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Automated incident detection using real-time floating car data

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Abstract
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 FCDAID 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.
Keywords
TRAVEL-TIME, LOOP DETECTORS, NETWORK, IBCN

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MLA
Houbraken, Maarten, et al. “Automated Incident Detection Using Real-Time Floating Car Data.” JOURNAL OF ADVANCED TRANSPORTATION, vol. 2017, 2017, doi:10.1155/2017/8241545.
APA
Houbraken, M., Logghe, S., Schreuder, M., Audenaert, P., Colle, D., & Pickavet, M. (2017). Automated incident detection using real-time floating car data. JOURNAL OF ADVANCED TRANSPORTATION, 2017. https://doi.org/10.1155/2017/8241545
Chicago author-date
Houbraken, Maarten, Steven Logghe, Marco Schreuder, P. Audenaert, Didier Colle, and Mario Pickavet. 2017. “Automated Incident Detection Using Real-Time Floating Car Data.” JOURNAL OF ADVANCED TRANSPORTATION 2017. https://doi.org/10.1155/2017/8241545.
Chicago author-date (all authors)
Houbraken, Maarten, Steven Logghe, Marco Schreuder, P. Audenaert, Didier Colle, and Mario Pickavet. 2017. “Automated Incident Detection Using Real-Time Floating Car Data.” JOURNAL OF ADVANCED TRANSPORTATION 2017. doi:10.1155/2017/8241545.
Vancouver
1.
Houbraken M, Logghe S, Schreuder M, Audenaert P, Colle D, Pickavet M. Automated incident detection using real-time floating car data. JOURNAL OF ADVANCED TRANSPORTATION. 2017;2017.
IEEE
[1]
M. Houbraken, S. Logghe, M. Schreuder, P. Audenaert, D. Colle, and M. Pickavet, “Automated incident detection using real-time floating car data,” JOURNAL OF ADVANCED TRANSPORTATION, vol. 2017, 2017.
@article{8544318,
  abstract     = {{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 FCDAID 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.}},
  articleno    = {{UNSP 8241545}},
  author       = {{Houbraken, Maarten and Logghe, Steven and Schreuder, Marco and Audenaert, P. and Colle, Didier and Pickavet, Mario}},
  issn         = {{0197-6729}},
  journal      = {{JOURNAL OF ADVANCED TRANSPORTATION}},
  keywords     = {{TRAVEL-TIME,LOOP DETECTORS,NETWORK,IBCN}},
  language     = {{eng}},
  pages        = {{13}},
  title        = {{Automated incident detection using real-time floating car data}},
  url          = {{http://doi.org/10.1155/2017/8241545}},
  volume       = {{2017}},
  year         = {{2017}},
}

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