@proceedings {42,
	title = {Tracking the Transit Rider Experience: Using Smartphones to Measure Comfort and Well-Being Throughout the Trip},
	year = {2015},
	month = {01/2015},
	pages = {15},
	publisher = {Transportation Research Board},
	address = {Washington, D.C.},
	abstract = {<p>An experience sampling method using a smartphone application enables real-time observation of a rider\&rsquo;s trip on transit to identify the triggers causing negative perceptions of personal comfort and wellbeing. Transportation models currently lack the sensitivity for these subtle influences on mode choice. This transit-oriented experience survey demonstrates the ability of this data collection technique to provide a rich qualitative and quantitative dataset that clearly traces the changes in transit rider perception through the entire trip chain, while unobtrusively tracking the participant via global positioning system (GPS). The study involved 60 students who were given a smartphone with the survey app installed. These participants took trips by public transit bus, either on a predefined route or for their day-to-day activities. The smartphone survey successfully captured heightened perceptions of anxiety and discomfort when the participants experienced undesirable situations like boarding a crowded bus, or waiting at a bus stop located on a busy street with few amenities. Attributes of the rider experience, such as their emotional state and wellbeing, were rated by the participants during each state of before, during and after their trip on transit. GPS tracking along with voice and text capture also enabled a contextual understanding of the situation the participants were experiencing. Negative experiences can also influence perception of wait time and travel time during a transit trip. By better understanding rider experience and perceptions, improvements can be made to transit service amenities to provide a more comfortable experience, build rider loyalty, and make transit a more desirable mode choice.</p>
},
	keywords = {I72: Traffic and Transport Planning, Passenger Transportation, Planning and Forecasting, Public Transportation},
	url = {https://trid.trb.org/view.aspx?id=1339490},
	author = {Dunlop, Ian and Casello, Jeffrey M. and Doherty, Shannon}
}
@proceedings {48,
	title = {An Analysis of Stated Preference and GPS Data for Bicycle Travel Forecasting},
	year = {2011},
	month = {01/2011},
	pages = {18},
	publisher = {Transportation Research Board},
	address = {Washington, D.C.},
	abstract = {<p>In this paper, we present preliminary results from an ongoing study of cyclists and cycling in the Region of Waterloo, Ontario Canada. The paper describes two data collection efforts. The first is an on-line survey that provides information on cyclists\&rsquo; demographics as well as their household composition. The survey also gathers data on respondents\&rsquo; motivation for and obstacles to cycling. The second activity collects data on actual cycling trips using GPS units. We describe these units and the steps taken to validate the data. We use the GPS data to produce trip generation and attraction rates for cycling as a function of land use. We also generate a histogram of observed cycling trip lengths that can be used to calibrate a gravity-type model of trip distribution. We then explore the methods by which the survey and GPS data may be combined to develop multi-class and multi-trip purpose generalized cost functions. These formulations may be applied to prioritizing infrastructure investments, as well as for mode and path choice models. We conclude with a discussion of ongoing research work.</p>
},
	keywords = {Data and Information Technology, I72: Traffic and Transport Planning, Pedestrians and Bicyclists, Planning and Forecasting},
	url = {https://trid.trb.org/view.aspx?id=1093054},
	author = {Casello, Jeffrey M. and Nour, Akram and Rewa, Kyrylo and Hill, John}
}
