1 NATMEC 2008 Christopher Monsere Robert L. Bertini, Mathew Berkow, and Michael Wolfe Intelligent...

1NATMEC 2008NATMEC 2008

Christopher Monsere Christopher Monsere Robert L. Bertini, Mathew Berkow, and Michael WolfeRobert L. Bertini, Mathew Berkow, and Michael WolfeIntelligent Transportation Systems LaboratoryIntelligent Transportation Systems LaboratoryMaseeh College of Engineering and Computer ScienceMaseeh College of Engineering and Computer SciencePortland State UniversityPortland State University

Towards Incorporating Arterial Performance Towards Incorporating Arterial Performance Quality in the PORTAL Archived Data User Quality in the PORTAL Archived Data User ServiceService

OutlineOutline

What is PORTAL? Arterial performance Our prototype using:

Existing traffic signal infrastructureProbe (bus) geolocation data

Did it work? Next steps

What is PORTAL? Arterial performance Our prototype using:

Existing traffic signal infrastructureProbe (bus) geolocation data

Did it work? Next steps

PORTAL -- Region’s ADUSPORTAL -- Region’s ADUSPORTAL -- Region’s ADUSPORTAL -- Region’s ADUS

What’s in the PORTAL Database?What’s in the PORTAL Database?

Loop Detector DataLoop Detector Data20 s count, lane occupancy, 20 s count, lane occupancy, speed from 500 detectors speed from 500 detectors

(1.2 mi spacing) (1.2 mi spacing)

Incident DataIncident Data140,000 since 1999140,000 since 1999

Weather DataWeather DataEvery day since 2004Every day since 2004

VMS DataVMS Data19 VMS since 199919 VMS since 1999

DaysDaysSince July 2004Since July 2004About 300 GBAbout 300 GB

4.2 Million Detector 4.2 Million Detector IntervalsIntervals

Bus DataBus Data1 year stop level data1 year stop level data

140,000,000 rows140,000,000 rows

001497

WIM DataWIM Data22 stations since 200522 stations since 2005

30,026,606 trucks30,026,606 trucks

Crash DataCrash DataAll state-reported crashes All state-reported crashes

since 1999 - ~580,000since 1999 - ~580,000

What’s Behind the Scenes?What’s Behind the Scenes?

Database ServerDatabase ServerPostgreSQL Relational Database PostgreSQL Relational Database Management System (RDBMS)Management System (RDBMS)

StorageStorage2 Terabyte Redundant Array 2 Terabyte Redundant Array of Independent Disks (RAID)of Independent Disks (RAID) Web InterfaceWeb Interface

Selected Arterial Performance MeasuresSelected Arterial Performance MeasuresSelected Arterial Performance MeasuresSelected Arterial Performance Measures

TABLE 1 SELECTED ARTERIAL PERFORMANCE MEASURES

Metric Measurement Interval Location Maximum Speed

per Vehicle per Person

per Distance per Time

(cycle, 15 min, hour, day)

per Lane per Lane Group per Approach per Segment per Facility

per Area

Average Speed Speed Indexa Density Running Time Travel Time Travel Time Variance Average Delay Maximum Delay Queue Length Platoon Ratio Number of Stops Signal Failure Duration of Congestion per Day Number of Incidents per Day/Peak Period Duration Incidents per Event Nonrecurring Delay aRatio of average speed to posted speed.

Inspiration – Signal System Data OnlyInspiration – Signal System Data OnlyInspiration – Signal System Data OnlyInspiration – Signal System Data Only

Inspiration – Bus Geolocation Data OnlyInspiration – Bus Geolocation Data OnlyInspiration – Bus Geolocation Data OnlyInspiration – Bus Geolocation Data Only

Powell Blvd.

This Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVLThis Project: Combine Signal and Bus AVL

Past and Ongoing Efforts – Signal DataPast and Ongoing Efforts – Signal DataPast and Ongoing Efforts – Signal DataPast and Ongoing Efforts – Signal Data

Using stop bar detectors to generate Using stop bar detectors to generate an arterial performance mapan arterial performance map Hallenbeck, Ishimaru, Davis, KangHallenbeck, Ishimaru, Davis, Kang LiangLiang

Performance based on summation of Performance based on summation of delay componentsdelay components Liu, MaLiu, Ma Skabardonis, GeroliminisSkabardonis, Geroliminis

Intersection/Signal PerformanceIntersection/Signal Performance Sharma, Bullock, BonnesonSharma, Bullock, Bonneson Smaglik, Bullock, SharmaSmaglik, Bullock, Sharma

Oregon Historical Society

Signal System Data:Signal System Data:Portland’s Portland’s Detection Detection InfrastructureInfrastructure

Data AggregationData AggregationCount Station Count Station

5 min5 minOther Detector Other Detector

15 min15 min7 Day Sample7 Day Sample

Case Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed MapCase Study: Barbur Blvd. Speed Map

SheridanHooker

Hamilton

3rdTerwilligerBertha

I-5 Off-ramp

Park & Ride

Detectors at Barbur and BerthaDetectors at Barbur and BerthaDetectors at Barbur and BerthaDetectors at Barbur and Bertha

5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)5 Minute Speed and Occupancy (at Hamilton)

0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

Occupancy

AM Peak Speed Map From Detector DataAM Peak Speed Map From Detector DataAM Peak Speed Map From Detector DataAM Peak Speed Map From Detector Data

Hamilton

Bertha

Park & Ride

Sheridan

7:00 AM 9:00 AM

Slope =Distance /Time

Signal Data Only SummarySignal Data Only Summary

Point Detection Detector spacing and coverage How to extrapolate measurement to link level?

Very Limited Time Aggregation 5 Minute Won’t Work!

Lack of Access to Real Time Data

Point Detection Detector spacing and coverage How to extrapolate measurement to link level?

Very Limited Time Aggregation 5 Minute Won’t Work!

Lack of Access to Real Time Data

Past and Ongoing Efforts –Bus GeolocationPast and Ongoing Efforts –Bus GeolocationPast and Ongoing Efforts –Bus GeolocationPast and Ongoing Efforts –Bus Geolocation

Buses as probesBuses as probes Bertini & Tantiyanugulchai (2003)Bertini & Tantiyanugulchai (2003) Vandehey, Parks, Koonce & Vandehey, Parks, Koonce &

Bonneson (2006 working paper)Bonneson (2006 working paper) Chakroborty and Kikuchi (2004)Chakroborty and Kikuchi (2004)

Measuring & reporting Measuring & reporting congestioncongestion Hall and Vyas (2000)Hall and Vyas (2000)

Measuring network LOSMeasuring network LOS Uno, Tamura, Iida, Nagahiro and Uno, Tamura, Iida, Nagahiro and

Yamawaki (2007)Yamawaki (2007)

TriMet Archived AVL DataTriMet Archived AVL DataTriMet Archived AVL DataTriMet Archived AVL DataR

9 01NOV2001 8:53:32 8:49:15 8:53:28 285 0 1120 4964 0 0 0 0 0 21 41 10558.58 7644468 676005

9 01NOV2001 8:55:00 8:51:41 8:54:46 285 0 1120 4701 4 0 0 0 1 20 50 15215.05 7649112 676328

9 01NOV2001 8:56:22 8:52:00 8:55:08 285 0 1120 4537 36 3 0 6 0 26 34 15792.35 7649674 676220

Route Number Vehicle Number Service Date Actual Leave Time Scheduled Stop Time Actual Arrive Time Operator ID Direction Trip Number Bus Stop Location

Dwell Time Door Opened Lift Usage Ons & Offs (APCs) Passenger Load Maximum Speed

on Previous Link Distance Longitude Latitude

Powell Blvd. Corridor StudyPowell Blvd. Corridor StudyPowell Blvd. Corridor StudyPowell Blvd. Corridor Study

