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Automated Incident Detection Using Real-Time Floating Car Data
Joint Authors
Houbraken, Maarten
Logghe, Steven
Schreuder, Marco
Audenaert, Pieter
Colle, Didier
Pickavet, Mario
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-11
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The aim of this paper is to demonstrate the feasibility of a live Automated Incident Detection (AID) system using only Floating Car Data (FCD) in one of the first large-scale FCD AID field trials.
AID systems detect traffic events and alert upcoming drivers to improve traffic safety without human monitoring.
These automated systems traditionally rely on traffic monitoring sensors embedded in the road.
FCD allows for finer spatial granularity of traffic monitoring.
However, low penetration rates of FCD probe vehicles and the data latency have historically hindered FCD AID deployment.
We use a live country-wide FCD system monitoring an estimated 5.93% of all vehicles.
An FCD AID system is presented and compared to the installed AID system (using loop sensor data) on 2 different highways in Netherlands.
Our results show the FCD AID can adequately monitor changing traffic conditions and follow the AID benchmark.
The presented FCD AID is integrated with the road operator systems as part of an innovation project, making this, to the best of our knowledge, the first full chain technical feasibility trial of an FCD-only AID system.
Additionally, FCD allows for AID on roads without installed sensors, allowing road safety improvements at low cost.
American Psychological Association (APA)
Houbraken, Maarten& Logghe, Steven& Schreuder, Marco& Audenaert, Pieter& Colle, Didier& Pickavet, Mario. 2017. Automated Incident Detection Using Real-Time Floating Car Data. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1171007
Modern Language Association (MLA)
Houbraken, Maarten…[et al.]. Automated Incident Detection Using Real-Time Floating Car Data. Journal of Advanced Transportation No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1171007
American Medical Association (AMA)
Houbraken, Maarten& Logghe, Steven& Schreuder, Marco& Audenaert, Pieter& Colle, Didier& Pickavet, Mario. Automated Incident Detection Using Real-Time Floating Car Data. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1171007
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1171007