters
Non-Commute Factors
Commute Counters
Average
Permanent Count
Program
The TMG 2013 Approach
The TMG 2013 Approach
The TMG 2013 Approach
Short Duration
Count Program
Short Duration
Count Program
Turning Movement Counts
Segment Count
A
B
Short Duration Counters• Pedestrian
• BicycleInfraredManual
Manual Pneumatic Tube Counters
Traffic Monitoring Guide 2013 Update, Chapter 4.
Short Duration
Count Program
Potential Selection Criteria
• Variety of facility types
Path On-street
Potential Selection Criteria
• Variety of land uses– Central business district
– Residential
– School/University
• Technology related criteria
Short Duration
Count Program
Count Duration
0%
10%
20%
30%
40%
50%
60%
70%
0 200 400 600
% E
rro
r o
f A
AD
B E
stim
ates
Count Duration (hours)
Count Duration
0%
10%
20%
30%
40%
50%
60%
70%
0 200 400 600
% E
rro
r o
f A
AD
B E
stim
ates
Count Duration (hours)
1 week
Short Duration
Count Program
Schedule Counts
0%
20%
40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12
Ab
solu
te %
Err
or
in A
AD
B
Esti
mat
es
Month
Schedule Counts
0%
20%
40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12
Ab
solu
te %
Err
or
in A
AD
T Es
tim
ate
Month
May to October bestfor Midwestern Climate
The TMG 2013 Approach
Factoring Method
Adapted from Traffic Monitoring Guide
AADB = Cknown* D * M
Cknown = 24-hour count
D = Daily Factor
M = Monthly Factor
AADB
VMT for
bicycles
CONCLUSIONS & RECOMMENDATIONS
Summary
• Traffic Monitoring Guide Approach:
– Permanent Count Program
– Short Duration Count Program
– Compute AADT for Bikes and Pedestrians
Recommendations
• Both permanent and short duration count programs are needed.
• Continuous counters are needed!
• Prefer 1 week short count
• Short duration counts in high volume months
– May to October (Midwestern climates)
• Integrate bike/ped counts into traffic data for preservation and access
Balance Permanent and Short Duration Programs
PERMANENT
COUNT
PROGRAM
SHORT
DURATION
COUNT
PROGRAM
Iterative Process
Iterative Process
Example
1st Year
PERMANENT
COUNT
PROGRAM
SHORT
DURATION
COUNT
PROGRAM
1 Permanent Counter 20 Manual Counts
2nd Year
PERMANENT
COUNT
PROGRAM
SHORT
DURATION
COUNT
PROGRAM
1 Permanent Counter 24 Automated Short Duration Sites(one week per site)
Rotate 1 counter all summer
3rd Year
PERMANENT
COUNT
PROGRAM
SHORT DURATION
COUNT PROGRAM
5 Permanent Counters 48 Automated Short Duration Sites(one week per site)
Rotate 2 counters all summer
4th Year
PERMANENT
COUNT
PROGRAM
SHORT DURATION COUNT
PROGRAM
6 Permanent Counters 120 Automated Short Duration Sites(one week per site)
Rotate 5 counters all summer
10th Year
PERMANENT COUNT
PROGRAM
SHORT DURATION COUNT
PROGRAM
12 Permanent Counters 720 Automated Short Duration Sites(one week per site) on 3 year rotation
Rotate 10 counters all summer on 3 year rotation
On-going Work
• Colorado, Vermont, Minnesota, Oregon, North Carolina, Washington State DOT’s are developing programs.
• TRB Bike/Ped Data Subcommittee https://sites.google.com/site/bikepeddata/home
• FHWA to include bike/ped counts in Travel Monitoring Analysis System (TMAS)
• NCHRP 07-19: Bike/Ped Data Methods & Technologies• Google Group for future discussion!• OTREC’s Bike/Ped Data Archive
TRB Bike/Ped Data Subcommittee
Questions?
Krista Nordback
Nordback@pdx.edu
503-725-2897
Guide to Bicycle & Pedestrian Count Programshttp://www.pdx.edu/ibpi/count
EXTRA SLIDES
Why daily counts?
0
10
20
30
40
50
60
70A
vera
ge H
ou
rly
Co
un
t
Why daily counts?
0
10
20
30
40
50
60
70A
vera
ge H
ou
rly
Co
un
t
Why daily counts?
0
10
20
30
40
50
60
70A
vera
ge H
ou
rly
Co
un
t
Why annual average?
0
200
400
600
800
1000
1200
1 2 3 4 5 6 7 8 9 10 11 12
Ave
rage
Dai
ly C
ou
nt
Month
Why annual average?
0
200
400
600
800
1000
1200
1 2 3 4 5 6 7 8 9 10 11 12
Ave
rage
Dai
ly C
ou
nt
Month
635
Nosal, T., L. Miranda-Moreno, et al. (2014). Incorporating weather: a comparative analysis of Average Annual Daily Bicyclist estimation methods. 93rd Annual Meeting of the Transportation Research Board. Washington, D.C., National Academies.
Hankey, S., G. Lindsey, et al. (2014). Day-of-Year Scaling Factors and Design Considerations for Non-motorized Traffic Monitoring Programs. 93rd Annual Meeting of the Transportation Research Board. Washington, D.C., National Academies.
The Problem
Bicycle counts live here Some bicycle
counts live here.and die here.
TMAS
No bicycle counts live here.
