Beyond Archiving: Developing and Attracting Users of an

Beyond Archiving: Developing and Attracting Users of an Archived Data User Service

Robert L. Bertini

Department of Civil and Environmental Engineering

Portland State University

P.O. Box 751

Portland, OR, 97207 USA

E-mail: [email protected]

Phone: 503-725-4249

Fax: 503-725-5950

Jonathan Makler

Metro

600 NE Grand Ave.

Portland, OR 97232 USA

E-mail: [email protected]

Phone: 503-797-1873

Fax: 503-797-1911.

Submitted for presentation and publication to the

87th Annual Meeting of the Transportation Research Board

January 21–25, 2007

Revised October 2007

TRB 2008 Annual Meeting CD-ROM Paper revised from original submittal.

Bertini and Makler 2

Abstract. The value of creating an ITS data archive is somewhat undisputed, and a number exist in states and major

metropolitan regions in North America. In addition to providing a secure data storage environment many archives

include tools for analyzing the quality of the data and for creating performance measures describing the

transportation system both in real time and on a historical basis. An ITS data archive provides a unique opportunity

to measure how a transportation system operates over time. An ITS data archive has been developed in Portland,

Oregon at relatively low cost, taking advantage of sensors and communications used to operate the system in real

time. The value of the data archive is governed by the quality of the analysis tools provided for users. The objective

of this paper is to describe the results of a survey conducted to gauge ADUS user needs and experiences from both

the planning and operations perspectives. Recommendations for improvements and next steps are provided.

INTRODUCTION

The Portland Oregon Regional Transportation Archive Listing (PORTAL) is the official intelligent transportation

systems data archive for the Portland metropolitan region. PORTAL has been archiving 20-second speed, count, and

occupancy data from the approximately 500 inductive loop detectors (at an average spacing of 1.2 mi) in the

Portland metropolitan region since July 2004. The ITS infrastructure in the Portland region also includes nearly 100

CCTV cameras, 138 ramp meters, transit signal priority, advanced bus dispatch system, and an extensive fiber optics

network. The bi-state (including Southwest Washington) regional transportation agencies (including Portland State

University) are connected via a high speed (gigabit) ethernet ITS network that facilitates data sharing and

interoperatility (1,2,3).

About 200 MB per day of PORTAL data are stored in a PostgreSQL relational database management

system, and the database is approximately 300GB in size. PORTAL’s web-based entry point (Figure 1) is written

primarily in PHP and provides user-friendly access to the data archive without requiring users to have programming

capabilities. As shown in Figure 2, PORTAL also includes weather data, 140,000 incident logs and variable message

sign (VMS) data since 1999. PORTAL has a web-based interface that provides performance metrics designed to

assist practitioners and researchers. Currently PORTAL has 254 registered users from transportation agencies,

consultants and academia. The objective of this paper is to describe how PORTAL’s constituents are actually using

the ITS data archive in their daily work, in both planning and operations environments. This work is based on a

recent web-based survey of PORTAL’s users, along with follow-up interviews and continuing analysis. Results of

this project are being used to improve PORTAL’s user interface, as well as its tools, and will be useful for cities or

regions with existing ITS data archive systems and for those planning future implementations.

Archived ITS data is viewed as an integral component of the U.S. ITS Architecture (4). PORTAL was

developed in accordance with the Archived Data User Service (ADUS) framework developed by the U.S.

Department of Transportation (DOT) as part of the architecture and has been has designated by the Portland ITS and

operations agencies as the official ITS data archiving entity for the Portland region. As suggested in the FHWA ITS

Guidelines (5), user access to PORTAL is via a web-based interface providing easy access to both raw data and a

wide range of common summary data and standard performance measures. Currently, PORTAL’s users include

transportation planners, metropolitan planning organizations (MPOs), traffic management operators, transit

operators, and transportation researchers. PORTAL is made possible by the fact that transportation agencies in the

Portland metropolitan region freely share their data, and make it available free to the public. This underlying

philosophy is critical to the success of the system.

FIGURE 1 PORTAL user interface.



