Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/72797
Title: Big data analytics for smart transportation
Authors: Tan, Aaron Zheng-Kai
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2017
Abstract: The emergence of private cars for hire companies such as Uber and Grab have been disrupting the taxi industry around the world. These affected taxi drivers usually do not have other means of earning a living. Additional competition have brought their incomes down drastically. This impact is also felt in Singapore, and this project aims to alleviate this disruption by improving taxi efficiency through taxi ridesharing. In this project, the taxi ridesharing concept will be discussed, along with its associated quantifiable and non-quantifiable benefits. A simulation system for the concept is proposed, together with its possible real world implementation. Insights gained from this simulation system will be analyzed, as well as applications to achieve efficiency for taxi drivers are explored.
URI: http://hdl.handle.net/10356/72797
Schools: School of Computer Science and Engineering 
Organisations: LTA
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Amended_Final_Report_TanZhengKaiAaron.pdf
  Restricted Access
Amended Final Report4.8 MBAdobe PDFView/Open

Page view(s)

410
Updated on Mar 17, 2025

Download(s) 50

44
Updated on Mar 17, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.