The Solution
bike counts
TMAS
bike counts
CDOT Continuous Counters
All Colorado Continuous Counters
• 45 stations with enough data to study (2010-2012)
– 21 bicyclist only count stations
– 24 bicyclists and pedestrians combined stations
Denver Metro Area
Short-term Counters
About 6 portable infrared counters:
• Rotated around the state
– By request
– About 30 sites
• Each site over 1 week, usually at least one month
Colorado Count Stations
Bicycle Only Bicycle & Pedestrian
All
Number of Stations 21 24 45
Average AADT 401 182 284
Rural 10% 88% 51%
Mountains 10% 50% 31%
On Paths 67% 100% 84%
Other Suggested Groupings
• Turner, TTI: 3 factor groups
– Commute
– In between
– Non-Commute–
• Miranda-Moreno: 4 factor groups
– Commute
– 2 groups in between
– Non-Commute
Inductive loop counters on paths
Inductive Loops
Inductive loop counters on-street
Inductive loop counters in vehicle lane
Piezoelectric Bike Counters
Video Detection
Pneumatic Tube Counting
On Path
On Road
National Bicycle and Pedestrian Documentation Project
http://bikepeddocumentation.org/downloads/
There’s an app for that!
Manual counting on your smart phone!
by Thomas Götschi
National Bicycle and Pedestrian Documentation Project
http://bikepeddocumentation.org/downloads/
Portland Volunteer
Count Form
Bike/Ped Daily Factors
0%
20%
40%
60%
80%
100%
120%
140%
160%
Pe
rce
nt
of
AA
DT Group 1
Group 2
Group 3
Bike/Ped and Motorists Factors
0%
20%
40%
60%
80%
100%
120%
140%
160%
Pe
rce
nt
of
AA
DT Group 1
Group 2
Group 3
CDOT Group 3Recreational Motorists
Bike/Ped and Motorist Factors
0%
50%
100%
150%
200%
250%
300%Ja
nu
ary
Feb
ruar
y
Mar
ch
Ap
ril
May
Jun
e
July
Au
gust
Sep
tem
…
Oct
ob
er
No
vem
b…
Dec
emb
…
Pe
rce
nt
of
AA
DT
Group 1
Group 2
Group 3
CDOT Group 3Recreational Motorists
Daily Patterns for Bike/Ped
0%
50%
100%
150%
200%
250%
Pe
rce
nt
of
AA
DT
Monthly Patterns for Bike Only
0%50%
100%150%200%250%300%350%400%450%500%
0 2 4 6 8 10 12
Pe
rce
nt
of
AA
DT
Month
Monthly Pattern
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
1 2 3 4 5 6 7 8 9 10 11 12
% o
f A
AD
BP
Month
With Outliers removedDillon Dam Path
Four Mile
Officers Gulch
Swan Mt
Arbaney Kittle
EmmaRGT
EofAspen
HunterCrk
WoodyCrk
Dawson Butte
Glendale
Greenland
Hidden Mesa
Spruce Meadows
Spruce Mt
Rock Creek
CCHolly-2011
KC470
Broomfield Combo
Colorado Example (Bikes and Peds combined)
Hourly Pattern
0%
5%
10%
15%
20%
25%
% o
f A
AD
B
Arap38thArapahoe2BdwyNsideBdwySsideBldrCrkEsideBldrCrkEside2BldrCrkWsideBldrCrkWside2BrdwyBwyTmesaCentennialFoothillsFoothills2FthlsNECorFthlsSECorPrl55thNPrl55thSPrlPkwySECorPrlPkwySWCorSkunk
City of Boulder Example (Bikes only)
Bike/Ped Factors
0%
50%
100%
150%
200%
250%
300%Ja
nu
ary
Feb
ruar
y
Mar
ch
Ap
ril
May
Jun
e
July
Au
gust
Sep
tem
…
Oct
ob
er
No
vem
b…
Dec
emb
…
Pe
rce
nt
of
AA
DT
Group 1
Group 2
Group 3
Factor Method
• Adapted from Traffic Monitoring Guide
AADB = Cknown* H * D * M
Cknown = known manual count for one hour
H = Hourly Factor
D = Daily Factor
M = Monthly Factor
3 Steps to Estimate AADB
1. Collect continuous counts
2. Compute factors
3. Collect short duration counts
• I know AADB at 25 continuous count stations.
Compute AADB
Motor Vehicle Count
Example
Iowa State University http://www.ctre.iastate.edu/pubs/traffichandbook/3trafficcounts.pdf
COUNTING TECHNOLOGIES
Permanent Counters• Pedestrian
• Bicycle
InfraredVideo Image Recognition
Radar
Pressure Sensor
Inductive Loop Video Detection
Video Image Recognition
Microwave
Magnetometers
Pedestrian Counts• Permanent: Hourly Counts 24/7
• Short Duration: One Hour to One Month
InfraredManual
InfraredVideo Image Recognition
Radar
Pressure Sensor
Bicycle Counts• Permanent: Hourly Counts 24/7
• Short Duration: One Hour to One MonthInductive Loop
Manual
Video Detection
Pneumatic Tube Counters
Video Image Recognition
Microwave
Magnetometers
NCHRP 07-19: Testing accuracy of existing bike/ped count technologies.
Traffic Monitoring Guide. 2013, FHWA: Washington, DC.
Manual Counts• Volunteer vs. Paid Staff
• Paper vs. Electronic iPhone App
• Screenline vs. Intersection Turning Movement Count
• On-site vs. Video watching in office
by Thomas Götschi
Passive Infrared Counters
Traffic Monitoring Guide. 2013, FHWA: Washington, DC.
Active Infrared
Traffic Monitoring Guide. 2013, FHWA: Washington, DC.
Pressure Sensors
Jean-Francois Rheault, Eco CounterTraffic Monitoring Guide. 2013, FHWA: Washington, DC.
Video Image Processing
Traffic Monitoring Guide. 2013, FHWA: Washington, DC.
Source: Elizabeth Stolz, Sprinkle Consulting