A Survey of Traffic Data Visualization

Author

Wei Chen ; Fangzhou Guo ; Fei-Yue Wang

Author_Institution

State Key Lab. of Comput. Aided Design & Comput. Graphics, Zhejiang Univ., Hangzhou, China

Volume

16

Issue

6

fYear

2015

Firstpage

2970

Lastpage

2984

Abstract

Data-driven intelligent transportation systems utilize data resources generated within intelligent systems to improve the performance of transportation systems and provide convenient and reliable services. Traffic data refer to datasets generated and collected on moving vehicles and objects. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. This paper introduces the basic concept and pipeline of traffic data visualization, provides an overview of related data processing techniques, and summarizes existing methods for depicting the temporal, spatial, numerical, and categorical properties of traffic data.

Keywords

data visualisation; intelligent transportation systems; traffic information systems; categorical properties; data hidden patterns; data processing technique; data resources; data-driven intelligent transportation system; dataset distribution; dataset structure; moving objects; moving vehicles; numerical properties; spatial properties; temporal properties; traffic data visualization; Data analysis; Data collection; Data preprocessing; Data visualization; Query processing; Visual analytics; Traffic; data-driven intelligent transportation system; traffic data visualization; visual analysis;

fLanguage

English

Journal_Title

Intelligent Transportation Systems, IEEE Transactions on

Publisher

ieee

ISSN

1524-9050

Type

jour

DOI

10.1109/TITS.2015.2436897

Filename

7120975