portland adus bertini & byrd psu its lab 16-jan-16 page 1 developing a transportation data...

Portland ADUSBertini & ByrdPSU ITS LabMay 3, 2023

Developing a Transportation Data Archive for the Portland Metropolitan Area.Robert L. BertiniAndrew ByrdThareth Yin

ITE Quad ConferenceApril 23, 2004


Introduction.Outline.

Introduction National ITS Architecture Portland ADUS ADUS Architecture Data Processing and Storage Data Analysis and Visualization Trial Uses Next Steps


“Data are too valuable to only

use once.”

Introduction.Guiding Principles.


“Management of the

transportation system cannot

be done without knowledge of

its performance.”

Introduction.Guiding Principles.


Introduction.National Science Foundation.

National Science Foundation CAREER: Mining Archived Intelligent Transportation Systems Data: A Validation Framework for Improved Performance Assessment and Modeling


Introduction.NSF Project Objectives. Exploit still-untapped ITS data for accurate

assessment of system operation. Develop and test multimodal transportation system

performance measures. Better understanding of fundamental traffic flow

phenomena. Improved traffic flow modeling. Forecasting future system state so true control

measures can be applied and evaluated. Outreach aimed toward increasing enrollment, quality

and diversity in the transportation program. Attract and retain students from diverse backgrounds

and with diverse learning styles to science and engineering.


National ITS Architecture.Overview.


National ITS Architecture.Overview.

1. Travel And Traffic Management 1.1 Pre-trip Travel Information1.2 En-route Driver Information1.3 Route Guidance1.4 Ride Matching & Reservation1.5 Traveler Services Information1.6 Traffic Control1.7 Incident Management1.8 Travel Demand Management1.9 Emissions Testing & Mitigation1.10 Highway Rail Intersection

2. Public Transportation Management 2.1 Public Transportation Management2.2 En-route Transit Information2.3 Personalized Public Transit2.4 Public Travel Security

3. Electronic Payment 3.1 Electronic Payment Services

4. Commercial Vehicle Operations 4.1 Comm. Vehicle Electronic Clearance4.2 Automated Roadside Safety Inspection

4.3 On-board Safety & Security Monitoring4.4 Commercial Vehicle Administrative Processes4.5 Haz. Material Security & Incident Response4.6 Freight Mobility

5. Emergency Management 5.1 Emergency Notification & Personal Security5.2 Emergency Vehicle Management5.3 Disaster Response And Evacuation

6. Advanced Vehicle Safety Systems 6.1 Longitudinal Collision Avoidance6.2 Lateral Collision Avoidance6.3 Intersection Collision Avoidance6.4 Vision Enhancement For Crash Avoidance6.5 Safety Readiness6.6 Pre-crash Restraint Deployment6.7 Automated Vehicle Operation

7. Information Management 7.1 Archived Data Function

8. Maintenance And Construction Management 8.1 Maintenance & Construction Operations


National ITS Architecture.ADUS Is Born. ITS technologies collect data

Real time control Incident management Traffic signal systems Traveler information

Also useful if saved and accessible Data already being collected—incentive for

storing them for future use. Difficulty not in collecting data but in gaining access

to that data Archived Data User Service (ADUS)

Managing ITS data beyond ITS Careful management of data for various

stakeholders


National ITS Architecture.ADUS Is Born. ADUS controls archiving functionality for all ITS

data: Operational Data Control: manage operations

data integrity. Data Import and Verification: acquire historical

data. Automatic Data Historical Archive: permanent

data archive. Data Warehouse Distribution: integrates

planning, safety, operations, and research communities into ITS and processes data products for these communities

ITS Community Interface: provides common interface to all ITS users for data products specification and retrieval.


National ITS Architecture.Data Poor to Data Rich.

Traffic Surveillance Fare/Toll Systems Incident

Management Traffic Video Environmental CVO Traffic Control Highway/Rail Emergency

Response

ITSITSDataData

ArchivesArchives

Performance MonitoringNational reportingPerformance-based planningEvaluationsPublic Reactions

Long Range PlanningTRANSIMSIDASFour step modelsTransit routes

Operations PlanningIncident managementER deploymentSignal timingTransit service

Travel Time ForecastingCustomized route planningATIS Advisories

Other Stakeholder FunctionsSafetyLand useAir qualityMaintenance management


Portland ADUS.PSU Designated Regional Archive Center.


Portland ADUS.Current Status.

ODOT Freeway loop detector

data Incident dataNOAA Weather dataTriMet Bus poll data Bus dispatch dataCity of Portland Traffic signal count/speed

dataWashington State DOT


Portland ADUS.Who Can Use ITS Data?Fourteen Stakeholders Identified:

Transportation Planning Transportation System Monitoring Air Quality Analysis MPO/State Freight and Intermodal Planning Land Use/Growth Management Planning Transportation Administrators and Policy

Analysis Traffic Management Transit Management Construction and Maintenance Safety Planning and Administration Commercial Vehicle Operations Emergency Management Transportation Research Private Sector


Portland ADUS.Vision.

75 CCTV Cameras 436 Inductive

Loop Detectors 118 Ramp Meters


ADUS Architecture.Implementing A Successful Archive. Existing Systems

California PeMS Puget Sound (WSDOT / TRAC) San Antonio, TX TransGuide

Positive features and lessons learned Texas DOT and TTI study Begin with a single data source Provide data through the web or CD

subscription Save raw data Make aggregate data available to users Data quality control measures Provide documentation!


ADUS Architecture.Fiber Optic Data Connection.


ADUS Architecture.Data Flows.

ODOTTMOC

Loop Controllers

Fiber

PSUADUSServer

Fiber

WebServer

TriM

et

WS

DO

T

City

of

Por

tland

Future

BackupServer

Operations Planning PublicUser Classes


ADUS Architecture.Database Backend / Web Frontend. Database backend

SQL relational database 200 MB per day of raw

data 75 GB per year High capacity disk array 5MB compressed for

download Off-site backup server

Daily backups Uninterruptible power

Web-based interface Easily accessible PHP language


Data Processing and Storage.The Web Interface Is Up and Running.

Loop health analysis Proven techniques prevent propagation of

error


Data Processing and Storage.Aggregation Levels. Raw 20-second loop detector data

Useful for research, traffic flow theory Huge data sets Previously difficult to manage and organize

High resolution aggregates 5 and 15 minute aggregates Flow, speed, and occupancy retained VMT, VHT, travel time, delay added Useful for research and planning purposes

Lower resolution aggregates Hourly or daily VMT, VHT, travel time, delay Increased processing speed for long term

overviews


Data Analysis and Visualization.Contour Plots.


Data Analysis and Visualization.Time Series Plots.


Trial Uses.Preliminary Performance Analyses. Metro travel demand modeling

Highway 217 V/C versus travel time function Used database backend and custom queries

Metro performance measures report

Hwy 217 delay curve comparison

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2

v/c ratio

trav

el ti

me

(min

.)

high vdfdelay

low vdfdelay

conical vdfdelay


Next Steps.Expanding Archive Functionality. Tri-Met

Bus and MAX Location/dispatch

Washington State DOT City of Portland Additional performance

measures and plots


Acknowledgments.

National Science Foundation

Oregon Department of Transportation

City of Portland TriMet Portland State University Oregon Engineering and

Technology Industry Council


Feedback.Your Opinions and Suggestions.As potential users, your opinions and input on this

project are appreciated. Please let us know what you think about existing or future:

Data sources Performance measures Data visualizations and summaries

Contact us:

[email protected]@cs.pdx.edu

http://www.its.pdx.edu

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