We Are Traffic: Creating Robust Bicycle and Pedestrian Count Programs (4-14)

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Information about We Are Traffic: Creating Robust Bicycle and Pedestrian Count Programs...
Education

Published on April 21, 2014

Author: otrec

Source: slideshare.net

Description

**Revised thanks to participant feedback**
As agencies looking to improve bicycle and pedestrian infrastructure have learned, it doesn’t count if it’s not counted. Counting provides information on the level of intersections, paths and roadways—data already available for motor vehicles but lacking for non-motorized travelers. For the first time, Federal Highway Administration’s Traffic Monitoring Guide now includes a chapter detailing how to monitor bicycle and pedestrian traffic. These slides explain how to create a robust bicycle and pedestrian count program based on the new guidance. Agencies that show clear evidence of use are more likely to receive funding for projects, so join us and learn how to improve your existing count program or create a new one. Webinar youtube video can be seen at: http://youtu.be/PXzcJRvwPmc

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 MONITORING PROGRAMS

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

Permanent Counters • Pedestrian • Bicycle Infrared Video Image Recognition Radar Pressure Sensor Inductive Loop Video Detection Video Image Recognition Microwave Magnetometers

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 ContinuousCountStations 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% %ofAADB Colorado Example (Bikes only)

Hourly Commute Pattern 0% 5% 10% 15% 20% 25% 12:00AM 1:00AM 2:00AM 3:00AM 4:00AM 5:00AM 6:00AM 7:00AM 8:00AM 9:00AM 10:00AM 11:00AM 12:00PM 1:00PM 2:00PM 3:00PM 4:00PM 5:00PM 6:00PM 7:00PM 8:00PM 9:00PM 10:00PM 11:00PM %ofAADB City of Boulder Example (Bikes only)

Hourly Non-commute Pattern 0 50 100 150 200 250 300 350 400 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 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 AverageHourlyVolume 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 Plains Non-commute Mountain Non-commuteHigher Week- ends? Rural Mtn Trail? Weekly Pattern Location Yes Yes 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 = 500 1,000

Monthly Factor M = AADB MADB where MADB = Ave daily bike count in that month June = 500 1,000 = 0.5

Monthly Factor M = AADB MADB where MADB = Ave daily bike count in that month June = 500 1,000 = 0.5 Daily counts in June are twice AADB.

Groups: Mountain Non- Commute Front Range Non- 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 PrecisionofMonthlyFactors 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 • Bicycle InfraredManual 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 %ErrorofAADBEstimates Count Duration (hours)

Count Duration 0% 10% 20% 30% 40% 50% 60% 70% 0 200 400 600 %ErrorofAADBEstimates 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 Absolute%ErrorinAADB Estimates Month

Schedule Counts 0% 20% 40% 60% 80% 100% 1 2 3 4 5 6 7 8 9 10 11 12 Absolute%ErrorinAADT Estimate Month May to October best for 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

On-line Guide 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 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 Count Sites

2nd Year PERMANENT COUNT PROGRAM SHORT DURATION COUNT PROGRAM 1 Permanent Counter 12 Automated Short Duration Sites (one week per site + transfer time) Rotate 1 counter all summer

3rd Year PERMANENT COUNT PROGRAM SHORT DURATION COUNT PROGRAM 5 Permanent Counters 24 Automated Short Duration Sites (one week per site + transfer time) Rotate 2 counters all summer

4th Year PERMANENT COUNT PROGRAM SHORT DURATION COUNT PROGRAM 6 Permanent Counters 60 Automated Short Duration Sites (one week per site + transfer time) Rotate 5 counters all summer

10th Year PERMANENT COUNT PROGRAM SHORT DURATION COUNT PROGRAM 14 Permanent Counters 360 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 Programs http://www.pdx.edu/ibpi/count

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