Map-matching system design & implementation
Transportation data analytics has become increasingly important in the modern metropolis like Singapore. As a modern city with huge amount population and vehicle, large amount transportation data will be generated and can be used in data analysis. These analytical results can help in many areas s...
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sg-ntu-dr.10356-714682023-07-07T16:21:37Z Map-matching system design & implementation Zhao, Huangjie Yap Kim Hui School of Electrical and Electronic Engineering Li Mo DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer system implementation Transportation data analytics has become increasingly important in the modern metropolis like Singapore. As a modern city with huge amount population and vehicle, large amount transportation data will be generated and can be used in data analysis. These analytical results can help in many areas such as route planning, urban planning, behaviour prediction, and various kinds of application design. With the support of data analysis technics, these knowledges can help in developing a more effective and efficient transportation system and meet the demand of the gradually developing metropolis. One topic of transportation data analytics is Map-Matching. The motivation of this area is to reduce the noise of the received GPS data and retrieve more information related to a given GPS data point with the help of digital map. These new knowledges mined from GPS points can help in other analysis such as transportation pattern mining, road transportation volume prediction and many other areas. The focus of this project is to reduce the noise of GPS data of taxis in Singapore. The projects aim to develop a system that takes taxi trajectory data, i.e., a list of GPS coordinates, as input and output the predicted traversing information of the taxi along the digital map. Bachelor of Engineering 2017-05-17T01:45:16Z 2017-05-17T01:45:16Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71468 en Nanyang Technological University 48 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer system implementation Zhao, Huangjie Map-matching system design & implementation |
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Transportation data analytics has become increasingly important in the modern
metropolis like Singapore. As a modern city with huge amount population and
vehicle, large amount transportation data will be generated and can be used in data
analysis. These analytical results can help in many areas such as route planning,
urban planning, behaviour prediction, and various kinds of application design. With
the support of data analysis technics, these knowledges can help in developing a
more effective and efficient transportation system and meet the demand of the
gradually developing metropolis.
One topic of transportation data analytics is Map-Matching. The motivation of this
area is to reduce the noise of the received GPS data and retrieve more information
related to a given GPS data point with the help of digital map. These new
knowledges mined from GPS points can help in other analysis such as transportation
pattern mining, road transportation volume prediction and many other areas.
The focus of this project is to reduce the noise of GPS data of taxis in Singapore.
The projects aim to develop a system that takes taxi trajectory data, i.e., a list of GPS
coordinates, as input and output the predicted traversing information of the taxi along
the digital map. |
author2 |
Yap Kim Hui |
author_facet |
Yap Kim Hui Zhao, Huangjie |
format |
Final Year Project |
author |
Zhao, Huangjie |
author_sort |
Zhao, Huangjie |
title |
Map-matching system design & implementation |
title_short |
Map-matching system design & implementation |
title_full |
Map-matching system design & implementation |
title_fullStr |
Map-matching system design & implementation |
title_full_unstemmed |
Map-matching system design & implementation |
title_sort |
map-matching system design & implementation |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/71468 |
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1772826832834396160 |