ADUS USER SURVEY OF CURRENT FEATURES

In order to assess overall user satisfaction and to learn how PORTAL’s constituents are using the system, a web-

based unscientific survey was developed and distributed to all registered PORTAL users. There were a total of 42

responses (a 17% response rate), and respondents helped assess overall user satisfaction and revealed how

PORTAL’s constituents are using the system. The survey asked questions about the respondents’ jobs and day-to-

day data needs. Figure 3 shows that about one third of the users who responded consider themselves in an academic

category, followed by nearly a quarter of users in an operations environment, with the remainder in engineering,

FIGURE 2 PORTAL data sources.

Loop Detector Data20 s count, lane occupancy, speed from

500 detectors (1.2 mi spacing)

Incident Data140,000 since 1999

Weather DataVMS Data

19 VMS since 1999

How Do You Find PORTAL’s User Interface?

Easy

39%

Neither EasyNorDifficult23%

Difficult

23%

Very Difficult3%

Very Easy

6%

N/A 6%

How Often Do You Use PORTAL as a Tool?

Only on special occasions 58%

Yearly 3%

Monthly

13%

Weekly

13%

Never 3%

Other 10%

What Kind of User Do You Consider Yourself?

Academic

(Researcher

or Student)

32%

Engineering

16%

Operations

23%

Planning

10%

Policy 3%

Other 16%

Employer Type

University

30%

Private/consulting firm29%

Regional or

local agency

19%

State agency

13%

Federal agency6%

Other 3%

FIGURE 3 PORTAL user types. FIGURE 4 PORTAL employer types.

FIGURE 5 PORTAL use frequency. FIGURE 6 PORTAL user interface.



planning, and policy arenas.

To gauge the range of user employers Figure 4 shows that most users are affiliated with universities,

followed by private/consulting firm users. Nearly 20% of users work for regional or local agencies, followed by

users employed by state and federal agencies. It was important to gain an understanding of how PORTAL is used, so

respondents were asked to describe how often they use PORTAL as a tool. As shown in Figure 5, almost 60% of

those surveyed use PORTAL on special occasions, when they have a particular need. Reasonable fractions use

PORTAL weekly or monthly followed by small percentages of users in the yearly, never, and other categories.

Each respondent was asked to report their satisfaction with the system and for specific comments. These

inputs will be used as a basis upon with to improve and expand PORTAL in the future. Each respondent was also

asked to provide specific examples of how they use PORTAL in their job. As shown in Figure 6, about half of the

survey respondents consider PORTAL’s user interface to be very easy or easy. About one quarter consider the

interface to be difficult or very difficult—the PORTAL team is targeting these users further to aim training or

system improvements toward making the system more accessible and less difficult in perception and in reality. One

survey question asked specifically if a user would like a personalized PORTAL demonstration, and 10% responded

yes. These inputs will be used as a basis upon with to improve and expand PORTAL in the future.

There are several major categories of analysis possible within PORTAL, available via selection of a

particular ―tab.‖ Respondents were asked to rate their use and level of familiarity with each tab. Figure 7 shows the

results. It’s clear that the largest fractions of users are familiar with the Timeseries and Congestion tabs, followed by

the Incident Reports and Monthly Data tabs. Some of the ―tabs‖ have been created for particular users, so this is a

helpful signal that users are relatively familiar with many of the key functions.

ADUS USER SURVEY OF FUTURE EXPANSION

The PORTAL system will be expanding to include additional data sources including: city arterial performance data

from traffic signal systems; transit bus data from the automatic vehicle location (AVL) system; tools for analyzing

variable message sign (VMS) data; freeway data from the Washington State Department of Transportation for the

Vancouver area; more detailed weather data; and pre-2004 freeway loop detector data aggregated at 15-minute

levels. As a final set of survey questions, users were asked to rate each of the new sources so that priorities can be

set in a rigorous way.

Respondents rated each of the seven expansion categories on a scale of 1 to 5, where 1 was the most

desired. Figure 8 shows that the strongest response was for the arterial performance data (mean score of 1.8). Fig 9

shows a sample arterial performance report using transit AVL data from one route in Portland. The next generation

of PORTAL will include the ability to produce both transit performance measures and arterial performance reports

based on transit probe data. The figure shows an example for one route with each colored segment reporting on the

speed of the bus at a particular location.

The next two strongest categories were the transit performance and WSDOT data (mean scores of 2.2). The

lowest score here was for the ODOT weigh in motion data. Each respondent was also asked whether they had

FIGURE 7 PORTAL category use frequency.

