Automated Bicycle Data Collection: A Case Study from

Portland, ORWestern District Annual ITE Meeting

June 26th, 2012

Presenter:Sirisha Kothuri

skothuri@pdx.edu

Authors:

Sirisha Kothuri

Titus Reynolds

Christopher Monsere

Peter Koonce

Automated Bicycle Data Collection

1

Outline

Introduction Study Area Bicycle Counts Bicycle Delay Summary Next Steps

Automated Bicycle Data Collection

2

Automated Bicycle Data Collection

3Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Our intentions are to be assustainable a city as possible.That means socially, that means environmentally and that means economically. The bike is great on all three of those factors. You just can’t get a better transportation return on your investment than you get with promoting bicycling.

– Mayor Sam Adams

Source: P Koonce

Portland’s Bicycle NetworkAutomated Bicycle Data Collection

4Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

2010 Bicycle Network Bicycle boulevards Bicycle lanes Off street paths Total system (314 mi)

Source: R Geller

Portland’s Bicycle NetworkAutomated Bicycle Data Collection

5Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Source: R Geller

Bridge Bicycle Traffic

Bikeway Miles

Increasing Bicycle UseCyclistsPer Day

BikewayMiles

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

0

2,500

5,000

7,500

10,000

12,500

15,000

17,500

0

50

100

150

200

250

300

350

Bridge Bicycle Traffi c2,850 3,555 3,885 3,830 3,207 4,520 5,225 5,690 5,910 6,015 7,686 8,250 8,562 8,875 10,192 12,046 14,563 16,711

Bikeway Miles 79 84.5 87 104 114 144 167 183 214 222.5 236 253 256 262 265.5 269 272 274

2008:~300 miles of bikeways

16,711 daily trips

1996:~150 miles of bikeways

4,520 daily trips

2004:SmartTrips Program expands

Where are we going?Automated Bicycle Data Collection

6Introduction | Study Area | Bicycle Data | Pedestrian Data | Summary | Next Steps

Why is this important?

Bicycle Data Gaps/Deficiencies in data Evaluation of system performance Current demand estimation Future infrastructure and operational needs Prioritize investments Improve safety

Automated Bicycle Data Collection

7Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Objective

Utilize existing infrastructure to develop a long term monitoring and collection system to monitor bicycle activity.

Automated Bicycle Data Collection

8Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Study AreaAutomated Bicycle Data Collection

9Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

I-205

I-5

I-84US-26

DowntownOR -217

Bicycle Data Bicycle Counts Bicycle Delay

Pedestrian Data Push button actuations Pedestrian Delay

Bicycle DataAutomated Bicycle Data Collection

10Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Single inductive loops Advance loop counts Criteria for counts

Bicycle lane Advance loop in bike

lane Individual loop wire Communication

Automated Bicycle Data Collection

11Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Count Verification

Outbound Loop

Inbound Loop

Video and loop counts Underestimation of

loop counts

Automated Bicycle Data Collection

12Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Daily Trend

Automated Bicycle Data Collection

13Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Weekday Trends

Automated Bicycle Data Collection

14Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Bicycle Delay

Active at one intersection Internal logic commands Latch is set -

Bike is detected Light status ≠ green

Latch is released Light status = green

Delay = Duration of latch Maximum delay per cycle

Automated Bicycle Data Collection

15Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Bicycle Delay

0

5

10

15

20

1:00 4:00 7:00 10:00 13:00 16:00 19:00 22:00

Freq

uenc

y

Time

0-2021-40>40

Delay Reduction Strategies Coordinated Free Increase in permissive length

PORTAL

Regional data archive Data currently archived:

Freeway loop detector Weather Incidents Bluetooth Bike and Ped Arterial

Automated Bicycle Data Collection

16Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

http://portal.its.pdx.edu/

Conclusions

Growing need for bicycle data Operations Planning

Bicycle counts from inductive loops Cost effective Potential for undercounting Affected by placement, sensitivity and

calibration

Automated Bicycle Data Collection

17Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Next Steps

Expansion and verification of counts Expansion of bicycle delay to other

intersections Optimizing signal timing based on delay

Automated Bicycle Data Collection

18Introduction | Study Area | Bicycle Counts | Bicycle Delay | Summary | Next Steps

Thank you!

Sirisha Kothuri

skothuri@pdx.edu

Titus Reynolds

titus.reynolds@portland oregon.gov

Christopher Monsere

monsere@pdx.edu

Peter Koonce

peter.koonce@portlandoregon.gov

Automated Bicycle Data Collection

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http://portal.its.pdx.edu/