Multi-hypothesis GPS and electronic fence data fusion for safety-critical positioning in railway worksites
| Autor: | Joao Figueiras, Andrea Bondavalli, Hans-Peter Schwefel, Jesper Grønbæk |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Fence (finance)
Engineering Warning system business.industry Real-time computing Kalman filter Sensor fusion Identification (information) Global Positioning System Kalman filters alarm systems hidden Markov models occupational safety personnel railway safety sensor fusion traffic engineering computing False alarm business Hidden Markov model Simulation |
| Zdroj: | Figueiras, J, Gronbaek, J, Schwefel, H-P & Bondavalli, A 2013, Multi-hypothesis GPS and electronic fence data fusion for safety-critical positioning in railway worksites . in Proceedings-6th Latin-American Symposium on Dependable Computing, LADC 2013 ., 6542603, IEEE Press, pp. 31-39, 2013 Sixth Latin-American Symposium on Dependable Computing (LADC), Rio de Janairo, Brazil, 02/04/2013 . https://doi.org/10.1109/LADC.2013.23 LADC |
| DOI: | 10.1109/LADC.2013.23 |
| Popis: | Safety-critical applications often use position information as a mean of assessing the safety level of people. For this reason, such information is required to be precise in terms of accuracy and timeliness. This paper regards position mechanisms for personalized warning systems for railway workers. Position accuracy for safety assessment purposes is defined as the precise identification whether the worker is located in a dangerous or safe zone within a certain worksite. This paper extends a previous publication from the same authors to a scenario with multiple workers, while analyzing the combination of wearable GPS receivers and electronic fences strategically placed at the worksite. The proposed data fusion algorithm comprises a Kalman Filter (KF) for filtering GPS observations and a Hidden Markov Model (HMM) for fusion with fence data. A Multiple-Hypothesis Tracking (MHT) mechanism is used to handle multiple workers within the worksite as a mean to compensate the inability of the fence to distinguish the workers. The proposed solution is analyzed under experimental setups. The obtained results outperformed a GPS-only solution and the previously proposed solution by reducing or even removing false alarm and safety-related missed detection events. |
| Databáze: | OpenAIRE |
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