Post date: Mon, 12/04/2017 - 2:28pm
Event Date:
Content Type: News Item
Principal Investigator: Liming Wang, Portland State University
Learn more about this curriculum and how you can apply it at your school by viewing the one-page Executive Summary and the full Final Report on the Project Overview page.

A NITC education grant funded a new course for planners, engineers, scientists and students to help improve their data processing workflow.

Liming Wang, an assistant professor in the Toulan School of Urban Studies & Planning at Portland State University, is on a mission to simplify data processing. A NITC education grant supported his efforts to develop a new course: Introduction to Data Science. The course is designed to help students and professionals to improve their workflow for data-intensive research. The course covers how to collect data, clean them up, visualize, explore, model and eventually compile the data with findings in a report.

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Post date: Sun, 09/17/2017 - 12:36pm
Event Date:
Oct 06, 2017
Content Type: Events

SEMINAR VIDEO


SEMINAR SLIDES
Missed the presentation or want to look back at the slides? View the slides here.

Travel times, operating speeds, and service reliability influence costs and service attractiveness. This research outlines an approach to quantify how these metrics change after a modification of roadway design or transit routes using archived transit data. The Tri-County Metropolitan Transportation District of Oregon (TriMet), Portland’s public transportation provider, archives automatic vehicle location (AVL) data for all buses as part of their bus dispatch system (BDS). This research combines three types of AVL data (stop event, stop disturbance, and high-resolution) to create a detailed account of transit behavior; this probe data gives insights into the behavior of transit as well as general traffic....

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Post date: Mon, 06/05/2017 - 5:28pm
Event Date:
Jun 12, 2017
Content Type: Event (discontinue usage)

The Portland State University Department of Civil and Environmental Engineering is pleased to announce that NITC dissertation fellow Kristina Currans will defend her PhD Dissertation: "Data and Methodological Issues in Assessing Multimodal Transportation Impacts for Urban Development."

Advisor: Dr. Kelly J. Clifton

Since its first edition in 1976, the Institute of Transportation Engineers (ITE) Trip Generation Handbook has become the predominant method for estimating the transportation impacts of land use, despite the lack of sensitivity to changes in the urban environments. As a result, local governments continue to be hampered by the urban application of the Handbook, overestimating (and overcharging for) automobile facilities, creating additional barriers to achieving multimodal or sustainable comprehensive plans. This dissertation explores the spatial, social, and temporal contexts of ITE’s Handbook, quantifying variations in vehicle trip generation estimates where...

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Post date: Tue, 05/30/2017 - 1:13pm
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Content Type: News Item

As social media comes to permeate every aspect of modern life, public transit is no exception.

Transit agencies are increasingly making social media an integral part of their day-to-day management, using it to connect with riders about system alerts, live transit arrival information, service disruptions and customer feedback.

However, there is very little evidence to show how effective these efforts really are in achieving agency goals.

Measuring the Impacts of Social Media on Advancing Public Transit, a NITC project led by Jenny Liu of Portland State University, seeks to provide a better understanding of how transit agencies use social media and to develop some performance measures to assess the impacts of social media on promoting public transit.

This project aims to measure how social media actually impacts agency goals like increasing recruitment and retention of transit riders; increasing resources and customer satisfaction; addressing system performance efficiency; and improving employee productivity and morale.

A survey of 27 public transportation providers across the country found that although 94% of those surveyed agencies used some form of social media, only 28% had a social media plan or strategy prior to implementation.

Liu’s research explores the types of performance measures that could...

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Post date: Fri, 12/23/2016 - 11:39am
Event Date:
Mar 03, 2017
Content Type: Events

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New technologies such as smart phones and web applications constantly collect data on individuals' trip-making and travel patterns. Efforts at using these "Big data" products, to date, have focused on using them to expand or inform traditional travel demand modeling frameworks; however, it is worth considering if a new framework built to maximize the strengths of big data would be more useful to policy makers and planners.

In this presentation Greg Macfarlane will present a discussion on elements of travel models that could quickly benefit from big data and concurrent machine learning techniques, and results from a preliminary application of a prototype framework in Asheville, North Carolina.

Dr. Macfarlane is an analyst in the Systems Analysis Group of WSP | Parsons Brinckerhoff, developing and applying advanced travel demand models. His research and expertise includes trip-based models, activity-based models, integrated...

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Post date: Mon, 11/14/2016 - 10:56pm
Event Date:
Dec 13, 2016
Content Type: Events

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If you would like to receive continuing education credits such as PDH or CM, please make sure to complete this evaluation form once you've watched the entire video so that we have a record of your attendance.

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Post date: Tue, 10/11/2016 - 12:11pm
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Content Type: News Item

A new NITC report introduces an important tool for safety analysis: a naturalistic method of data collection that can be used to improve the cycling experience.

Before now, most naturalistic studies (studies where data are collected in a natural setting, rather than a controlled setting) in bicycle safety research have been captured by stationary cameras and haven't followed cyclists along a route.

Researchers in this study used first-person video and sensor data to measure cyclists' reactions to specific situations.

Safety research in general has advanced significantly through naturalistic driving studies, which gather data from real drivers to illuminate the causes of traffic incidents both major and minor. For motorized vehicles, the U.S. Department of Transportation has been developing portable, vehicle-based data collection technologies since the early 1990s.

Portland State University researchers Feng Liu, Miguel Figliozzi and Wu-chi Feng sought to capture the cycling experience with physiological sensors and helmet-mounted cameras.

Their report, Utilizing Ego-centric Video to Conduct Naturalistic Bicycling Studies, offers a successful method for integrating video and sensor data to record...

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Post date: Mon, 09/19/2016 - 2:40pm
Event Date:
Oct 28, 2016
Content Type: Events

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Post date: Tue, 04/26/2016 - 8:26am
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Content Type: News Item

NITC researchers have tested a method of collecting transportation behavior data using a smartphone app, with promising results.

The process could save transit agencies “hundreds of thousands of dollars,” says lead researcher Christopher Bone, and give them access to comprehensive, real-time data about their ridership, all without compromising passengers’ privacy.

Christopher Bone, Marc Schlossberg, Ken Kato, Jacob Bartruff and Seth Kenbeek of the University of Oregon designed a custom mobile application, which allows passengers to volunteer information about their travel habits, and recruited passengers to use it in a test case.

Their report, “Crowdsourcing the Collection of Transportation Behavior Data,” was released this month.

Download it here.

Participants were asked to use the app for three weeks on Lane Transit District’s EmX bus line located in the Eugene-Springfield area in western Oregon. Researchers placed sensors on the buses and at stops to detect when someone using the app was boarding. When a user came within range of a sensor,...

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Post date: Mon, 01/04/2016 - 6:24pm
Event Date:
Content Type: News Item

Traffic congestion on urban roadways can influence operating costs and cause travel delays.

Portland State University master’s students Nicholas Stoll and Travis Glick will present a paper introducing solutions for locating the sources of congestion at the 2016 annual meeting of the Transportation Research Board.

With their faculty advisor, Miguel Figliozzi, Stoll and Glick looked into using bus GPS data to identify congestion hot spots.

By using high-resolution GPS data to visualize trends in bus behavior and movement, the researchers were able to examine the sources of delay on urban arterials.

These visualizations, which can be in the form of heat maps or speed plots like the one shown here on the right (an application of numerical method applied to a 2,000 ft segment of SE Powell), can be used by transportation agencies to identify locations where improvements are needed. For example, adding a queue jump lane at a congested intersection can improve flow.

The researchers used fine-grained bus data provided by TriMet to create the visualizations. Buses have been used as probes to estimate...

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