54%

38%

24%

32%

41%

35%

32%

14%

51%

14%

8%19%

41%

3%

5%

0% 10% 20% 30% 40% 50% 60%

Timeseries

Grouped Data

Data Fidelity

Raw Data

Monthly Data

Weather

Performance

Dashboard

Congestion

SVG Maps

Bivariate Plots

Google Traffic

Incident Reports

None

Other



specific examples of how they use PORTAL in their job—a total of 21% of users surveyed offered sample PORTAL

uses.

EXAMPLE DATA ARCHIVE USES

How is PORTAL being used? From its inception it has been envisioned as a tool to be used on a day to day basis by

planners, engineers, consultants, operations personnel, and even managers and decision makers. Some of

PORTAL’s features are specifically aimed at particular people—for example, the data quality tab is aimed at

improving the quality of the loop detector data that forms the core of the system. PORTAL has helped ODOT

identify a communications issue that was creating a bottleneck in the data transmission, and that is now being

alleviated through the installation of new fiber optics switching equipment. By providing a ―top ten‖ detector error

report PORTAL helps ODOT prioritize field personnel to target the ―worst‖ detectors and repair them. Portland is

known for its rainy weather, and Metro has used the PORTAL system to suggest that the wet months witness more

congestion than other times of the year. They have shown that the months with the highest rainfall also witness the

most congestion. PORTAL can report the total monthly rainfall, and the occurrence of congestion (average amount

of time per day when congestion is present) can be reported for the same periods.

PORTAL is also a tool for evaluating the ramp metering system (currently 138 ramps are metered using a

systemwide adaptive control system), and by providing easy access to ramp counts and mainline speeds, ODOT has

used PORTAL to assist in management of the ramp metering system. ODOT also uses PORTAL to improve its use

of the loop detectors to estimate freeway travel times.

Based on the survey results, three main areas of PORTAL application are now presented: tracking recurrent

congestion, linking operations with transportation planning and improving incident response.

Tracking Recurrent Congestion

As shown in Fig 10, PORTAL is being used to monitor freeway performance over time. As the region’s MPO,

Metro is responsible for developing the region’s long range transportation plan and the congestion management

program. Metro began to use the speed maps shown in Fig 10 to compare freeway speeds during particular time

periods (four seasons per year in this case) from the Summer 2004 through the Fall of 2006. As shown by the colors,

on some segments speeds are higher, while on others speeds are lower. This tool can be used for any corridor (or the

entire region) and for any time period. The visualization aspect of the mapping tool has proven to be useful in

conveying the impacts of capital improvement projects (e.g. freeway widening and bottleneck alleviation) to a wide

audience. The FHWA has encouraged Metro to use performance tools such as this in the update to its Congestion

Management Program, which is currently underway. Figure 9 shows a sample portion of a monthly congestion

monitoring report for a section of southbound I-405. This shows the locations and durations where actual average

weekday speeds dropped below the FHWA congested speed of about 42 mph. This can be tracked from month to

month and on any corridor. This is an example of how PORTAL makes new kinds of analysis possible quickly and

at little additional cost.

FIGURE 8 Desired future PORTAL extensions.

Future Extensions

0% 10% 20% 30% 40% 50% 60% 70%

Freeway variable message sign data

Arterial performance data

Transit performance data

Washington DOT freeway data

ODOT Weigh In Motion Data

Freeway vehicle classification data

Pre-2004 freeway data (15 min

aggregation)1

2

3

4

5



Strengthening Links Between Operations and Planning

In updating its Regional Transportation Plan (RTP), Metro has used PORTAL to conduct a regional cross sectional

analysis at key points on the freeway network. Figure 10 shows annual average daily speeds (from weekdays in

2005) at eight key locations on the region’s freeways. The results show high speeds during off-peak periods, and

highlights the presence of a mid-day off peak period between 10:00 and 2:00 at most locations. Clearly at some

points speeds drop well below 40 mi/hr in both the morning and afternoon peak periods. Several are bottlenecks that

occur when one freeway ―tees‖ into another, while several others are the subject of current environmental and

planning studies for improvement. This tool highlights the value of the archived speed data throughout the network.

In addition, Metro and ODOT have used PORTAL to assess the impact of a major capital construction

project on a key east-west freeway corridor. Figure 11 contains a Hwy 26 Cross Section Study, and illustrates how

speed on the eastbound Sunset Highway changed between 2004, when construction was active, and 2005, when it

was complete. Note that each speed curve follows the same basic pattern—slow during the morning peak and

FIGURE 9 Using transit AVL data to report on arterial performance.

