Evolution and Usage of the Portal Data Archive: 10-Year Retrospective

The Portal transportation data archive (http://portal.its.pdx.edu/) was begun in June 2004 in collaboration with the Oregon Department of Transportation, with a single data source: freeway loop detector data. In 10 years, Portal has grown to contain approximately 3 TB of transportation-related data from a wide variety of systems and sources, including freeway data, arterial signal data, travel times from Bluetooth detection systems, transit data, and bicycle count data. Over its 10-year existence, Portal has expanded both in the type of data that it receives and in the geographic regions from which it gets data. This paper discusses the evolution of Portal. The paper describes the new data, new regions, and new systems that have been added and how those changes have affected the archive. The paper concludes with a section on the uses of Portal that provides several examples of how Portal data have been used by regional partners, with a focus on measuring the performance of the multimodal transportation system, but also including educational elements and research

Multimodal Data at Signalized Intersections: Strategies for Archiving Existing and New Data Streams to Support Operations and Planning & Fusion and Integration of Arterial Performance Data

There is a growing interest in arterial system management due to the increasing amount of travel on arterials and a growing emphasis on multimodal transportation. The benefits of archiving arterial-related data are numerous. This research report describes our efforts to assemble and develop a multimodal archive for the Portland-Vancouver region. There is coverage of data sources from all modes in the metropolitan region; however, the preliminary nature of the archiving process means that some of the data are incomplete and samples. The arterial data sources available in the Portland-Vancouver region and that are covered in this report include data for various local agencies (City of Portland, Clark County, WA, TriMet and C-TRAN) covering vehicle, transit, pedestrian, and bicycle modes. We provide detailed descriptions of each data source and a spatial and temporal classification. The report describes the conceptual framework for an archive and the data collection and archival process, including the process for extracting the data from the agency systems and transferring these data to our multimodal database. Data can be made more useful though the use of improved visualization techniques. Thus as part of the project, a number of novel, online visualizations were created and implemented. These graphs and displays are summarized in this report and example visualizations are shown. As with any automated sensor system, data quality and completeness is an important issue and the challenge of automating data quality is large. Preliminary efforts to validate and monitor data quality and automate data quality processing are explored. Finally, the report presents efforts to combine transit and travel time data and signal timing and vehicle count data to generate some sample congestion measures

Creating And Using A Publicly Available Multimodal Transportation Data Archive

PORTAL provides a centralized, electronic database that facilitates the collection, archiving, and sharing of data and information for public agencies within the region. The data stored in PORTAL includes 20-second granularity loop detector data from freeways in the Portland-Vancouver metropolitan region, arterial signal data, travel time data, weather data, incident data, VAS/VMS message data, truck volumes, transit data, and arterial signal data. Many of these data feeds are received by PORTAL in real time or on a daily basis and for most, the retrieval and archiving process is fully automated. BikePed Portal: Jurisdictions around the country are collecting non-motorized traffic count data, but the lack of a centralized database inhibits data sharing and greatly reduces the utility of this important and growing dataset. In response, we created a national online non-motorized traffic count archive. This archive allows users to upload, view and download data. Access to a centralized non-motorized traffic data archive opens the door to innovation in research, design, and planning.https://pdxscholar.library.pdx.edu/trec_seminar/1191/thumbnail.jp

Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice

The Federal Highway Administration (FHWA) has set a high priority on the use of existing dynamic message signs (DMS) to provide travel time estimates to the public. The Oregon Department of Transportation (ODOT) currently has three DMS in the Portland metropolitan area configured to display travel time information. In the near future, ODOT would like to make travel time estimates available on additional DMS, over the Internet on tripcheck.com and via 511. Travel time estimates are valuable to the traveling public; however, the estimates must be accurate to be useful. The FHWA indicates that 90% accuracy is ideal and suggests a minimum accuracy of 80%. Thus, in order to display travel time estimates, it is essential to understand the accuracy of the estimates. The purpose of this study is to extend prior travel time research conducted at Portland State University with additional data collection and analysis to provide statistical confidence in travel time estimates and to determine the best travel time estimation approach for ODOT. Ground truth data in the form of probe vehicle runs will be collected and travel time estimates will be evaluated using that data. Several travel time estimation algorithms will be evaluated and modifications to existing algorithms will be proposed. In addition, this project will provide analysis to help understand the reliability and performance of the algorithms under various conditions (free-flow, congestion, incidents). A methodology will be developed for determining if travel time estimates fall within an acceptable accuracy limits. At the conclusion of the project, it is desired that a methodology can be recommended that will provide accurate measures of travel time for use with DMS, the Internet and 511 applications

Smart Cities Initiatives in the Portland Region

This talk will describe work in Smart Cities in the Portland region. We’ll begin with the framework and motivation for the Smart Cities work and the question What is a Smart City? We’ll discuss Portland’s approach to Smart Cities, provide some historical context and then give an overview of ongoing Smart Cities projects including work on AV policy, the Portland Urban Data Lake, new sensors and earthquake resilience. The goal of the talk is to give the audience an overview of the work being done in Portland to bring a human face to data and technology and to inspire question and discussion.https://pdxscholar.library.pdx.edu/systems_science_seminar_series/1084/thumbnail.jp

Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice, Phase II

The Federal Highway Administration (FHWA) has put a high priority on the use of existing dynamic message signs (DMS) to provide travel time estimates to the public. The Oregon Department of Transportation (ODOT) has three DMS in the Portland metropolitan area configured to display travel time information. In the near future, ODOT would like to make travel time estimates available on additional DMS, over the Internet on tripcheck.com and via 511. Travel time estimates are valuable to the traveling public; however, the estimates must be accurate to be useful. The purpose of this study is to extend prior travel time research conducted by Portland State University with additional analysis to provide statistical confidence in travel time estimates and to determine the best travel time estimation approach for ODOT. The initial ODOT-funded phase of this project gathered a large amount of ground truth data and analyzed the performance of the current algorithms and current infrastructure using that data. However, additional work remains to be done. OTREC Phase I of this project will focus on using the existing data to understand the conditions under which travel time estimation algorithms are not accurate. This extension will build on that work to investigate improvements to travel time estimation algorithms and to identify a set of metrics for travel time accuracy and guidelines for when travel time estimates should be provided. At the conclusion of the project, it is desired that a methodology can be recommended that will provide accurate measures of travel time for use with DMS, the Internet and 511 applications

Improving Travel Information Products via Robust Estimation Techniques

Traffic-monitoring systems, such as those using loop detectors, are prone to coverage gaps, arising from sensor noise, processing errors and transmission problems. Such gaps adversely affect the accuracy of Advanced Traveler Information Systems. This project will explore models based on historical data that can provide estimates to fill such gaps. We build on an initial study by Mr. Rafael J. Fernandez-Moctezuma, using both a linear model and an artificial neural network (ANN) trained on historical data to estimate values for reporting gaps. These initial models were 80% and 89% accurate, respectively, in estimating the correct speed range, and misclassifications were always between adjacent speed ranges (in particular, the free-flow range and congested range were never confused). Going forward, we will investigate other non-linear models, such as Gaussian Mixtures, that provide further statistical metrics, in contrast to the uninterpreted weights of ANNs. This work will exploit the Portland Transportation Archive Listing (PORTAL) at the Intelligent Transportation Systems Laboratory at PSU. Dr. Tufte helps supervise development of PORTAL, and Mr. Fernandez used PORTAL data in his study. PORTAL holds more than two years of Portland-area freeway-loop-detector data at both detailed and aggregated levels, and is an ideal resource for the proposed work. Initially we will be building and testing estimators in off-line mode. We will select a highway segment (comprising multiple detector stations) that is representative in terms of pattern of outages. We will build models for this segment, then examine their performance on estimates for synthetic gaps (so we can compare estimates to reported values). Later, using live loop-detector data (which PORTAL supports), we will work towards on-line estimation over the local freeway network, which requires computing estimates in a timely manner. Our end target is improvements in end-user travel information products, such as the Portland-Metro Speed Map on ODOT\u27s Trip Check. Our main evaluation metric will be the trade-off curve bewteen accuracy of prediciton and percentage of gaps that can be filled. This research supports national surface-transportation research priorities, including the Systems Management Information area (ITS JPO). Within that area, it relates to (2) Data Management (techniques and guidance for processing and managing data associated with highway and transit monitoring) and (5) Data Dissemination (exchanging information about transportation services and providing that information to travelers). [Page 3-15, U.S. Department of Transportation Research, Development, and Technology Plan, 6th Edition

Creating a National Nonmotorized Traffic Count Archive: Process and Progress

Robust bicycle and pedestrian data on a national scale would help promote effective planning and engineering of walking and bicycling facilities, build the evidence-based case for funding such projects, and dispel notions that walking and cycling are not occurring. To organize and promote the collection of nonmotorized traffic data, a team of transportation professionals and computer scientists is creating a national bicycle and pedestrian count archive. This archive will enable data sharing by centralizing continuous and short-duration traffic counts in a publicly available online archive. Although other archives exist, this will be the first archive that will be national in scope and enable data to be uploaded directly to the site. This archive will include online input, data quality evaluation, data visualization functions, and the ability to download user-specified data and exchange the data with other archives and applications. This paper details the first steps in creating the archive: (a) review count types, standard formats, and existing online archives; (b) list primary functional requirements; (c) design archive architecture; and (d) develop archive data structure. The archive’s versatile data structure allows for both mobile counters and validation counts of the same traffic flow, an innovation in design that greatly expands the usefulness of the archive

Guiding Data-Driven Transportation Decisions

Urban transportation professionals are under increasing pressure to perform data-driven decision making and to provide data-driven performance metrics. This pressure comes from sources including the federal government and is driven, in part, by the increased volume and variety of transportation data available. This sudden increase of data is partially a result of improved technology for sensors and mobile devices as well as reduced device and storage costs. However, using this proliferation of data for decisions and performance metrics is proving to be difficult. In this paper, we describe a proposed structure for a system to support data-driven decision making. A primary goal of this system is improving the use of human time, effort and attention with side benefits of improved consistency and documentation