NDLI: Optimal detection of faulty traffic sensors used in route planning

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Optimal detection of faulty traffic sensors used in route planning

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Optimal detection of faulty traffic sensors used in route planning

Content Provider	ACM Digital Library
Author	Laszka, Aron Dubey, Abhishek Ghafouri, Amin Koutsoukos, Xenofon
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. To minimize the impact of sensor failures, we must detect them promptly and accurately. 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 false-positive 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.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450349895
DOI	10.1145/3063386.3063767
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-04-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Fault detection Cyber-physical systems Route planning Smart city
Content Type	Text
Resource Type	Article

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