1 Lessons From Developing an Archived Data User Service: Who Is Using It? Lessons from Developing an Archived Data User Service in Portland, Oregon: Who Is Using It? Linking Archived Data User Service, Performance Measures, and Freeway Operations to Improve Mobility Transportation Research Board Annual Meeting January 21, 2007 Robert L. Bertini

2 Lessons From Developing an Archived Data User Service: Who Is Using It? OutlineOutline  About PORTAL  User Survey Results  Some Success Stories  About PORTAL  User Survey Results  Some Success Stories

3 Lessons From Developing an Archived Data User Service: Who Is Using It? What’s in the PORTAL Database? Loop Detector Data 20 s count, lane occupancy, speed from 500 detectors (1.2 mi spacing) Incident Data 140,000 since 1999 Weather Data VMS Data 19 VMS since 1999 Data Archive Days Since July 2004 About 300 GB

4 Lessons From Developing an Archived Data User Service: Who Is Using It? PORTAL and Regional Facts  PORTAL  SQL relational database  200 MB/day, 75 GB per year  Regional Infrastructure  98 CCTV Cameras  138 Ramp Meters  TriMet Automatic Vehicle Location (AVL) System and Bus Dispatch System (BDS)  Extensive fiber optics network  Bi-state region  Regional ITS Committee: TransPort  Data sharing philosophy  Gigabit ethernet/private ITS network  PSU official data archive entity

5 Lessons From Developing an Archived Data User Service: Who Is Using It? Performance Measures Used  Volume  Speed  Occupancy  Vehicle Miles Traveled  Vehicle Hours Traveled  Travel Time  Delay

6 Lessons From Developing an Archived Data User Service: Who Is Using It? Contour Plots - Speed

7 Lessons From Developing an Archived Data User Service: Who Is Using It? Weather Popup

8 Lessons From Developing an Archived Data User Service: Who Is Using It? Data Quality Popup

9 Lessons From Developing an Archived Data User Service: Who Is Using It? Data Quality Popup

10 Lessons From Developing an Archived Data User Service: Who Is Using It? Time Series - Volume

11 Lessons From Developing an Archived Data User Service: Who Is Using It? Grouped Data – Travel Time

12 Lessons From Developing an Archived Data User Service: Who Is Using It? Performance Report - Reliability

13 Lessons From Developing an Archived Data User Service: Who Is Using It? Monthly Report

14 Lessons From Developing an Archived Data User Service: Who Is Using It? Daily Dashboard

15 Lessons From Developing an Archived Data User Service: Who Is Using It? Incident Reports Incident on NB I-205, log truck rear-ended a nursery truck, two cars also involved, duration over 4 hours. 11/15/2005 Northbound I-205 Incident on SB I- 205, NB effects visible

16 Lessons From Developing an Archived Data User Service: Who Is Using It? Monthly Incident Reports

17 Lessons From Developing an Archived Data User Service: Who Is Using It? Mapping – Speed By Month Average Evening Peak Speed (5-6 pm) July 2005December 2005

18 Lessons From Developing an Archived Data User Service: Who Is Using It? Mapping – Speed Subtraction Average Evening Peak Speed (5-6 pm) Difference July-December 2005

19 Lessons From Developing an Archived Data User Service: Who Is Using It? Bivariate Plots

20 Lessons From Developing an Archived Data User Service: Who Is Using It? Data Quality Reports Stations Reporting (June 2006 weekdays):   No Traffic (all lanes) > 20% of Samples   Communications Failure > 15% of Samples

21 Lessons From Developing an Archived Data User Service: Who Is Using It? Google Traffic

22 Lessons From Developing an Archived Data User Service: Who Is Using It? Bus Data  Arterials

23 Lessons From Developing an Archived Data User Service: Who Is Using It? PORTAL User Survey  ed 189 users  Total of 40 responses (21%)  Assess overall user satisfaction and learn how PORTAL’s constituents are using the system

24 Lessons From Developing an Archived Data User Service: Who Is Using It? User Types

25 Lessons From Developing an Archived Data User Service: Who Is Using It? Employer Type University 30% Private/consulting firm 29% Regional or local agency 19% State agency 13% Federal agency 6% Other 3%

