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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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, they...

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ORcycle is a new smartphone application (for both Android and iOS) developed by Transportation, Technology, and People (TTP) lab researchers at Portland State University as part of an Oregon Department of Transportation (ODOT) research project. ORcycle collects user, route, infrastructure, crash, and safety data. ORcycle was successfully launched in early November 2014 and presents many improvements over existing or similar apps. Initial data findings and insights will be presented. Lessons learned as well as opportunities and challenges associated with smartphone data collection methods will be discussed. More information about the app can be found here: http://www.pdx.edu/transportation-lab/orcycle

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The video begins at 5:40.

Current research at the Institute of Transport and Logistics Analysis of the University of Sydney, under Professor Peter Stopher, has been concentrating on using personal GPS devices to collect travel behaviour data of individuals. In this seminar, Professor Stopher will outline the several projects that have been conducted and are currently underway that are using GPS. He will describe the survey procedures, and then provide an overview of some of the results emerging from collection of such data. Of particular interest is that the GPS surveys are being conducted in most cases by using a panel, with at least two waves of data collection, and that panel members carry the GPS devices for anywhere from one week to one month. Initial studies of the variability in daily travel, where there are no fatigue effects from recording multiple days in a diary, are showing some interesting patterns and leading to some important conclusions.

Peter Stopher is Professor of Transport Planning at the Institute of Transport and Logistics Studies of the University of Sydney, a position he has held since the beginning of 2001. Previously he held academic positions and also worked as a full-time consultant in the USA since 1968. He obtained his B.Sc. (Eng) and Ph.D. from University College London in the 1960s. He has more than 40 years of experience as an educator and consultant in transport...

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PRESENTATION SLIDES

Miss the presentation or want a look back at the slides? You can view them here.

WEBINAR VIDEO

 

This webinar will explain how app-based technologies can improve upon traditional pen-and-paper-based daily transportation diaries in terms of quantity and quality of data collected, particularly for environmental justice populations. The researchers will describe their own efforts, working on an inter-disciplinary team, to develop a custom-designed app, MyAmble, that measures the impact of transportation disadvantage more broadly across access to basic resources, opportunity to participate in wider society, and quality of life. MyAmble includes several innovations – daily digital trip planning, a text-messaging-based qualitative interview tool, and a challenge logger enabling participants to document real-time transportation barriers through videos and photos. Viewers will learn pragmatic strategies for implementing similar app-based ecological momentary assessment transportation data collection tools. In addition, researchers will share lessons learned from working on a technology-based interdisciplinary team.

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Topic: Airsage cell phone data and its application in travel modeling
Summary: As part of the initial phase of development for the Idaho Statewide Travel Demand Model, Parsons Brinckerhoff developed a base year auto and truck trip matrix using AirSage cell phone OD data, a statewide network in Cube, traffic counts, and origin-destination matrix estimation (ODME) procedures. To begin, the 4000+ statewide zone system was aggregated into a 700 super zone system for collecting the cell phone OD data. Next, the cell phone data was collected for the month of September 2013 for the following market segments: Average weekday resident HBW, HBO, NHB, and visitor NHB trips. The cell phone trips were then disaggregated to zones using each zone’s share of super zone population and employment. These initial trip matrices were assigned to the daily statewide network using free flow travel time for route impedance and iteratively adjusted to minimize the difference between the estimated link volumes and traffic counts by user class.

This iterative trip matrix balancing procedure, also known as ODME, converged nicely by user class and facility type and produced reasonable flows. The...

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