# Evaluation of Adjustment Effects of Highway Guide Signs Based on the TOPSIS Method
## 5 Evaluation Model and Application
### Construction of the Evaluation Model Based on the TOPSIS Method
#### 5.1.2 Evaluation Procedure  
The evaluation of highway guide signs follows a structured approach based on the previously established indicators and evaluation model. The steps are as follows:  
1. Collection of background data
2. Gather relevant basic information about the evaluated road, including its classification, number of lanes, road alignment, geometric conditions, and intersections. 3. Development of a survey plan  
Define a detailed survey strategy. Subjective indicators: Use questionnaires focusing on driver behavior and needs to collect relevant data. Objective indicators: Conduct field research to obtain real-world data on the guide signs along the road. Figure 3: Structural model for evaluating guide sign effectiveness. Implementation of field surveys  
Execute the survey plan as designed: Conduct subjective surveys by distributing questionnaires to drivers at highway service areas to gather feedback for subjective metrics. For objective data, surveyors drive along the highway section under evaluation, using direct observation and video recordings to collect data on the guide signs. Calculation of evaluation indicators  
Classify the collected data based on the indicator categories. Compute each indicator using the formulas provided in the research framework. Evaluation of the objects  
Apply the TOPSIS method to assess the effectiveness of the guide signs on the highway, determining how well they meet optimal standards. There are seven specific steps, as follows:  
Formulate the decision matrix. In the evaluation of road network signage, let \(M=(M1,M2,\cdots,M_{m})\) represent the set of evaluation objects and \(D=(D1,\ D2,\cdots,\)\(D_{n})\) represent the set of indicators. The value of an evaluation object \(M_{i}\) concerning an indicator \(D_{j}\) is denoted as \(x_{ij}(i=1,2,\ldots,m;j=1,2,\ldots,n)\). Thus, the decision matrix X is structured as follows:  
\[\text{X}= \begin{pmatrix}\text{D}_{1}&\text{D}_{2}&\ldots&\text{D}_{n}\\ \text{M}_{1}&\text{x}_{11}&\text{x}_{12}&\ldots&\text{x}_{1n}\\ \text{M}_{2}&\text{x}_{21}&\text{x}_{22}&\ldots&\text{x}_{2n}\\ \vdots&\vdots&\vdots&\vdots&\vdots\\ \text{M}_{m}&\text{x}_{m1}&\text{x}_{m2}&\ldots&\text{x}_{mn}\\ \end{pmatrix}  \tag{25}\]  
Normalization of indicators. To eliminate the impact of differing dimensions among evaluation indicators on decision-making, normalization is applied to the data. Indicators are classified into two categories based on their nature: high-priority indicators (where larger values are better) and low-priority indicators (where smaller values are better). Different normalization algorithms are used for these two types of indicators. \[\text{x}_{ij}^{\prime}= \begin{cases}\frac{\text{x}_{ij}-\min\left\{\text{x}_{ ij}\text{x}_{2i}\text{-}\cdots\text{x}_{mij}\right\}}{\max\left\{\text{x}_{ ij}\text{x}_{2j}\text{-}\cdots\text{x}_{mij}\right\}-\min\left\{\text{x}_{ ij}\text{x}_{2i}\text{-}\cdots\text{x}_{mij}\right\}};\text{high-priorityindicators}\\ \frac{\max\left\{\text{x}_{ij}\text{x}_{2i}\text{-}\cdots\text{x}_{mij}\right\}- \text{x}_{ij}}{\max\left\{\text{x}_{i}\text{x}_{2i}\text{-}\cdots\text{x}_{ mij}\right\}-\min\left\{\text{x}_{ij}\text{x}_{2j}\text{-}\cdots\text{x}_{mij} \right\}};\text{low-priorityindicators}\\ \end{cases}  \tag{26}\]  
Determine the weights of each indicator. The Analytic Hierarchy Process (AHP) is employed to perform pairwise comparisons of each indicator's importance relative to the corresponding criteria at the upper level. This method helps in establishing the relative weights of the indicators and conducting a consistency check to verify their coherence. Construct the weighted decision matrix. Multiply the weights of each indicator by the non-dimensional matrix to obtain the weighted decision matrix \(R=\left(r_{ij}\right)_{m\times n}\) for the directional signs. This matrix reflects the importance of each indicator in relation to the overall assessment, allowing for a more informed evaluation of the directional signs' effectiveness.