USA Rail Planner: A user-focused web-scraping solution for rail travel planning in the United States
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Authors
Alvarez, Nicholas
Issue Date
2022
Type
Thesis
Language
Keywords
data collection , human computer interaction , itinerary planning , rail transportation , travel planning , web mining
Alternative Title
Abstract
Planning a cross-country train journey in the United States can be a time-consuming process. The USA Rail Planner, presented in this thesis, provides travelers an easy way to plan a multi-city rail trip to any of the destinations served by Amtrak trains in the United States. The manual work of searching the Amtrak website and inputting information into a spreadsheet is no longer necessary. By interfacing with the website, information can be parsed by the application quickly and presented to the user in a simpler, ordered, and less cluttered format, allowing them to make educated decisions in their trip planning process. Dynamic route maps, detailed train information, and many other planning features are present in the application. Quality-of-life additions, such as train timetables, city tourism pages, and local transit connections, make the application well-rounded in the tourism and travel domains. Furthermore, this user-centered Python-based application that employs web scraping and other modern software technologies provides an efficient and easy way to create an itinerary which can be exported later. User study results (N=12) show that the USA Rail Planner is significantly better than existing methods, reducing the time to create an itinerary by 47% and it was the preferred method for all but one participant.
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Citation
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License
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 United States