Mobile Transit Information from Universal Design and Crowdsourcing

Extensive interviews with riders of the Pittsburgh, Pennsylvania, bus system revealed that, as the top priority, riders wanted to know the actual arrival time of buses. Following a universal design approach, a system called Tiramisu was created to foster a greater sense of community between riders and transit bus service providers. The design focused on acquisition of crowdsourced information for bus location and bus fullness. On the basis of that input, the system predicted the arrival time of buses and provided a convenient platform for reporting problems and positive experiences within the transit system. The intention was to create a community of riders that materially participated in the delivery of the transit service. Tiramisu also supported specific information and reporting needs for riders with disabilities and thereby provided greater independent mobility around the community. An early field trial of Tiramisu suggested that the approach was both feasible and potentially viable.

[1]  Daren C. Brabham,et al.  Crowdsourcing Public Participation in Transit Planning: Preliminary Results from Next Stop Design Case , 2010 .

[2]  John Zimmerman,et al.  Swarthmore College , 2012 .

[3]  Chao Li,et al.  Modeling context aware interaction for wayfinding using mobile devices , 2006, Mobile HCI.

[4]  Philip L Winters,et al.  Travel Assistance Device (TAD) to Help Transit Riders - Deployment to transit agencies , 2010 .

[5]  Michael Freed,et al.  RADAR: A Personal Assistant that Learns to Reduce Email Overload , 2008, AAAI.

[6]  Billie Louise Bentzen,et al.  New orientation and accessibility option for persons with visual impairment: transportation applications for remote infrared audible signage , 2001, Clinical & experimental optometry.

[7]  Vinayak Dixit,et al.  Issues, Practices, and Needs for Communicating Evacuation Information to Vulnerable Populations , 2010 .

[8]  Edward Steinfeld,et al.  Modality Preference for Rider Reports on Transit Accessibility Problems , 2010 .

[9]  Edward Steinfeld,et al.  The value and acceptance of citizen science to promote transit accessibility , 2010 .

[10]  Aaron Steinfeld,et al.  Evaluation of an integrated multi-task machine learning system with humans in the loop , 2007 .

[11]  S. Kiesler,et al.  Applying Common Identity and Bond Theory to Design of Online Communities , 2007 .

[12]  Philip L Winters,et al.  Global Positioning System Integrated with Personalized Real-Time Transit Information from Automatic Vehicle Location , 2010 .

[13]  Aaron Steinfeld,et al.  Interaction Development for a Public Transit Rider Reporting System , 2010 .

[14]  Alan Borning,et al.  OneBusAway: results from providing real-time arrival information for public transit , 2010, CHI.

[15]  James Biagioni,et al.  TransitGenie: a context-aware, real-time transit navigator , 2009, SenSys '09.

[16]  David Feathers,et al.  Space Requirements for Wheeled Mobility Devices in Public Transportation: Analysis of Clear Floor Space Requirements , 2010 .

[17]  John Zimmerman,et al.  Understanding the space for co-design in riders' interactions with a transit service , 2010, CHI.

[18]  Alexander Repenning,et al.  Mobility agents: guiding and tracking public transportation users , 2006, AVI '06.

[19]  C. Casey REAL-TIME INFORMATION : NOW ARRIVING , 2003 .

[20]  A S Iannuzziello Communicating with Persons with Disabilities in a Multimodal Transit Environment , 2001 .

[21]  Alan Borning,et al.  Location-Aware Tools for Improving Public Transit Usability , 2010, IEEE Pervasive Computing.

[22]  Masood Masoodian,et al.  An Empirical Study of Textual and Graphical Travel Itinerary Visualization using Mobile Phones , 2003, AUIC.