We Are Traffic - Counting Bikes & Peds

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?


If we don’t count it, it doesn’t count.


• 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 CountersCommonly pneumatic tubes

http://mtehelp.tech-metrocount.com/article.aspx?key=mc5805

http://mtehelp.tech-metrocount.com/article.aspx?key=mc5805

Colorado’s Permanent Counters

Annual Average Daily Traffic (AADT)

PERMANENT COUNT

PROGRAM

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

PERMANENT COUNT PROGRAM

SHORT DURATION

COUNT PROGRAM

AADT


APPLY FACTORS

SHORT DURATION

COUNT PROGRAM

AADT


APPLY FACTORS

SHORT DURATION

COUNT PROGRAM

AADT


APPLY FACTORS

SHORT DURATION

COUNT PROGRAM

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


National Bicycle and Pedestrian Documentation Project

Manual Counts: 2 hours 5 to 7pm Tues, Wed, or Thurs in mid-September

http://bikepeddocumentation.org/

http://bikepeddocumentation.org/

Passive Infrared Counters

Inductive loop counters in bike lanes

Combined Bicycle and Pedestrian Continuous Counter


Permanent Count

Program

Permanent Count

Program

Geographic/Climate Zones

Urban vs. Rural

Annual Average Daily Bicyclists (AADB)

Volume Categories

0 100 200 300 400 500 600 700 800 900

AADB

Conti

nuou

s Co

unt S

tatio

ns Medium

High

600

200

Low

Traffic Monitoring Guide 2013 Update, Chapter 4.

Permanent Count

Program

Daily Patterns

Sunday

Monday

Tuesday

Wednesd

ay

Thursday

Friday

Saturday

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

% o

f AAD

B

Colorado Example (Bikes only)

Hourly Commute Pattern

12:00 AM

1:00 AM

2:00 AM

3:00 AM

4:00 AM

5:00 AM

6:00 AM

7:00 AM

8:00 AM

9:00 AM

10:00 AM

11:00 AM

12:00 PM

1:00 PM

2:00 PM

3:00 PM

4:00 PM

5:00 PM

6:00 PM

7:00 PM

8:00 PM

9:00 PM

10:00 PM

11:00 PM0%

5%

10%

15%

20%

25%

% o

f AAD

B

City of Boulder Example (Bikes only)

Hourly Non-commute Pattern

0:001:00

2:003:00

4:005:00

6:007:00

8:009:00

10:0011:00

12:0013:00

14:0015:00

16:0017:00

18:0019:00

20:0021:00

22:0023:00

0

50

100

150

200

250

300

350

400

JanFebMarAprMayJunJulAugSepOctNovDec

Ave

rage

Hou

rly

Volu

me

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


Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between


Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between


Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

12 Possible groups

Commute

Non-Commute

In Between


Commute

Non-Commute

2 Annual Patterns

Commute

Non-Commute

CommuteCommute

Urban PlainsNon-commuteUrban Plains

Non-commute

Mountain Non-commute

Mountain Non-commuteHigher

Week-ends?

Higher Week-ends?

Rural Mtn Trail?

Rural Mtn Trail?

Weekly PatternWeekly Pattern

LocationLocation

YesYes

NoNo

Permanent Count

Program

Factoring MethodAdapted from Traffic Monitoring Guide

AADB = Cknown* D * M

Cknown = 24-hour count

D = Daily FactorM = Monthly Factor





Monthly Factor

M = AADBMADB

whereMADB = Ave daily bike count in that month

Monthly Factor

M = AADBMADB


June

= 5001,000

Monthly Factor

M = AADBMADB


June

= 5001,000

= 0.5

Monthly Factor

M = AADBMADB


June

= 5001,000

= 0.5

Daily counts in June are twice AADB.

Groups:Mountain

Non-Commute

Front Range Non-

Commute CommuteJanuary 3.9 1.5

February 3.2 2.0March 1.3 1.2April 2.2 1.1 1.1May 1.0 0.8 0.9June 0.5 0.8 0.7July 0.4 0.8 0.8

August 0.5 0.7 0.7September 0.7 0.8 0.8

October 1.7 1.0 1.0November 1.5 1.4December 2.5 2.3

Colorado Monthly Factors

Permanent Count

Program

How many counters/group?

0 2 4 6 8 10 12 140%

10%20%30%40%50%60%70%80%90%

100%

Non-Commute Factors

Commute Counters

Average

Number of Counters

Prec

isio

n of

Mon

thly

Fac

tors

Permanent Count

Program


Time


Time

Space


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

0 100 200 300 400 500 600 7000%

10%

20%

30%

40%

50%

60%

70%

Count Duration (hours)

% E

rror

of A

AD

B Es

timat

es

Count Duration

0 100 200 300 400 500 600 7000%

10%

20%

30%

40%

50%

60%

70%

Count Duration (hours)

% E

rror

of A

AD

B Es

timat

es

1 week

Short Duration

Count Program

Schedule Counts

1 2 3 4 5 6 7 8 9 10 11 120%

10%20%30%40%50%60%70%80%90%

100%

Month

Abso

lute

% E

rror

in A

ADB

Estim

ates

Schedule Counts

1 2 3 4 5 6 7 8 9 10 11 120%

10%20%30%40%50%60%70%80%90%

100%

Month

Abso

lute

% E

rror

in A

ADT

Estim

ate

May to October bestfor Midwestern Climate






AADB

VMT for

bicycles

CONCLUSIONS & RECOMMENDATIONS

Summary

• Traffic Monitoring Guide Approach:– Permanent Count

Program– Short Duration Count

Program– Compute AADT for Bikes

and Pedestrians

On-line Guide

www.pdx.edu/ibpi/count

http://www.pdx.edu/ibpi/count

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


SHORT DURATION

COUNT PROGRAM

Iterative Process

Iterative Process

Example

1st Year


SHORT DURATION

COUNT PROGRAM

1 Permanent Counter 20 Manual Counts

2nd Year


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


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

https://sites.google.com/site/bikepeddata/home



TRB Bike/Ped Data Subcommittee

Questions?Krista Nordback

[email protected]

Guide to Bicycle & Pedestrian Count Programshttp://www.pdx.edu/ibpi/count

mailto:[email protected]



EXTRA SLIDES

Why daily counts?