26 Lessons From Developing an Archived Data User Service: Who Is Using It? Use Frequency

27 Lessons From Developing an Archived Data User Service: Who Is Using It? Ease of Use

28 Lessons From Developing an Archived Data User Service: Who Is Using It? Which Tabs Do You Use

29 Lessons From Developing an Archived Data User Service: Who Is Using It? Examples?Examples?

30 Lessons From Developing an Archived Data User Service: Who Is Using It? Future Extensions

31 Lessons From Developing an Archived Data User Service: Who Is Using It? Demo Request

32 Lessons From Developing an Archived Data User Service: Who Is Using It? Some Success Stories The incident reports provided within PORTAL are designed to give traffic operations mangers 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. 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. Finally, the FHWA, ODOT and Metro (the regional planning organization) are using PORTAL to improve the Portland congestion management program.The incident reports provided within PORTAL are designed to give traffic operations mangers 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. 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. Finally, the FHWA, ODOT and Metro (the regional planning organization) are using PORTAL to improve the Portland congestion management program. As show in Figure 2, PORTAL is being used to monitor freeway performance over time. Metro has developed the map shown to compare freeway speeds in May 2006 versus May As shown by the colors, on some segments speeds are higher, while on others speeds are lower. In addition, Metro and ODOT have used PORTAL to assess the impact of construction on a major freeway corridor. Figure 3 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 slightly slow during the evening peak—but that the speeds are lower in 2004 than they were in 2005.As show in Figure 2, PORTAL is being used to monitor freeway performance over time. Metro has developed the map shown to compare freeway speeds in May 2006 versus May As shown by the colors, on some segments speeds are higher, while on others speeds are lower. In addition, Metro and ODOT have used PORTAL to assess the impact of construction on a major freeway corridor. Figure 3 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 slightly slow during the evening peak—but that the speeds are lower in 2004 than they were in 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. Figure 4 shows that the months with the highest rainfall also witness the most congestion. The total monthly rainfall is shown in columns while the occurrence of congestion (average amount of time per day when congestion is present) is illustrated by the line. The final paper will provide other specific examples provided by PORTAL survey respondents, as well as recommendations for next steps that can be extended to developers of ITS data archives in other cities.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. Figure 4 shows that the months with the highest rainfall also witness the most congestion. The total monthly rainfall is shown in columns while the occurrence of congestion (average amount of time per day when congestion is present) is illustrated by the line. The final paper will provide other specific examples provided by PORTAL survey respondents, as well as recommendations for next steps that can be extended to developers of ITS data archives in other cities. The incident reports provided within PORTAL are designed to give traffic operations mangers 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. 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. Finally, the FHWA, ODOT and Metro (the regional planning organization) are using PORTAL to improve the Portland congestion management program.The incident reports provided within PORTAL are designed to give traffic operations mangers 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. 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. Finally, the FHWA, ODOT and Metro (the regional planning organization) are using PORTAL to improve the Portland congestion management program. As show in Figure 2, PORTAL is being used to monitor freeway performance over time. Metro has developed the map shown to compare freeway speeds in May 2006 versus May As shown by the colors, on some segments speeds are higher, while on others speeds are lower. In addition, Metro and ODOT have used PORTAL to assess the impact of construction on a major freeway corridor. Figure 3 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 slightly slow during the evening peak—but that the speeds are lower in 2004 than they were in 2005.As show in Figure 2, PORTAL is being used to monitor freeway performance over time. Metro has developed the map shown to compare freeway speeds in May 2006 versus May As shown by the colors, on some segments speeds are higher, while on others speeds are lower. In addition, Metro and ODOT have used PORTAL to assess the impact of construction on a major freeway corridor. Figure 3 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 slightly slow during the evening peak—but that the speeds are lower in 2004 than they were in 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. Figure 4 shows that the months with the highest rainfall also witness the most congestion. The total monthly rainfall is shown in columns while the occurrence of congestion (average amount of time per day when congestion is present) is illustrated by the line. The final paper will provide other specific examples provided by PORTAL survey respondents, as well as recommendations for next steps that can be extended to developers of ITS data archives in other cities.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. Figure 4 shows that the months with the highest rainfall also witness the most congestion. The total monthly rainfall is shown in columns while the occurrence of congestion (average amount of time per day when congestion is present) is illustrated by the line. The final paper will provide other specific examples provided by PORTAL survey respondents, as well as recommendations for next steps that can be extended to developers of ITS data archives in other cities.

