The emergence of cell phones with embedded Global Positioning System (GPS) chips provides opportunities to push personalized real-time travel information subject to an individual's current location. One such application, a travel assistant device, notifies cognitively disabled public transportation users when it is time to request a stop and exit the vehicle. GPS-enabled cell phones must provide highly accurate real-time location data for this type of service. The components used in the data-collection process are identified, and a quantitative analysis of real-time GPS data obtained with a cell phone while walking, driving a vehicle, and riding public transportation is provided. The expectation was that position accuracy would suffer when the GPS signal was obstructed by a vehicle or the user's clothing. The obtained data demonstrate the results of location fix attempts over different transportation modes in an urban environment. The highest percentage of GPS fixes (79.0%) was obtained by users walking with the cell phone open and unobstructed; walking also produced valid GPS data (i.e., location data estimated to be accurate within 30 m of the true position) 66.2% of the time. For bus trips, GPS and valid fix percentages were 71.7% and 66.1%, respectively, when the phone was held near the window; when the phone was placed in the traveler's lap, these numbers fell to 51.3% and 27.8%, respectively. Car trips provided higher numbers: 77.7% and 71.6%, respectively. Location-based transportation applications are feasible using current technology, but predictive algorithms may be required to deliver highly accurate and timely location-aware services to cell phone users in highly obstructed environments.