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Full-Text Articles in Engineering
Webinar: Segmenting The Market For Transportation Demand Management Campaigns, Philip L. Winters, Amy Lester
Webinar: Segmenting The Market For Transportation Demand Management Campaigns, Philip L. Winters, Amy Lester
TREC Webinar Series
Social marketing seeks to develop and integrate marketing concepts with other approaches to influence behaviors that benefit individuals and communities for the greater social good. It is a useful transportation demand management (TDM) planning approach to promote travel behavior change. The purpose of this study was to explore a consumer market segmentation technique successfully used in Europe for its applicability to marketing efforts in the United States. Attitudinal and demographic data were collected from 1900 individuals in Florida, Oregon, and Virginia modeled after the European approach. Clustering analysis was applied to divide the sample into segments so that members of …
Webinar: Meeting & Exceeding Mobility User Expectations With Real-Time Transit Information, Sean J. Barbeau, Derek Fretheim
Webinar: Meeting & Exceeding Mobility User Expectations With Real-Time Transit Information, Sean J. Barbeau, Derek Fretheim
TREC Webinar Series
Every day transit riders ask the same question: when’s the next one coming? To answer this question, transit agencies are transitioning to providing real-time transit information through smartphones or displayed at transit stops.
The proliferation of transit planning and real time arrival tools that have hit the market over the past decade is staggering. Yet with transit ridership on the decline, agencies can’t afford to ignore the importance of providing accurate, real time information to their customers. Real-time transit information improves the reliability and efficiency of passenger travel, but barriers have prevented some transit agencies from adopting the GTFSrealtime v1.0 …
Transit Demand Analysis And User Classification Using Automatic Fare Collection (Afc) Data, Alireza Khani
Transit Demand Analysis And User Classification Using Automatic Fare Collection (Afc) Data, Alireza Khani
PSU Transportation Seminars
Development of origin-destination demand matrices is crucial for transit planning. The development process is facilitated by transit automated data, making it possible to mine boarding and alighting patterns on an individual basis. This research proposes a novel stochastic trip chaining method which uses Automatic Fare Collection (AFC) and General Transit Feed Specifications (GTFS) data to infer an origin-destination (O-D) matrix.