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With the recent growth of cities, traffic congestion has increased dramatically, and intelligent transportation systems are gaining attention as a way to solve this problem. This further emphasizes the need for an efficient traffic management system with advanced technology. Advances in technologies such as artificial intelligence play a crucial role in improving the efficiency of intelligent transportation systems.
However, in order to improve and enhance these AI-based systems, it is necessary to adapt and continuously update them to meet the needs and expectations of users. In this study, we explore how to improve intelligent transportation systems using requirements engineering and TOPSIS. First, user requirements were collected and analyzed through requirements engineering. Then, the importance of each requirement was evaluated through TOPSIS analysis, and the priority of improvements was set based on this. The significance of this study is that it proposed an improvement plan for intelligent transportation systems by integrating requirements engineering and TOPSIS. It also enables user-centered system improvement and can play an important role in maximizing the effectiveness of intelligent transportation systems. The results of this study are expected to make important contributions to the improvement and development of AI-based intelligent transportation systems.
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