本研究以流量守恆為基礎，探討路網中車輛偵測器佈設策略問題。近年來車輛偵測器佈設策略被廣泛的研究與討論，目的是透過佈設偵測器之部分路段流量，推估路網未佈設偵測器的路段流量，甚至進一步推算路徑流量與旅次起訖點的流量，這些推估的流量資料，對於短期交通管理及長期運輸規劃工作，具有重要的參考價值。
在探討路網車輛偵測器佈設問題的方法論方面，從最簡單的線性方程式到線性代數之方法皆有論及；但數學方程式有其限制所在，例如初始點的限制與大型路網運算費時等問題。為改善上述問題，本研究運用不同於數學代數模式的「圖形理論」，據以求解交通路網中車輛偵測器的最佳佈設策略。
圖形理論為非數學的邏輯推算法，在交通運輸上的應用常見於求解最短路徑、排程與排班等問題，具有快速求解與簡潔易懂的理念。本研究以圖形理論其中的一個方法：圖形著色理論，應用於求解交通路網的車輛偵測器最佳佈設策略問題，研究目的除了驗證圖形理論應用於該議題的可行性之外，同時評估不同求解方法在各類型路網上的求解效率。
最後，本研究透過不同路網模式之驗證及複雜度比較，評估圖形著色理論在路網偵測器佈設策略問題的適用性與優勢。

Vehicle detector is fundamental to traffic managers, which provides speed and flow data for traffic control and management. Due to a budgetary constraint of transportation agencies vehicle detector installation problem in a traffic network becomes increasingly important.
This research discusses with the Network Sensor Location Problem (NSLP) based on rule of flow conservation. We present a graphical coloring approach to determine the smallest subset of detectors which should be installed in a traffic network. All link flows in a target network can be inferred from the flows collected by these installed detectors.
We point out the coloring approach for NSLPs in this study, which shows that it is possible to select links for detector installation in a much easier and more flexible manner for practical applications.
The research compares the proposed coloring approach and the literatures’ approaches through time and space complexity; it proves that the performance of coloring approach is more effective than algebra-based approaches. At last, this research concludes the advantages and disadvantages for the literatures’ methods and the coloring approach.

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