Citation
Amin Ghafouri, Aron Laszka, Abhishek Dubey, Xenofon Koutsoukos. "Optimal Detection of Fault Traffic Sensors Used in Route Planning". 2nd International Workshop on Science of Smart City Operations and Platforms Engineering (SCOPE), April, 2017.

Abstract
In a smart city, real-time traffic sensors may be deployed for various applications, such as route planning. Unfortunately, sensors are prone to failures, which result in erroneous traffic data. Erroneous data can adversely affect applications such as route planning, and can cause increased travel time and environmental impact. To minimize the impact of sensor failures, we must detect them promptly and with high accuracy. However, typical detection algorithms may lead to a large number of false positives (i.e., false alarms) and false negatives (i.e., missed detections), which can result in suboptimal route planning. In this paper, we devise an effective detector for identifying faulty traffic sensors using a prediction model based on Gaussian Processes. Further, we present an approach for computing the optimal parameters of the detector which minimize losses due to falsepositive and false-negative errors. We also characterize critical sensors, whose failure can have high impact on the route planning application. Finally, we implement our method and evaluate it numerically using a real-world dataset and the route planning platform OpenTripPlanner.

Electronic downloads

• http://aronlaszka.com/papers/ghafouri2017optimal.pdf

• HTML

  Amin Ghafouri, Aron Laszka, Abhishek Dubey, Xenofon
  Koutsoukos. <a
  href="http://www.cps-forces.org/pubs/243.html"
  >Optimal Detection of Fault Traffic Sensors Used in Route
  Planning</a>, 2nd International Workshop on Science of
  Smart City Operations and Platforms Engineering (SCOPE),
  April, 2017.

• Plain text

  Amin Ghafouri, Aron Laszka, Abhishek Dubey, Xenofon
  Koutsoukos. "Optimal Detection of Fault Traffic Sensors
  Used in Route Planning". 2nd International Workshop on
  Science of Smart City Operations and Platforms Engineering
  (SCOPE), April, 2017.

• BibTeX

  @inproceedings{GhafouriLaszkaDubeyKoutsoukos17_OptimalDetectionOfFaultTrafficSensorsUsedInRoutePlanning,
      author = {Amin Ghafouri and Aron Laszka and Abhishek Dubey
                and Xenofon Koutsoukos},
      title = {Optimal Detection of Fault Traffic Sensors Used in
                Route Planning},
      booktitle = {2nd International Workshop on Science of Smart
                City Operations and Platforms Engineering (SCOPE)},
      month = {April},
      year = {2017},
      abstract = {In a smart city, real-time traffic sensors may be
                deployed for various applications, such as route
                planning. Unfortunately, sensors are prone to
                failures, which result in erroneous traffic data.
                Erroneous data can adversely affect applications
                such as route planning, and can cause increased
                travel time and environmental impact. To minimize
                the impact of sensor failures, we must detect them
                promptly and with high accuracy. However, typical
                detection algorithms may lead to a large number of
                false positives (i.e., false alarms) and false
                negatives (i.e., missed detections), which can
                result in suboptimal route planning. In this
                paper, we devise an effective detector for
                identifying faulty traffic sensors using a
                prediction model based on Gaussian Processes.
                Further, we present an approach for computing the
                optimal parameters of the detector which minimize
                losses due to falsepositive and false-negative
                errors. We also characterize critical sensors,
                whose failure can have high impact on the route
                planning application. Finally, we implement our
                method and evaluate it numerically using a
                real-world dataset and the route planning platform
                OpenTripPlanner.},
      URL = {http://cps-forces.org/pubs/243.html}
  }
  

Posted by Waseem Abbas on 2 Mar 2017.
Groups: forces
For additional information, see the Publications FAQ or contact webmaster at cps-forces org.