@proceedings {41, title = {Developing and Optimizing a Transportation Mode Inference Model Utilizing Data from GPS Embedded Smartphones}, year = {2015}, month = {01/2015}, pages = {16}, publisher = {Transportation Research Board}, address = {Washington, D.C.}, abstract = {

Advances in wireless communications and technologies provide the opportunity to collect detailed information on travel trajectory using smart-phones equipped with GPS and accelerometers. These types of smart-phones are ubiquitous and, as such, present an opportunity to conveniently collect spatial and temporal data at regular time intervals. This can be useful to utilize as a method to document travel behavior \– origin, destination, departure time, route choice, trip purpose, and mode choice. One of the challenges that has been addressed in the literature is how to identify the transportation mode of travel. This paper presents a data-driven classification model to infer transportation mode choice from data collected with GPS equipped smart phones. Rather than making a priori assumptions, the authors instead employ an optimization method to objectively produce the following classifier components and methods: a ranked feature vector based on the power of differentiation between different modes; the classification technique between the range of candidate classifiers; the number of ranked attributes to include in the feature vector; data formatting; and optimal model parameters. The model is trained and tested using known transportation mode segments \– limits of travel by a given mode. The calibrated model is evaluated by testing its ability to classify travel mode correctly for GPS data at a different level of disaggregation than the one used in the model training step. The model provides an accuracy of approximately 86\% at the disaggregated level (e.g. Walk, Bike, Transit, and Private Automobile) and approximately 94\% at aggregated level (e.g. Non-Motorized and Motorized.)

}, keywords = {Data and Information Technology, Highways, I72: Traffic and Transport Planning, Pedestrians and Bicyclists, Public Transportation}, url = {https://trid.trb.org/view.aspx?id=1338992}, author = {Nour, Akram and Casello, Jeffrey M. and Hellinga, Bruce} } @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 = {

An experience sampling method using a smartphone application enables real-time observation of a rider\’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.

}, 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 {46, title = {The Influence of Ownership and Business Models on Achieving Transit Improvements}, year = {2012}, month = {01/2012}, pages = {14}, publisher = {Transportation Research Board}, address = {Washington, D.C.}, abstract = {

In recent years, several cities in Mexico have embarked on a series of public transport initiatives to improve operations in road-based urban transportation directed to a more centrally regulated provision. Implementation of these improvements is contentious because of informal transport suppliers\’ reluctance to enter into such modifications. This paper assesses three ownership models\’ impacts on informal transport suppliers\’ willingness to participate in bus improvements. The models are: (1) a man-and-his bus, in which the owner of the concession operates and manages a single unit; (2) a concession and vehicle lease, in which a driver leases the vehicle from and pays a service fee to the concession holder for the right to operate the unit; and (3) a concession-only lease, in which the driver pays a monthly set amount for the right to operate. From this assessment, the authors conclude that greater opportunities exist to engage informal transport suppliers in a desired public transport initiative in places where models (2) and (3) exist rather than model (1). Converting from model (1) to centralized operations represents a loss of social status which is not felt to the same extent when converting from models (2) or (3). Finally, they note that many areas in Mexico are served by illegal but tolerated private operations. These cases present opportunities to introduce an improved service because governments may persuade those operating illegally to participate in legal franchise systems.

}, keywords = {Administration and Management, Passenger Transportation, Public Transportation}, url = {https://trid.trb.org/view.aspx?id=1129982}, author = {Lopez Dodero, Abel and Casello, Jeffrey M. and Molinero Molinero, Angel R. and Santiago-Rodr{\'\i}guez, Deborah} } @proceedings {49, title = {The Development and Deployment of GIS Tools to Facilitate Transit Network Design and Operational Evaluation}, year = {2010}, month = {01/2010}, pages = {21}, publisher = {Transportation Research Board}, address = {Washington, D.C.}, abstract = {

With the growth of Geographic Information Systems (GIS) in transportation analysis,opportunities exist to utilize GIS functionality specifically in transit planning. In this paper, we present two GIS tools which are now in use in the Regional Municipality of Waterloo, Ontario. The first tool addresses the transit network design problem. The approach utilizes GIS to identify desire lines or major travel demand corridors from which trunk transit routes are proposed and evaluated. The second tool is also designed to analyze travel patterns between activity centers concentrating on the need for and user costs of transfers. For any origin destination pair, the tool utilizes GIS functions to determine where transfers are required as well as the physical distance and expected travel delay (based on scheduled times) to complete the transfer. The GIS tools were built using VBA scripting in ArcMap 9.3 part of ESRI\’s general ArcGIS suite. The tools offer proven methodologies for use within transit network design and evaluation at a level of resource requirement that is consistent with most transit agencies. The customization of the tools in GIS has facilitated repetitive tasks and requires little training in its use. Further, the tools can be adapted for use in any transit agency and are customizable to local conditions.

}, keywords = {Data and Information Technology, Public Transportation}, url = {https://trid.trb.org/view.aspx?id=910619}, author = {Simard, Stephanie and Springate, Erica and Casello, Jeffrey M.} }