Extracting Pedestrian Movement Parameter Of Exit-selection And Single File Experiments Based On RFID

How to evacuate the persons effectively is very vital to reduce the casualties, when the fire, earthquake and other disasters happened. The basis of evacuation research is the personnel movement characteristics, and the key of personnel movement characteristics research is the pedestrian movement parameters. The common methods of extracting the pedestrian movement parameters are the artificial statistics and video processing. The former is low efficiency, and the later has the limit of shot location and environment for example, the cameras could not shot the pedestrian movements clearly under the smoke, fog and dark environment.Currently, the RFID technology develops rapidly and is used widely. In this article, we study how apply the RFID technology to the pedestrian movement experiments, besides, we obtain a new method to extract the pedestrian movement parameters quickly. We conducted the pedestrian movement exit-selection experiments and the single channel pedestrian movement experiment which includes two different conditions, with visibility and without visibility. The number of persons, and the exit time, exit flow and flow rate, and the velocity of pedestrian were obtained by the RFID method and the video processing. The experiment results obtained by two methods were compared with each other to verify the method of extracting pedestrian movement parameters we proposed.According to the experiment results, we found that, about90%of the exit time relative errors, the absolute values are less than0.08and the absolute values of all the errors of exit time are less than0.10. About90%of the exit flow relative errors are less than0.20. The absolute value of relative error about the average exit flow and flow rate is less than3.55%of one exit, for another exit, the absolute value is less than8.38%. Almost all the velocity relative errors, the absolute values are less than0.30, and about70%of velocity error, the absolute value is less than0.20. At the same time, we compared the pedestrian velocity under the visibility environment with the velocity without the visibility circumstance. It is found that, for most of the pedestrians, the velocity in daytime is larger than the velocity under dark environment. This matches the real situation.According to the pedestrian movement experiments of exit-selection and single channel, the RFID technology was verified that, it could be applied to extract the parameters of pedestrian quickly and effectively. Besides, the method we presented in this article overcomes the shortcomings of the traditional artificial and video processing. This has the great significance to the study of human evacuation and the evacuation model.