Interactive Maps for Visualizing Optimal Route Planning Strategy

Information

• Publication Type: Bachelor Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: October 2018
• Date (Start): 23. May 2018
• Date (End): 26. October 2018
• Matrikelnummer: 01426939
• First Supervisor: Hsiang-Yun Wu

Abstract

There are many situations in our everyday life like events, concerts, landmarks, attraction parks, etc. that often require from visitors to line-up in front of long queues and thus spend hours in waiting. An example of that are the Disneyland amusement parks. They are all very popular and attract a significant number of people every day. For this reason, the lining-up in front of attractions may cost much time – even up to a couple of hours. Despite that, the Disneyland parks are visited by millions of people every year [sta]. So to avoid so much waiting they need to make a plan in advance – when and in which order to visit the wanted attractions. However, to make such a plan, it could be very time consuming, difficult and even unpleasant, because many prerequisites need to be considered in advance. Having the main problems and annoyances described, the goal of this thesis is to create an assisting application. Its purpose is to give the visitors the possibility to create their own plan for their visit to Tokyo Disneyland. It contains two main assisting components. Firstly, an optimization algorithm calculating an optimized route of the chosen attractions as well as a route visualization for an easy attraction finding. Both will reduce the time for lining-up and pre-planning. Such a technique will make it easier for visitors to see as many attractions as possible for a single day and thus, make the most of their visit.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@bachelorsthesis{Vasileva-2018,
  title =      "Interactive Maps for Visualizing Optimal Route Planning
               Strategy",
  author =     "Elitza Vasileva",
  year =       "2018",
  abstract =   "There are many situations in our everyday life like events,
               concerts, landmarks, attraction parks, etc. that often
               require from visitors to line-up in front of long queues and
               thus spend hours in waiting. An example of that are the
               Disneyland amusement parks. They are all very popular and
               attract a significant number of people every day. For this
               reason, the lining-up in front of attractions may cost much
               time – even up to a couple of hours. Despite that, the
               Disneyland parks are visited by millions of people every
               year [sta]. So to avoid so much waiting they need to make a
               plan in advance – when and in which order to visit the
               wanted attractions. However, to make such a plan, it could
               be very time consuming, difficult and even unpleasant,
               because many prerequisites need to be considered in advance.
               Having the main problems and annoyances described, the goal
               of this thesis is to create an assisting application. Its
               purpose is to give the visitors the possibility to create
               their own plan for their visit to Tokyo Disneyland. It
               contains two main assisting components. Firstly, an
               optimization algorithm calculating an optimized route of the
               chosen attractions as well as a route visualization for an
               easy attraction finding. Both will reduce the time for
               lining-up and pre-planning. Such a technique will make it
               easier for visitors to see as many attractions as possible
               for a single day and thus, make the most of their visit.",
  month =      oct,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2018/Vasileva-2018/",
}