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Accessible Transportation Technologies Research Initiative (ATTRI): State of the Practice Scan

Joseph Andrew Giampapa, Aaron Steinfeld, Ermine Teves, M. Bernardine Dias and Zachary Rubinstein
CMU-RI-TR-17-15, Carnegie Mellon University, April, 2017

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The Accessible Transportation Technologies Research Initiative (ATTRI) focuses on research to
improve the independent mobility of travelers with disabilities through the use of ITS and other
advanced technologies. This report is one of three intended to provide an overview of
technologies, innovations, and research that are applicable to the ATTRI vision. The particular
focus of this report is on a State of the Practice Scan [SOP], to survey technologies that are
currently in use on a wide scale within the United States. This document also contains
characterizations of the challenges that face the stakeholders. Descriptions of user experiences
with SOP technologies are determined by broad surveys of the user population.

The overall organization of this report echoes the organization of the overall ATTRI effort.
ATTRI focuses on five technology areas to improve transportation for persons of its three
stakeholder groups – people with disabilities, veterans with disabilities, and older adults: (1)
Wayfinding and Navigation, (2) ITS and Assistive Technologies, (3) Automation and Robotics,
(4) Data Integration, and (5) Enhanced Human Service Transportation. Review of each of the
five technology areas considers the applicability of such technologies to four transportation
modalities that ATTRI stakeholders encounter: (1) Transit, (2) Personal Vehicles, (3) First / Last
Mile, and (4) Pedestrian. Where necessary, a cross-cutting modality category is also included.

BibTeX Reference
title = {Accessible Transportation Technologies Research Initiative (ATTRI): State of the Practice Scan},
author = {Joseph Andrew Giampapa and Aaron Steinfeld and Ermine Teves and M. Bernardine Dias and Zachary Rubinstein},
keyword = {Accessible transportation, technology, community travel, international scan, best practices},
school = {Robotics Institute , Carnegie Mellon University},
month = {April},
year = {2017},
number = {CMU-RI-TR-17-15},
address = {Pittsburgh, PA},