Visualization and Travel Time Extraction System for the Statistics of TDCS Travel using MapReduce Framework

TL;DR

This paper presents a system that uses MapReduce to extract and visualize travel time statistics from large vehicle transportation datasets in Taiwan, aiding decision-making for road users.

Contribution

It introduces an interactive visualization system for large-scale transportation data using MapReduce, improving accessibility and interpretability of travel time statistics.

Findings

Effective extraction of travel statistics from big data

Visualization aids in travel time prediction

Supports decision-making for road users

Abstract

Recently, extracting some information as a knowledge from big data is very challenging activity. The size of data is very huge and it requires some special techniques and adequate processing hardware. It is also applied in vehicles transportation data at Taiwan National Freeway from the Traffic Data Collection System (TDCS). The results of this extraction will be very useful if it can be used by the community. So that the delivery of information extracted from large data that is easily understood becomes a necessary thing. Presentation of results using images / visuals will make it easier for people to interpret the information provided. In this project, an interactive visualization of the results of extracting statistical information is attempted to be provided. The results can be used by users to support the decision making of road users in determining the appropriate time when going through the road pieces around the Taichung City. This visualization of the statistics will help people who want to predict the travel time around Taichung City.