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 | Size | Format | |
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Amended_Final_Report_TanZhengKaiAaron.pdf Restricted Access | Amended Final Report | 4.8 MB | Adobe PDF | View/Open |
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