FIGURE 10 Regional cross sectional analysis.

Geographic

Bottlenecks

Mega-

project!

Design

Problems

Good

performance

Looming

Danger

Midweek Speed Data, 2005

0

10

20

30

40

50

60

70

80

90

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00

Time

Sp

eed

(m

ph

)

5NB @ Portland

84WB at 82nd

205 NB at Powell

205 SB at Stafford

5NB at Stafford

217 SB at BH

5SB at Capitol

26EB at Canyon



slightly slow during the evening peak—but that the speeds are substantially lower in 2004 than they were in 2005.

Figure 11 also couples hourly traffic volumes with speeds measured during 2005 which highlights the

heavy morning flows on this corridor. The figure reveals that flows remain high on this corridor throughout the day,

even during the midday. The ability to quickly produce studies such as these aids greatly in planning and operational

analysis. In fact, PORTAL’s capabilities have been used to aid in the completion of the requirements of a FHWA

Regional Concept of Transportation Operations (RCTO) grant. The aim of the grant is to advance planning

regionally for operations.

Improving Incident Response

Generally speaking nonrecurrent congestion is a target area for improvement, since it accounts for a large proportion

of the nation’s total congestion. While it is more difficult to make permanent capacity-increasing improvements to

the network, incident management is a low cost, highly effective strategy for reducing congestion. The incident

reports provided within PORTAL are designed to give traffic operations managers the tools to examine how their

assignment of incident response resources matches the incident rates in the field. For example the automated

incident report provides the average number of ongoing incidents by time of day which can be compared to the

number of response personnel. Incident data are entered into ODOT’s traffic management system database at the

regional traffic management operations center (TMOC). These data are incorporated automatically into PORTAL,

for mapping and analysis. Figure 12 shows a sample of the monthly incident analytical tools currently available

within PORTAL for December 2006. The figure shows that incidents for a particular month are broken down by

type (crash, stall, debris, tow, construction, and other). For this particular month, about 50% of the reported

FIGURE 11 Freeway cross section study.

Flow Analysis (2005)05 Speed Comparison

01000

2000

3000

4000

5000

0:00 4:00 8:00 12:00 16:00 20:00Time

Vo

lum

e (

veh

/hr)

0

10

20

30

40

50

60

70

Sp

eed

(m

ph

)

Vol05

Speed05

10

20

30

40

50

60

70

0:00 4:00 8:00 12:00 16:00 20:00Time

Sp

eed

(m

ph

)

Speed04

Speed05

Speed-2004-Cross Section StudyHwy 26 2004-2005

FIGURE 12 Monthly incident reporting.

Incident Types Number of Lanes Affected

Incident Locations Number of Ongoing Incidents

Time

Nu

mb

er

of

Incid

en

ts



incidents were stalls, and 20% were crashes. Incidents are shown by number of lanes affected; 0.8% affected 3

lanes, 5.6% affected two lanes, 30% affected one lane, and the rest did not affect any lanes. Incident locations are

also important for gauging incident response actions. Most incidents affected the right lanes and right shoulder.

Finally, the figure shows a plot of the number of ongoing incidents by time of day through the month. For example,

at 2:00 PM there was an average of 3.5 ongoing incidents. This reflects the need for about four incident responders

during the afternoon so that all incidents can be managed effectively.

It is possible to delve more deeply into the details of one incident, as shown in Figure 13. On June 12,

2006, a two-car crash occurred on northbound I-5 near Skidmore. The two left lanes were blocked from 8:15 to 9:27

AM. As shown in the figure, ODOT received three 911 calls, and confirmed the incident at 8:19. By 8:27 a message

was posted on three nearby VMS, and at 8:40 a tow was requested. At 9:26 the first vehicle was towed and the

second vehicle was removed. According to PORTAL speed and flow data, the traffic did begin to flow again at

about 9:30, and by 10:00 all effects of the incident were cleared. The City of Portland used PORTAL to estimate

that this one incident caused more than 5,000 veh-hr of delay, and converted this to a user cost of $144,000. System

users could have saved more than $10,000 if the tow truck had arrived ten minutes earlier. As a result of this

incident, and the subsequent analysis via PORTAL, a new regional task force known as the Portland Operations

Steering Team (POST) has been established in order to develop better incident management strategies that will

result in faster incident clearance. The availability of the PORTAL system enabled the preparation of the standard

incident autopsy shown in Figure 13, and has led to new levels of discussion and action regarding incidents in the

region. It is hoped that further decision support capabilities such as this can be provided in the future.

