Open AccessDriver's dashboard – using social media data as additional information for motorway operators
Author(s) -
Neuhold Robert,
Gursch Heimo,
Kern Roman,
Cik Michael
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2018.5337
Subject(s) - dashboard , social media , rss , computer science , web traffic , operator (biology) , data collection , transport engineering , visibility , world wide web , data science , engineering , geography , the internet , biochemistry , chemistry , statistics , mathematics , repressor , transcription factor , meteorology , gene
Data collection on motorways for traffic management operations is traditionally based on local measurement points and camera monitoring systems. This work looks into social media as an additional data source for the Austrian motorway operator ASFINAG. A system called Driver's Dashboard was developed collecting incident descriptions from Facebook and RSS feeds, filtering relevant messages, and fusing them with traffic data. All collected texts were analysed for concepts describing road situations linking the texts from the web and social media with traffic messages and traffic data. Driver's Dashboard was designed to examine the potential of social media for traffic monitoring with respect to Austrian characteristics in social media use and road transportation with only very few messages available compared with other studies. Of 3586 messages collected within a five‐week period, only 7.1% were automatically annotated as traffic relevant. Furthermore, the traffic relevant messages for the motorway operator were analysed more in detail to identify correlations between message text and traffic data characteristics. A correlation between message text and traffic data was found in nine of 11 messages by comparing the speed profiles and traffic state data with the message text.