Optimization of a Next-Generation 3D Zombie Survival FPS Game Architecture Based on Unreal Engine 5
Downloads
This paper proposes the design, technical implementation process, and optimization techniques of a 3D zombie disaster survival simulation game developed using the latest game engine, Unreal Engine 5. To maximize the player's visual and experiential immersion, the system constructs an intelligent tracking AI system combining the AIPerceptionComponent and Behavior Tree. It also implements a precise first-person shooting (FPS) mechanism utilizing Unreal Engine's physical Collision system. Furthermore, it maximizes the horrific atmosphere by introducing wide-angle distortion and camera shaking techniques—physical characteristics of action cameras—into the camera direction, and integrates the next-generation Lumen rendering technology. This study includes a practical troubleshooting methodology to resolve complex physical calculation errors and large asset synchronization conflicts that inevitably occur in a 3D game development environment with multiple developers. Through this, it proves that the system developed in this study simultaneously provides outstanding visual direction and a stable play environment.
Public Data Portal, “Government24 Public Service Open API.” [Online]. Available: https://www.data.go.kr/data/15113968/openapi.do#/tab_layer_detail_function
Spring, “Spring Boot Reference Documentation.” [Online]. Available: https://docs.spring.io/spring-boot/
Spring, “Spring Security Reference Documentation.” [Online]. Available: https://docs.spring.io/spring-security/
Meta Open Source, “React Documentation.” [Online]. Available: https://react.dev/
OpenAI, “OpenAI API Documentation.” [Online]. Available: https://platform.openai.com/docs/
PostgreSQL Global Development Group, “PostgreSQL Documentation.” [Online]. Available: https://www.postgresql.org/docs/
Y.-J. Ahn, H.-Y. Cho, and S.-J. Kang, “Customized Recipe Recommendation System Implemented in the Form of a Chatbot,” Journal of the Korea Academia-Industrial Cooperation Society, vol. 21, no. 5, pp. 543-550, 2020.
J.-H. Jung, W.-J. Lee, H.-W. Choi, D.-Y. Seo, J.-H. Lee, H.-B. Park, and H.-Y. Lee, “Development of a Customized Webtoon Recommendation Platform Using the GPT Model,” Proceedings of KIIT Conference, pp. 1361-1364, 2025.
J.-W. Son, H.-B. Kim, D. Yoon, S.-H. Park, K.-I. Lee, and S.-J. Kim, “Development of an AI Chatbot-Based Personalized Restaurant Recommendation System,” Proceedings of KIIT Conference, pp. 1273-1277, 2025.
S.-R. Jung and J. Kim, “Sentiment-Fused Hybrid Recommender System for Movie Domain: Integrating Aspect-Based Emotion Analysis with Collaborative-Content Filtering,” Journal of the Korea Big Data Society, vol. 10, no. 1, pp. 209-219, 2025.
