Abstract:
"Current applications for organizing road trips often provide general suggestions and
schedules, not considering the preferences of individual travellers. When users are
unable to find hidden gems and customize their travels to suit their unique interests and
travel preferences, they feel as though they have lost out on important opportunities.
To overcome this problem, this project will create a road trip planner and navigator
application that puts an emphasis on customization and gives users the ability to create
unforgettable trips.
To identify the common problems and preferences of road trippers, a thorough
investigation was conducted at the start of the project, involving surveys and user
interviews. These insights informed design decisions, which centred on elements such
as intelligent route suggestions, user preference profiles, and the incorporation of
unusual, off-the-beaten-path points of interest. Python and its surrounding ecosystem
were essential for applying machine learning algorithms and analysing data. MySQL
offered a dependable database, and Flask was chosen for its flexibility in building web
applications. The Google Maps API was integrated for its robust mapping and
navigation features, and the user interface was designed using HTML, CSS, and
JavaScript.
The project produced a workable web application prototype that promotes
customization. Routes and destinations can be customized by the application using
machine learning to match user preferences. The development of an easy-to-use
interface and a flawless user experience were prioritized. The process of development
reaffirmed the significance of user feedback loops, iterative design, and the utilization
of machine learning to augment user satisfaction in the context of travel planning."
