Traffic congestion, high gas price and inadequate public transportation are major challenges for any country, business or individual. The traditional approach to solving these problems has been to improve public transportation and use greener energy. These approaches require huge investment, research and time, and can only be carried out by governments or businesses. An alternative solution seeks to reduce the number of vehicles on the road based on ridesharing. Nevertheless, ridesharing is not a popular form of public transportation. A ridesharing application involves planning and collaboration in setting up rides. Some of the concerns of users of these applications are social discomfort that arises due to lack of trust amongst co-passengers and inconvenience in scheduling rides.
In this work we are trying to understand the perceptions of trust in a software application that integrates collaboration and social networks. We conducted a rideshare needs assessment survey conducted within the Virginia Tech community. The purpose behind this survey was to understand commuters travel patterns, their needs and to identify their preferences for private vehicles and public transit for a variety of travel needs. The survey results indicate that users are willing to increase participation in ridesharing programs if three core issues are addressed trust, convenience and incentives. Based on the results and analysis of our survey results we present an iPhone based ridesharing application that would leverage social networks to embed trust. To overcome the complexity in scheduling rides, we have made our application available on mobile phones (iPhone) so that users are connected on the go and make use of GPS for location awareness to plan their rides instantaneously. Our social software application is easy and intuitive to use, helps users find trusted rideshares and reduces the carbon footprint of the individual. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/34497 |
| Date | 14 September 2010 |
| Creators | Chaube, Vineeta |
| Contributors | Computer Science, Kavanaugh, Andrea L., McCrickard, D. Scott, Pérez-Quiñones, Manuel A. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | Chaube_V_T_2010.pdf |
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