Prediction of seat occupancy based on class and position for airbag deployment decision

Research output: Contribution to journalArticle

Abstract

This paper deals with the simulation to predict seat occupancy based on class and position for proper airbag application. Specifically, it involves the classification and position of the seat occupant. Weight sensing algorithm is used to classify the seat occupancy status as either occupied or not and if occupied, the occupant will be identified as an adult, a child or a non-human object. In addition, the occupant position either good or bad is calculated by considering the mass, inertia tensor; coordinate origins, tensile force of the seat belt and centre of gravity of vehicle and occupant body. Our simulation results showed that the developed system model was able to classify the occupant correctly and also able to deploy proper airbag size while satisfying other conditions. An airbag deployment or non-deployment caused by occupant classification and position was viewed using virtual reality from the system model. The simulations were carried out to validate the proposed system model using Matlab/Simulink, Stateflow, SimMechanics and Virtual Reality toolbox.

Original languageEnglish
Pages (from-to)302-310
Number of pages9
JournalEuropean Journal of Scientific Research
Volume14
Issue number2
Publication statusPublished - 2006

Fingerprint

Air Bags
seats
Seats
virtual reality
Virtual reality
prediction
Prediction
Virtual Reality
User-Computer Interface
Seat Belts
simulation
Classify
Gravitation
adult children
inertia
belts (equipment)
Simulation
Centre of gravity
Tensors
Matlab/Simulink

Keywords

  • Airbag
  • Classification and position
  • Deployment decision
  • Seat occupancy detection

ASJC Scopus subject areas

  • General

Cite this

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title = "Prediction of seat occupancy based on class and position for airbag deployment decision",
abstract = "This paper deals with the simulation to predict seat occupancy based on class and position for proper airbag application. Specifically, it involves the classification and position of the seat occupant. Weight sensing algorithm is used to classify the seat occupancy status as either occupied or not and if occupied, the occupant will be identified as an adult, a child or a non-human object. In addition, the occupant position either good or bad is calculated by considering the mass, inertia tensor; coordinate origins, tensile force of the seat belt and centre of gravity of vehicle and occupant body. Our simulation results showed that the developed system model was able to classify the occupant correctly and also able to deploy proper airbag size while satisfying other conditions. An airbag deployment or non-deployment caused by occupant classification and position was viewed using virtual reality from the system model. The simulations were carried out to validate the proposed system model using Matlab/Simulink, Stateflow, SimMechanics and Virtual Reality toolbox.",
keywords = "Airbag, Classification and position, Deployment decision, Seat occupancy detection",
author = "{M A}, Hannan and Aini Hussain and Azah Mohamed and Hilmi Sanusi and {Mohd Ihsan}, {Ahmad Kamal Ariffin} and {Mohd Nor}, {Mohd. Jailani}",
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T1 - Prediction of seat occupancy based on class and position for airbag deployment decision

AU - M A, Hannan

AU - Hussain, Aini

AU - Mohamed, Azah

AU - Sanusi, Hilmi

AU - Mohd Ihsan, Ahmad Kamal Ariffin

AU - Mohd Nor, Mohd. Jailani

PY - 2006

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N2 - This paper deals with the simulation to predict seat occupancy based on class and position for proper airbag application. Specifically, it involves the classification and position of the seat occupant. Weight sensing algorithm is used to classify the seat occupancy status as either occupied or not and if occupied, the occupant will be identified as an adult, a child or a non-human object. In addition, the occupant position either good or bad is calculated by considering the mass, inertia tensor; coordinate origins, tensile force of the seat belt and centre of gravity of vehicle and occupant body. Our simulation results showed that the developed system model was able to classify the occupant correctly and also able to deploy proper airbag size while satisfying other conditions. An airbag deployment or non-deployment caused by occupant classification and position was viewed using virtual reality from the system model. The simulations were carried out to validate the proposed system model using Matlab/Simulink, Stateflow, SimMechanics and Virtual Reality toolbox.

AB - This paper deals with the simulation to predict seat occupancy based on class and position for proper airbag application. Specifically, it involves the classification and position of the seat occupant. Weight sensing algorithm is used to classify the seat occupancy status as either occupied or not and if occupied, the occupant will be identified as an adult, a child or a non-human object. In addition, the occupant position either good or bad is calculated by considering the mass, inertia tensor; coordinate origins, tensile force of the seat belt and centre of gravity of vehicle and occupant body. Our simulation results showed that the developed system model was able to classify the occupant correctly and also able to deploy proper airbag size while satisfying other conditions. An airbag deployment or non-deployment caused by occupant classification and position was viewed using virtual reality from the system model. The simulations were carried out to validate the proposed system model using Matlab/Simulink, Stateflow, SimMechanics and Virtual Reality toolbox.

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