Automatic Passenger Detection in Safety Critical Mass Transit Environments
mode - rail, planning - safety/accidents, place - europe
Fall on track, Passenger detection/ identification, Discrimination, Radar cross section (RCS), UWB rada, Slotted waveguide, 3.9 − 5.4 GHz, Singularity expansion method (SEM), Complex natural resonance (CNR)
Enhancing user safety constitutes a major issue in railway transport. In this paper, a novel solution for detection and identification of objects falling on railway tracks is proposed. This solution is based on a system using a set of consecutive ultra wideband (UWB) monostatic radars fed by a common transmission line. The main objective of this work is to study the different radiofrequency and signal processing subsets in order to evaluate and validate the full system. A slotted waveguide operating in its fundamental mode is used as the common transmission line. Slots are periodically perforated in the waveguide to constitute the radars. An optimal bandwidth and constant radiation coverage along the track are then optimized. The singularity Expansion Method (SEM) is used to characterize the objects falling on railway tracks. Complex Natural Resonances are then computed or measured and stored in a library. They are used in a specific discrimination process. Using both numerical simulations and experimental results, the discrimination process shows that human bodies are well detected and distinguished as well as other objects typically found on platform (suitcases, bottles…).
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Mroué, A., Heddebaut, M., Elbahhar, F., Rivenq, A., & Rouvaen, J.M. (2013). Automatic Passenger Detection in Safety Critical Mass Transit Environments. International Journal of Intelligent Transportation Systems Research, May 2013, Vol. 11, (2), pp 87-100