• Journal of the Society of Disaster Information
• /
• v.18 no.3
• /
• pp.672-686
• /
• 2022

Purpose: This study derived the planning factors affecting the evacuation route of facilities for the disabled and to identify the planning factors that affect each facility. Method: The PLS(Partial Least Square)Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The most important planning elements for each facility were derived as door: closing time (1.131), corridor: ramp for wheelchairs (1.227), stairs: emergency lighting for stairs (1.117), and evacuation space: evacuation space convenience facilities (1.106). Conclusion: In order to plan an effective evacuation route for the disabled, a universal design should be applied to consider the perception, needs, and satisfaction of the disabled, rather than a comprehensive reflection.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.59-60
• /
• 2023

The automation of container terminals is an important factor that determines port competitiveness, and global advanced ports tend to strengthen their competitiveness through container terminal automation. The operational efficiency of the AGV, which is an essential transport equipment of the automated terminal, can improve the productivity of the automated terminal. The operation of AGVs in automated container terminals differs from that of conventional container terminals, as it is based on an automated system in which AGVs travel along designated paths and operate according to assigned tasks, requiring consideration of factors such as workload, congestion, and collisions. To prevent such problems and improve the efficiency of AGV operations, a more sophisticated model is necessary. Thus, this paper proposes an AGV scheduling model that takes into account the AGV travel path and task assignment within the terminal The model prevent the problem of deadlock and. various cases are generated by changing AGV algebra and number of tasks to create AGV driving situations and evaluate the proposed algorithm through algorithm and optimization analysis.