33 Lessons From Developing an Archived Data User Service: Who Is Using It? Some Success Stories  Data Quality  Ramp Metering  Incident Management  Freeway Travel Time  Regional ITS  Data Quality  Ramp Metering  Incident Management  Freeway Travel Time  Regional ITS

34 Lessons From Developing an Archived Data User Service: Who Is Using It? Communications Bottleneck  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  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 get them repaired.  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  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 get them repaired. Number of Samples Failing Selected Conditions; Jan-June 2006; I-5

35 Lessons From Developing an Archived Data User Service: Who Is Using It? Ramp Metering System Evaluation  ODOT uses 15 min ramp data to assist with new metering system  A system wide ramp metering (SWARM) system is being implemented in the Portland metropolitan area.  This study entails a before and after evaluation of the operational benefits of the new SWARM system  In particular, the study will quantify system wide benefits in terms of savings in delay, emissions and fuel consumption, and safety improvements  This will aid in the optimal deployment of the current SWARM system  ODOT uses 15 min ramp data to assist with new metering system  A system wide ramp metering (SWARM) system is being implemented in the Portland metropolitan area.  This study entails a before and after evaluation of the operational benefits of the new SWARM system  In particular, the study will quantify system wide benefits in terms of savings in delay, emissions and fuel consumption, and safety improvements  This will aid in the optimal deployment of the current SWARM system

36 Lessons From Developing an Archived Data User Service: Who Is Using It? Incident Autopsy: 6/12/06

37 Lessons From Developing an Archived Data User Service: Who Is Using It? Incident Autopsy: 6/12/06 8:152-vehicles collide 8:19Crash reported 8:27VMS message: CENTER LANES CLSD 8:40COMET requests tow 9:10 Tow arrives 9:27 Lanes clear 9:30Traffic starts to clear 9:45Traffic half clear 10:00Traffic all clear

38 Lessons From Developing an Archived Data User Service: Who Is Using It? Incident Autopsy: 6/12/ :0008:1008:2008:3008:4008:5009:0009:1009:2009:3009:4009:5010:00 10:10 10:2010:3010:4010:5011:00 vehicles per 5 minutes Crash All Lanes Clear All Traffic Clear Tow Arrives

39 Lessons From Developing an Archived Data User Service: Who Is Using It? Incident Autopsy  Political interest in incident management  Travel time reliability  Freight planning  Regional incident management task force now established  Political interest in incident management  Travel time reliability  Freight planning  Regional incident management task force now established

40 Lessons From Developing an Archived Data User Service: Who Is Using It? Freeway Travel Time Reporting  Portland State University recently conducted a study revealing inaccuracies in the current algorithm used for predicting travel time in the Portland area  The algorithm performed well under normal traffic conditions, however, underestimated travel time during periods of congestion  This project intends to build upon the investigation into alternative algorithms, and determine the best approach for improving travel time estimates in “real time” applications  These applications include providing estimates on variable message signs, tripcheck.com, and the 511 traveler information system  Portland State University recently conducted a study revealing inaccuracies in the current algorithm used for predicting travel time in the Portland area  The algorithm performed well under normal traffic conditions, however, underestimated travel time during periods of congestion  This project intends to build upon the investigation into alternative algorithms, and determine the best approach for improving travel time estimates in “real time” applications  These applications include providing estimates on variable message signs, tripcheck.com, and the 511 traveler information system

41 Lessons From Developing an Archived Data User Service: Who Is Using It? Portal In Action: Metropolitan Congestion Over Time WinterSpringSummerFall

