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Application of Sensor Fusion for Determining Position and Velocity of Automated People Mover System at Soekarno-Hatta Airport with Extended Kalman Filter
Putra H.A.a, Nazaruddin Y.Y.a, Juliastuti E.a
a Instrumentation and Control Research Group, Institut Teknologi Bandung, PT. Len Railway System, Design Engineering Department, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 IEEE.Automated People Mover System (APMS) at Soekarno-Hatta airport is an automated passenger carrier that serves between terminals by train based on the Communication Based Train Control (CBTC) system. This system allows the train to run automatically without the driver. To achieve this state of automation, the control system requires information on the position and speed of the train continuously. Although any sensors used to measure this data are quite accurate, it still produces error in the measurement. In this paper, a sensor fusion method with Extended Kalman Filter (EKF) will be proposed. It will combine measurement data from several sensors to get better result than what would possibly be achieved when these sensors were used individually. The sensors that will be fused in this study are tachometer and accelerometer. Real time experiment results on the APMS running on its track at the airport showed that the EKF method gives the Root Mean Squared Error (RMSE) value of 5.89. This method provides better result when compared to the tachometer whose RMSE value is 7.12 and accelerometer whose RMSE value is 7.41.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]APMS,Automated people mover,CBTC,Communication-based train controls,Measurement data,Real-time experiment,Root mean squared errors,Sensor fusion[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]APMS,CBTC,EKF,sensor fusion[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]This paper is supported by USAID through Sustainable Higher Education Research Alliances (SHERA) Program – Centre for Collaborative (CCR) National Center for Sustainable Transportation Technology (NCSTT).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICA.2019.8916691[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]