1:04:00 PM 1:09:00 PM 1:14:00 PMTime

Ross Island

Bridge

Test VehicleBusHypothetical BusPseudo BusModified Pseudo Bus B

1 Year’s Worth of TriMet Data1 Year’s Worth of TriMet Data

92 Bus Line 7,600 Stop Locations 273,469 Runs 140,751,486 Stops 50 Gigabytes of Data Extensive Network

Coverage Opportunity to

Evaluate Multiple Routes on Same Arterial

92 Bus Line 7,600 Stop Locations 273,469 Runs 140,751,486 Stops 50 Gigabytes of Data Extensive Network

Coverage Opportunity to

Evaluate Multiple Routes on Same Arterial

Building on Powell Blvd. StudyBuilding on Powell Blvd. StudyBuilding on Powell Blvd. StudyBuilding on Powell Blvd. Study

Begin with limited signal system data.Begin with limited signal system data. Gather Gather archivedarchived TriMet AVL data. TriMet AVL data. MergeMerge two data sources to examine synergies two data sources to examine synergies

due to due to data fusiondata fusion.. Use geolocation data to calibrate influence Use geolocation data to calibrate influence

areas from loops.areas from loops.

Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07Buses Inform Detector Readings – 2/12/07

Hamilton

Bertha

Park & Ride

Sheridan

8:00 AM 9:00 AM

Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07Buses Inform Detector Readings – 2/15/07

Hamilton

Bertha

Park & Ride

Sheridan

8:00 AM 9:00 AM

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

Midpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute DataMidpoint Method Using 5-Minute Data

5:00 PM 5:30 PM

Adjust Influence Areas ManuallyAdjust Influence Areas ManuallyAdjust Influence Areas ManuallyAdjust Influence Areas Manually

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

5:00 PM 5:30 PM

Bus Data Confirms AdjustmentBus Data Confirms AdjustmentBus Data Confirms AdjustmentBus Data Confirms Adjustment

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

5:00 PM 5:30 PM

Reveals Gaps in DetectionReveals Gaps in DetectionReveals Gaps in DetectionReveals Gaps in Detection

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

5:00 PM 5:30 PM

New Occupancy Map From Combined SourcesNew Occupancy Map From Combined SourcesNew Occupancy Map From Combined SourcesNew Occupancy Map From Combined Sources

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

5:00 PM 5:30 PM

An Improvement Over Mid-Point MethodAn Improvement Over Mid-Point MethodAn Improvement Over Mid-Point MethodAn Improvement Over Mid-Point Method

Hamilton

Park & Ride

Sheridan

6:00 PM

Bertha

5:00 PM 5:30 PM

The Proof?The Proof?The Proof?The Proof?

1012141618

Actual Bus Max Speed Method

Signal Max Speed x 1.25

Signal + Bus

Morning Peak Midday Off-Peak Evening Peak

Last Point -- Bus FrequencyLast Point -- Bus FrequencyLast Point -- Bus FrequencyLast Point -- Bus Frequency

ConclusionsConclusions

Our attempt to fuse data sources appears promising Confirms TriMet buses can be probes Signal data needs work

Challenges Detailed AVL Data (Stop Level) Not Available in

Real Time (?) Travel Times Limited by Detector Data

What to “archive” is still an open question

Our attempt to fuse data sources appears promising Confirms TriMet buses can be probes Signal data needs work

Challenges Detailed AVL Data (Stop Level) Not Available in

Real Time (?) Travel Times Limited by Detector Data

What to “archive” is still an open question

AcknowledgementsAcknowledgements

TransPort Members FHWA: Nathaniel Price ODOT: Galen McGill PSU & OTREC (Local Matching

Funds) City of Portland: Bill Kloos, Willie

Rotich TriMet: David Crout, Steve Callas JPACT and Oregon Congressional

Delegation ITS Lab: John Chee, Rafael

Fernandez

TransPort Members FHWA: Nathaniel Price ODOT: Galen McGill PSU & OTREC (Local Matching

Funds) City of Portland: Bill Kloos, Willie

Rotich TriMet: David Crout, Steve Callas JPACT and Oregon Congressional

Delegation ITS Lab: John Chee, Rafael

Fernandez

Thank You!www.its.pdx.edu

1 NATMEC 2008 Christopher Monsere Robert L. Bertini, Mathew Berkow, and Michael Wolfe Intelligent...

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