Traffic congestion in big cities in Malaysia has become a common scenario among the communities. The
journey between homes to working place twice a day at considerable distances is no longer a strange situation. Being in
traffic for hours in a sitting position requires recurrent tasks of manual pressing the pedal and brake excessively and if
they are done without the correct sitting posture, it may trigger fatigue faster, particularly for the leg and back of the
driver. In the long term, it will negatively affect the health of the driver, particularly in the form of physical, psychological,
and emotional. Therefore, this paper is trying to investigate the recurrent brake pedal pressings as well as the leg
postures while driving in traffic jam. The research is started with the experimental setup and data acquisition on brake
pedal pressing as well as leg posture followed by the modelling and analysis of the obtained data using particle swarm optimization (PSO) modelling technique. The validation step was then executed to verify the model derived using open-loop and closed-loop performance analysis. The results show that the pedal pressing force of leg posture can be closely represented using 2nd order transfer function and mimics the actual pedal pressing pattern during road traffic delay
