GIS-based decision-support tool.

Details

• Creators:
  Abellera, Lourdes V.
• Corporate Creators:
  California State Polytechnic University, Pomona. Dept. of Civil Engineering
• Corporate Contributors:
  University of California Center on Economic Competitiveness in Transportation
• Subject/TRT Terms:
  • Transportation planning
  • Urban transit
  • Urban transportation
  • Advanced traveler information systems
  • Intelligent transportation systems
  • Decision support systems
  • Geographic information systems
  • OCICATS (Online Community Input Classification to Advance
  • Transportation Services)
  • Decision-Support Tool
  More +
• Resource Type:
  Tech Report
• Geographical Coverage:
  California ; United States
• Corporate Publisher:
  California. Department of Transportation
• Description:
  Public transportation agencies can obtain large amounts of information regarding timeliness, efficiency, cleanliness, ridership, and other performance measures. However, these metrics are based on the interests of these agencies and do not necessarily represent the concerns of the customers. Recently, social media have become a platform for people to show their satisfaction or discontent about particular services and products (e.g., Twitter feeds, Yelp reviews, Change.org petitions). This tool was intended to reveal features of ridership that are not evident to transit agencies. For instance, a sense of community and pride are positive aspects of ridership that are not measured by traditional surveys. Specifically, sentiment analysis techniques were utilized to classify numerous sets of rider sentiment data over a period of time and for particular locations (e.g., Metrolink station). Each aspect was shown as a theme in a geographic information system (GIS) layer. This online GIS-based tool can be accessed by transportation planners to determine areas of service where they can focus their resources either for the short term or long term. Project deliverables include an analysis of online social media communications to identify statements regarding public transit ridership; discovery of factors affecting ridership from social media text communications; software documentation including a report describing in detail the developed methodology, results of the software evaluation of correctness, and a summary of novel ridership factors discovered by the system. This research will be featured as an article in ACCESS Magazine.
• Format:
  PDF
• Funding:
  65A0529 TO 028 ; WU no. 3762
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32451/dot_32451_DS1.pdf
• File Type:
  [PDF - 1.55 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:7b0d320aa70f759ad9f4f881e05614ee9938fd4fffb4cc9775ff731bfea7a82f