本研究針對高速公路工作區的安全問題，提出一種以使用者需求為出發點的智能安全警示系統設計方法。本研究中首先，對高速公路工作區的類型、空間劃分、空間影響進行了深入的探討，並對工作區的安全問題進行了全面的分析。我們發現，無論是施工人員還是駕駛者，都面臨著多種安全風險。為了解決這些問題，我們回顧了智能安全警示系統的發展與應用，特別是物聯網和人工智慧技術的應用。
在研究方法方面，本研究採用了品質機能展開（Quality Function Deployment，QFD）這種從使用者需求出發的方法。這使我們能夠從使用者的角度，深入理解他們的實際需求，並將這些需求轉化為具體的系統設計要素。
在本研究的實驗中，我們首先進行了用戶需求調查，收集了初級需求，並歸納了次級需求。然後，我們採用品質機能展開（QFD）方法，將用戶需求轉化為設計要素，並建立了用戶需求與設計要素間的關係矩陣，以及設計要素之間的關聯矩陣，從而確立了關鍵設計要素。在系統設計與驗證階段，我們設計了系統的物聯網架構，集成了系統的硬體設備，規劃了系統的軟體服務，並進行了系統的設計驗證。研究結果顯示，該智能安全警示系統獲得了使用者的較高接受度，並有著不錯的感知可用性表現。我們認為，本研究的成果將對解決高速公路工作區的安全問題，提供了新的思路。並為未來的智能安全警示系統設計開發提供實證參考。
本研究的主要貢獻在於提出了一種基於使用者需求的智能安全警示系統設計方法，並通過實證研究證明了其有效性。我們相信，這種以使用者需求為出發點的設計方法，將有助於提高智能安全警示系統的使用效果，並提升使用者的滿意度。

In this study, an intelligent safety warning system design method with user needs as the starting point is proposed for the safety problems in highway work zones. In this study, firstly, the type, spatial division, and spatial impact of highway work zones are thoroughly investigated, and a comprehensive analysis of work zone safety issues is conducted. We found that both construction workers and motorists are exposed to a variety of safety risks. To address these issues, we review the development and application of intelligent safety warning systems, especially the application of the Internet of Things and artificial intelligence technologies.
In terms of research methodology, this study adopts the Quality Function Deployment (QFD) approach, which starts from the user's needs. This allows us to understand the actual needs of users from their perspective and translate these needs into specific system design elements.
In the experiments of this study, we first conducted a user requirements survey to collect the primary requirements and summarize the secondary requirements. Then, we adopted the Quality Functional Development (QFD) method to transform the user requirements into design elements, and established the relationship matrix between user requirements and design elements, as well as the association matrix between design elements, so as to establish the key design elements. In the system design and validation stage, we designed the system's IoT architecture, integrated the system's hardware devices, planned the system's software services, and conducted the system design validation. The results of the study show that the intelligent safety warning system has gained high acceptance by users and has good perceived usability performance. We believe that the results of this study will provide new ideas for solving safety problems in highway work zones. It also provides empirical reference for the future design and development of intelligent safety warning systems.
The main contribution of this study is to propose an intelligent safety warning system design method based on user requirements and to prove its effectiveness through empirical studies. We believe that this user needs-based design approach will help to improve the effectiveness of the intelligent safety warning system and enhance the user satisfaction.

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