12:00 AM

2:00 AM

4:00 AM

6:00 AM

8:00 AM

10:00 AM

12:00 PM

2:00 PM

4:00 PM

6:00 PM

8:00 PM

10:00 PM0

10

20

30

40

50

60

70Av

erag

e H

ourl

y Co

unt

Why daily counts?

12:00 AM

2:00 AM

4:00 AM

6:00 AM

8:00 AM

10:00 AM

12:00 PM

2:00 PM

4:00 PM

6:00 PM

8:00 PM

10:00 PM0

10

20

30

40

50

60

70Av

erag

e H

ourl

y Co

unt

Why daily counts?

12:00 AM

2:00 AM

4:00 AM

6:00 AM

8:00 AM

10:00 AM

12:00 PM

2:00 PM

4:00 PM

6:00 PM

8:00 PM

10:00 PM0

10

20

30

40

50

60

70Av

erag

e H

ourl

y Co

unt

Why annual average?

1 2 3 4 5 6 7 8 9 10 11 120

200

400

600

800

1000

1200

Month

Aver

age

Dai

ly C

ount

Why annual average?

1 2 3 4 5 6 7 8 9 10 11 120

200

400

600

800

1000

1200

Month

Aver

age

Dai

ly C

ount

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

Cities and Counties

Bicycle counts live here Some bicycle

counts live here.

Federal (FHWA)

and die here.

TMAS

No bicycle counts live here.

State Agencies

The Solution

Cities and Counties

bike counts

Federal (FHWA)

TMAS

State Agencies

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 StationsBicycle Only Bicycle &

PedestrianAll

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


http://bikepeddocumentation.org/downloads/


There’s an app for that!

Manual counting on your smart phone!

by Thomas Götschi




Portland Volunteer

Count Form

Bike/Ped Daily Factors

Sunday

Monday

Tuesday

Wednesd

ay

Thursday

Friday

Saturday

0%20%40%60%80%

100%120%140%160%

Group 1

Group 2

Group 3

Perc

ent o

f AA

DT

Bike/Ped and Motorists Factors

Sunday

Monday

Tuesday

Wednesd

ay

Thursday

Friday

Saturday

0%20%40%60%80%

100%120%140%160%

Group 1Group 2Group 3CDOT Group 3

Perc

ent o

f AA

DT

Recreational Motorists

Bike/Ped and Motorist Factors

January

February

March AprilMay

JuneJuly

August

September

October

November

December

0%

50%

100%

150%

200%

250%

300%

Group 1Group 2Group 3CDOT Group 3

Perc

ent o

f AA

DT

Recreational Motorists

Daily Patterns for Bike/Ped

Sunday

Monday

Tuesday

Wednesd

ay

Thursday

Friday

Saturday

0%

50%

100%

150%

200%

250%

Perc

ent o

f AAD

T

Monthly Patterns for Bike Only

0 2 4 6 8 10 120%

50%100%150%200%250%300%350%400%450%500%

Month

Perc

ent o

f AA

DT

Monthly Pattern

1 2 3 4 5 6 7 8 9 10 11 120%

50%100%150%200%250%300%350%400%450%500%

With Outliers removed Dillon Dam PathFour MileOfficers GulchSwan MtArbaney KittleEmmaRGTEofAspenHunterCrkWoodyCrkDawson ButteGlendaleGreenlandHidden MesaSpruce MeadowsSpruce MtRock CreekCCHolly-2011KC470Broomfield Combo

Month

% o

f AA

DBP

Colorado Example (Bikes and Peds combined)

Hourly Pattern

12:00 AM

2:00 AM

4:00 AM

6:00 AM

8:00 AM

10:00 AM

12:00 PM

2:00 PM

4:00 PM

6:00 PM

8:00 PM

10:00 PM0%

5%

10%

15%

20%

25% Arap38thArapahoe2BdwyNsideBdwySsideBldrCrkEsideBldrCrkEside2BldrCrkWsideBldrCrkWside2BrdwyBwyTmesaCentennialFoothillsFoothills2FthlsNECorFthlsSECorPrl55thNPrl55thSPrlPkwySECorPrlPkwySWCorSkunk

% o

f AAD

B

City of Boulder Example (Bikes only)

Bike/Ped Factors

January

February

March AprilMay

JuneJuly

August

September

October

November

December

0%

50%

100%

150%

200%

250%

300%

Group 1Group 2Group 3

Perc

ent o

f AA

DT

Factor Method• Adapted from Traffic Monitoring Guide

AADB = Cknown* H * D * M

Cknown = known manual count for one hour

H = Hourly FactorD = Daily FactorM = Monthly Factor

3 Steps to Estimate AADB

1. Collect continuous counts2. Compute factors3. Collect short duration counts

• I know AADB at 25 continuous count stations.Contin

uous

Counts

Compute AADB

Motor Vehicle Count

Example

Iowa State University http://www.ctre.iastate.edu/pubs/traffichandbook/3trafficcounts.pdf

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


Active Infrared


Pressure Sensors

Jean-Francois Rheault, Eco CounterTraffic Monitoring Guide. 2013, FHWA: Washington, DC.

Video Image Processing


Source: Elizabeth Stolz, Sprinkle Consulting

Date post:	06-May-2015
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