## 2 Methodology
### Meteorological Event Responsiveness
The specific division method is to take the change in weather as the basis, on a certain route carrier, from the time of the traffic accident record to record the weather events; the same weather is recorded as one weather event, and when the weather changes, we restart the calculation as a new weather event. The set of weather events shown in Figure 1 can be represented as [rainy, sunny, cloudy, foggy, snowy]. 3. Weather event response mechanism  
Support in machine learning association rules, as a measure of the frequency of occurrence of itemsets in the total dataset, plays a key role in revealing the co-occurrence relationship between items in large datasets and is widely used in data mining research [30; 31]. The versatility of the support degree method in dealing with large-scale and heterogeneous datasets makes it an ideal basic tool for identifying the association between factors such as meteorological conditions and complex alignments and the impact of traffic accident fre  
Figure 1: Classification method of meteorological events. quency. Therefore, in order to investigate the association between highway traffic accidents and highway sections under meteorological conditions, this paper proposes the concept of responsiveness based on the idea of a support degree, which in turn evaluates the degree of connection between meteorology and accidents. The support degree indicates the frequency of occurrence of a certain itemset, i.e., the ratio of the number of transactions containing the itemset to the total transactions, as a measure of the frequency of occurrence of the item set in the total dataset. The basic form of support degree [32] expression is shown in Equations (1) and (2):  
\[\text{Support}\left(X\rightarrow Y\right)=P(X\cup Y), \tag{1}\]  
\[\text{Support}(X,Y)= \frac{P(X\cup Y)}{|D|}\times 100\% \tag{2}\]  
Equations (1) and (2) \(P(X\cup Y)\) denote the number of transactions containing both itemset \(X\) and itemset \(Y\), and \(|D|\) is the total number of transaction database records. The stepwise support expression [29] is shown in Equation (3):  
\[r_{ij}= \begin{cases}1&d_{ij}\leq\beta\\ 0&d_{ij}>\beta\end{cases}  \tag{3}\]  
Equation (3) where \(d_{ij}\) is the observed value; \(r_{ij}\) is the degree of support; \(\beta\) is the observation number threshold and is a constant. The value of the meteorological risk responsiveness is determined by calculating the number of meteorological event responses on each meteorological event carrier. The meteorological event response means that when the number of traffic accidents in a meteorological event reaches the specified threshold on a meteorological event carrier, it is defined as meeting the response conditions of the meteorological event, and the meteorological event is recorded as a response meteorological event, obtaining the meteorological response conditions formula as shown in Equation (4):  
\[x_{i}= \begin{cases}1&T_{i}\geq\theta\\ 0&T_{i}<\theta\end{cases}  \tag{4}\]  
where \(T_{i}\) is the number of traffic accidents of the \(i\)th meteorological event of a route unit; \(\theta\) indicates the number of traffic accidents required to meet the response to the meteorological event, i.e., the threshold of the number of accidents. When the number of traffic accidents of the \(i\)th meteorological event reaches the threshold, it is defined as a response to the meteorological event, and the value of \(x_{i}\) is set to 1. Conversely, when the number of traffic accidents of the \(i\)th meteorological event does not reach the threshold, it is considered a non-response to the meteorological event, and the value of \(x_{i}\) is set to 0.