air quality and multimodal evaluation of an adaptive traffic signal system: a case study on powell...

Air Quality and Multimodal Evaluation of an Adaptive Traffic Signal System: a case study on Powell Boulevard (Portland, Oregon)

Courtney SlavinDr. Miguel FigliozziWestern District ITE ConferenceSanta Barbara, CATuesday, June 26th, 2012

Outline• Objective• Air Pollution• Powell Boulevard Background• Adaptive Traffic Signal Control• Data Collection• Analysis • Conclusions• Future Work

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Objective• Is air quality affected by traffic signal

timing?• What factors are significantly contributing

to air pollution?

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Air Pollution• Regulated by US EPA (Environmental Protection

Agency)• NAAQS (National Ambient Air Quality

Standards)– Carbon monoxide– Particulate matter– Nitrogen oxide– Sulfur oxide– Smog– Lead

http://www.epa.gov/air/urbanair/ 4

Carbon Monoxide (CO)• From incomplete combustion of fuel• Reduces amount of oxygen to the body • Health effects: visual impairment, headaches,

reduced work capacity (EPA)

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Particulate Matter (PM)

http://www.epa.gov/airquality/particlepollution/basic.htmlVallero, D. Fundamentals of air pollution. Academic press, 2008. 6

• Made up of acids, organic chemicals, metals, and soil or dust particles

• PM2.5 particles ≤ 2.5 µm in diameter• Regulated

• Ultrafine particles (UFP) ≤ 0.1 µm in diameter• Not regulated

• Smaller sizes travel deeper into lungs• Health effects: asthma, respiratory infections,

cardiovascular disease, chronic bronchitis

http://www.mapquest.com/

Powell Blvd. Background

• Urban commuter arterial in Portland, Oregon

• Connects Portland downtown to Gresham

• High frequency bus route

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Traffic Volumes

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• Peak Hour– Westbound: 1,500 vehicles (7-8 am)– Eastbound: 1,800 vehicles (4-5 pm)

• Daily– Westbound: 19,000 – 22,000 vehicles– Eastbound: 18,000 – 20,000 vehicles– Total: 40,000 vehicles

Adaptive Traffic Signal Control• The City of Portland implemented an adaptive

traffic signal system along Powell Boulevard on October 8th, 2011

• SCATS: Sydney Coordinated Adaptive Traffic System • Developed in Australia• SCATS adjusts cycle length, phase splits, and

offsets to optimize traffic• Maintains the highest acceptable degree of

saturation

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Data CollectionPowell Blvd. & 26th Avenue

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Data Collection

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• Wednesday, October 26th, 2011

• Morning (7-9 am) peak period

• Equipment location:– 3’ from side of bus shelter– 12’ from curb– 5’ height for tubing

• Bus and heavy vehicle presence

Data Collection Setup

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Powell Blvd.

26th

Ave

.Bus Shelter

West

P-Trak: UFPDust Trak: PM2.5 Langan: COHobo Data Logger: Temperature, Humidity

NE Corner

Anemometer: Wind Speed & Direction

NW Corner

SW Corner SE Corner

Traffic Signal Timing Data

• Before SCATS: Time of day plans• After SCATS: Adaptive timing plans

– Detector volumes – Phase timing (start and end time times)– Cycle length

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Phasing Diagram

Powell Blvd.26

th Ave.4

4

6

2

Bus Shelter

1 5

Phase(s) MovementsA 2 & 6 WBTH & EBTHC 2 & 5 WBTH & WBLTE 1 & 6 EBTH & EBLTF 1 & 5 EBLT & WBLTD 4 NBTH & SBTH

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• 3 left turn options depending on demand

Analysis

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• Phasing descriptive statistics• Cycle length comparison

– Adaptive vs. Time of Day• Regression analysis

– Which of the following factors are significant in explaining pollutant levels (UFP, PM2.5 & CO)?