42 Lessons From Developing an Archived Data User Service: Who Is Using It? Cross Section Study Speed- Volume Analysis (2005) Speed Comparison ‘04 ‘05 Volume Speed

43 Lessons From Developing an Archived Data User Service: Who Is Using It? Cross Section Comparison Geographic Bottlenecks Mega- project! Design Flaws Good Free-flow performance Looming Danger

44 Lessons From Developing an Archived Data User Service: Who Is Using It? HOV Analysis

45 Lessons From Developing an Archived Data User Service: Who Is Using It? Workzone Influence

46 Lessons From Developing an Archived Data User Service: Who Is Using It? Weather Impacts

47 Lessons From Developing an Archived Data User Service: Who Is Using It? Speed Difference May 06-May 05

48 Lessons From Developing an Archived Data User Service: Who Is Using It? Snapshot Map May 2006 AM Peak

49 Lessons From Developing an Archived Data User Service: Who Is Using It? May-Nov 2005 Comparison

50 Lessons From Developing an Archived Data User Service: Who Is Using It? Traffic Volume and Speed on US26 Eastbound at Canyon Road in 2005 Traffic Volume and Speed on US26 Eastbound at Canyon Road in 2005

51 Lessons From Developing an Archived Data User Service: Who Is Using It? Traffic Speed on I-84 Westbound at NE 82nd Avenue, 2004 vs. 2005

52 Lessons From Developing an Archived Data User Service: Who Is Using It? Traffic Speed on I-5 Southbound at Capitol Highway, 2004 vs. 2005

53 Lessons From Developing an Archived Data User Service: Who Is Using It? Planning-Operations Connection  Congestion Management  Non-recurring  Reliability  System management  Promoting ITS  Links to freight and demand management  Planning for Operations  Regional Concept of Transportation Operations Grant  TSMO & ITS in RTP and TIP  MPO Committees  Connection to Economic Development  Congestion Management  Non-recurring  Reliability  System management  Promoting ITS  Links to freight and demand management  Planning for Operations  Regional Concept of Transportation Operations Grant  TSMO & ITS in RTP and TIP  MPO Committees  Connection to Economic Development

54 Lessons From Developing an Archived Data User Service: Who Is Using It? Metropolitan Mobility the Smart Way

55 Lessons From Developing an Archived Data User Service: Who Is Using It? Media Use

56 Lessons From Developing an Archived Data User Service: Who Is Using It? Media Use

57 Lessons From Developing an Archived Data User Service: Who Is Using It? Expanding Functionality   Data from:   min   TriMet – bus probe locations   Washington State DOT   City of Portland arterials   ODOT WIM Data   Additional processing tools and performance measures   Web interface is expanding use of archived data   Increasing awareness of the value of these systems   Provides decision support for transportation officials in the region

58 Lessons From Developing an Archived Data User Service: Who Is Using It? AcknowledgmentsAcknowledgments  Alex Skabardonis, Pravin Varaiya, Karl Petty and PEMS  PORTAL Team: Kristin Tufte, Sirisha Kothuri, James Rucker, Jessica Potter, John Chee, Spicer Matthews, Sue Ahn, Andy Delcambre, Tim Welch, Steve Hansen, Andy Rodriguez, Andrew Byrd  National Science Foundation  Oregon Department of Transportation  Federal Highway Administration  TransPort ITS Coordinating Committee  City of Portland  TriMet  Oregon Engineering and Technology Industry Council  Alex Skabardonis, Pravin Varaiya, Karl Petty and PEMS  PORTAL Team: Kristin Tufte, Sirisha Kothuri, James Rucker, Jessica Potter, John Chee, Spicer Matthews, Sue Ahn, Andy Delcambre, Tim Welch, Steve Hansen, Andy Rodriguez, Andrew Byrd  National Science Foundation  Oregon Department of Transportation  Federal Highway Administration  TransPort ITS Coordinating Committee  City of Portland  TriMet  Oregon Engineering and Technology Industry Council Visit PORTAL Online:

59 Lessons From Developing an Archived Data User Service: Who Is Using It? Thank You!