Congestion Monitoring Over Time

The features contained in PORTAL allow the Portland metropolitan region to examine freeway conditions over time

as part of ongoing congestion monitoring. By using these tools, it is possible to examine how conditions have

changed on particular facilities. As one example of this, Figure 14 shows seasonal freeway maps illustrating average

weekday segment speeds (by color). Using a tool such as this it is possible to see how travel conditions vary by

season and by year. As another example of congestion monitoring through PORTAL, Figure 15 shows a monthly

analysis of individual detectors for September 2006. This clearly illustrates that there is only one location that

routinely drops below a congested speed of 40 mph.

CONCLUSIONS

ITS data archive systems are in operation in several locations, including California, Washington, Maryland, Texas,

Virginia, and Oregon. This paper has described the results of a recent survey of the registered users of Oregon’s

PORTAL system. Users are generally satisfied with the system, are typically ―periodic‖ users (as opposed to regular

use), a few users requested personal demonstrations, and many offered example uses of the system. This paper has

demonstrated several example applications using PORTAL data including congestion monitoring, linkages between

planning operations, and nonrecurrent congestion.

In a research environment, it is critical to obtain feedback on the products that are developed so that

improvements can be made in an ongoing feedback loop. This user survey and subsequent analysis of the results has

been helpful in identifying priorities for PORTAL and has revealed the potential to improve transportation planning

FIGURE 13 Incident autopsy.



and operations in the Portland metropolitan region. In the future, continuing improvements will be aimed at

providing resources to agency staff and decision makers. Some arenas that are being considered continue to be

incident management, ways to improve travel time reliability, links to freight planning and tools aimed at members

of the general public.

ACKNOWLEDGEMENTS

Funding and support for this project is provided by the National Science Foundation, Oregon Department of

Transportation, Federal Highway Administration, City of Portland, TriMet and Metro. Special thanks to the

PORTAL development team, PORTAL users who responded to the survey and to Max Coffman for his assistance.

FIGURE 15 Monthly congestion monitoring.

I-405 SB Weekday Speed September 2006

0

10

20

30

40

50

60

70

0:0

0

1:0

0

2:0

0

3:0

0

4:0

0

5:0

0

6:0

0

7:0

0

8:0

0

9:0

0

10

:00

11:0

0

12:0

0

13:0

0

14:0

0

15:0

0

16:0

0

17

:00

18

:00

19

:00

20:0

0

21

:00

22:0

0

23:0

0

Time

Vo

lum

e (

vp

h)

Front Ave 0.55

5th Ave 0.97

Broadway 1.08

Montgomery 1.37

Taylor 1.81

Everett 2.22

“Congested” Speed

FIGURE 14 Regional congestion reporting over time.



REFERENCES

1. Bertini, R. L., K. Tufte, J. Rucker, J. Potter, and T. Welch. Expansion of an ITS Data Archive with Applications

for Improving Spatial Analysis and Tracking Non-Recurrent Congestion. In Proceedings of the 9th

International IEEE Conference on Intelligent Transportation Systems, Toronto, Canada, 2006.

2. Bertini, R. L., S. Matthews, S. Hansen, A. Delcambre, and A. Rodriguez. ITS Archived Data User Service in

Portland, Oregon: Now and Into the Future. In Proceedings of the 8th International IEEE Conference on

Intelligent Transportation Systems, Vienna, Austria, 2005.

3. Bertini, R. L., A. Byrd, and T. Yin. Implementing the ITS Archived Data User Service in Portland, Oregon. In

Proceedings of the 7th Annual IEEE Conference on Intelligent Transportation Systems, Washington, D.C.,

2004.

4. ADUS Program. Archived Data User Service (ADUS): An Addendum to the ITS Program Plan. USDOT,

September 1998.

5. Turner, S. Guidelines for Developing ITS Data Archiving Systems. Report 2127-3. FHWA, U.S. Department of

Transportation, Texas Department of Transportation and Texas Transportation Institute, 2001.


Documents

Beyond Archiving: Developing and Attracting Users of an