• Traffic signal timing parameters• Traffic volumes• Heavy vehicles• Transit buses

Phasing Descriptive Statistics(in seconds)

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Min Median Mean Standard Deviation Max Frequency TOD

Phase A 56 70 72.05 10.32 120 63 60

Phase C 5 13 12.57 4.19 22 30

20Phase E 9 13 12.63 2.00 15 8

Phase F 10 13 13.42 2.16 20 31

Phase D 12 33 29.05 6.51 33 63 32

Cycle Length 80 116 115.29 14.29 168 63 110

Adaptive vs. Time of Day Cycle Length

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07:00 07:30 08:00 08:30 09:00

80

10

01

20

14

01

60

October 26, 2011

Cyc

le L

en

gth

(se

cs)

Regression Analysis Results – PM2.5

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Parameter % Change per Unit Change in X

% Change per 1% Change in X

% Mean Contribution*

Bus Red Light (secs) 0.50 0.004 0.44

Heavy Vehicle Presence (1 or 0)

8.12 0.002 0.24

Green A (secs)Green E (secs)Green D (secs)

-0.280.490.26

-0.2040.0090.075

-18.490.917.79

Volume/Cycle (vehs) 0.06 0.063 6.45

*Relative to baseline (sum of constant, temperature, and relative humidity

For example: 1 extra second of green time for Phase A reduces PM2.5 by 0.28%.

Conclusions

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• Longer green time on Powell reduces air pollution

• Relative to the baseline atmospheric conditions, the largest mean contributions to in PM2.5 are:– Green A: 19% reduction– Green D: 8% increase– Volume: 7% increase – Heavy vehicles and bus presence are < 1%

Future Work• Include CO2

• Analysis at other two corners of the intersection

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Acknowledgements• Oregon Transportation, Research and Education Consortium

(OTREC)• Peter Koonce & Willie Rotich (City of Portland

Transportation Bureau)• David Crout & Kurtis McCoy (TriMet)• Eric Albright (Portland State University)

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Questions?

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Courtney SlavinGraduate Student and Research Assistant, ITS LABDepartment of Civil & Environmental Engineering Portland State University Phone: 971-237-3049Email: cslavin@pdx.edu

Miguel FigliozziAssociate Professor Department of Civil & Environmental EngineeringPortland State University P.O. Box 751Portland, OR 97207Phone: 503-725-2836 Email: figliozzi@pdx.edu

References• Particulate Matter: Air & Radiation. Six Common Air Pollutants. [Online]

US EPA. [Cited: July 2, 2011.] http://www.epa.gov/air/urbanair/• Vallero, D. Fundamentals of air pollution. Academic press, 2008.• Particulate Matter: Air & Radiation. Basic Information. [Online] US EPA.

[Cited: July 2, 2011.] http://www.epa.gov/oar/particlepollution/basic.html.

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Regression Analysis Results – UFP

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Parameter % Change per Unit Change in X

% Change per 1% Change in X

% Mean Contribution*

Bus Red Light (secs) 0.77 0.007 0.67

Green A (secs)Green C (secs)

-0.260.27

-0.1880.015

-17.161.56

Volume/Cycle (vehs) 0.29 0.279 32.16

*Relative to baseline (sum of constant, temperature, and relative humidity

Regression Analysis Results – CO

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Parameter % Change per Unit Change in X

% Change per 1% Change in X

% Mean Contribution*

Diesel Particulate Filter on Bus (1 or 0)

-11.74 -0.006 -0.61

Heavy Vehicle Presence (1 or 0)

19.57 0.005 0.55

Green A (secs)Green F (secs)Green C (secs)Cycle Length (secs)

-0.33-1.05-0.90-0.47

-0.237-0.070-0.052-0.545

-21.09-6.76-511

-44.08Volume/Cycle (vehs) 0.54 0.519 67.76

*Relative to baseline (sum of constant, temperature, and relative humidity