Investigation of Unexpected Crossing-Lane Activity on Curving Road Using Digital Human Modelling Analysis

Abstract

This study investigates the truck driving posture, vision safety, and perception time safety for truck drivers adjusting their velocity at the curving road due to crossing lane activity. The investigation method starts defining the road contour of the target using Geospatial Information System software (QBase). After the road elevation projection was made, the line was drawn to the surface in CAD software. After that, Digital Human Modelling (DHM) was created on the Japanese population with Indonesian anthropometry properties of 50%ile. The environment scenario was assembled based on the 3D model road surface and 3D vehicle models, and DHM in series. The objective scenario used vision analysis and driver perception response analysis. The result shows that even if the truck and SUV blockage has not appeared, the truck driver will not see the motorcycle on the corner. After that, pillar-A also contributes to blocking the truck driver's vision. Since it contributes to construction safety, the trade-off cannot be negotiated. A speed trap shall be applied before the curving zone to increase safety. The speed trap could instantly reduce the truck and other vehicles' speed in both lanes.