## 3 Results and Discussion
### Association Rules
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & **head\_set** & **tail\_set** & **Support** & **Confidence** & **Lift** \\ \hline \hline \multicolumn{6}{l}{(a) vulnerable road user} \\ \hline
1 & [’Physical Isolation is Only Central Isolation’] & [’Functional Zone is Urban District’] & 0.132 & 0.857 & 2.199 \\
2 & [’Service-POI is 50–500 pcs/km\({}^{2}\)’] & [’Road Type is Trunk Road’] & 0.199 & 0.9 & 1.827 \\
3 & [’Physical Isolation is Only Central Isolation’] & [’Road Type is Trunk Road’] & 0.132 & 0.857 & 1.74 \\
4 & [’Collision Type is Single vehicle accident’] & [’Road Type is Trunk Road’] & 0.125 & 0.85 & 1.725 \\
5 & [’Functional Zone is Urban District’] & [’Road Type is Trunk Road’] & 0.316 & 0.811 & 1.647 \\ \hline \multicolumn{6}{l}{(b) motor vehicle driver} \\ \hline
1 & [’Road Type is Secondary and Tertiary Road’] & [’Shopping-POI is \(\leq\)50 pcs/km\({}^{2}\)’] & 0.145 & 0.892 & 2.022 \\
2 & [’Functional Zone is Rural District’] & [’Shopping-POI is \(\leq\)50 pcs/km\({}^{2}\)’] & 0.185 & 0.851 & 1.927 \\
3 & [’Road Type is Secondary and Tertiary Road’] & [’Service-POI is \(\leq\)50 pcs/km\({}^{2}\)’] & 0.157 & 0.969 & 1.633 \\
4 & [’Functional Zone is Rural District’] & [’Service-POI is \(\leq\)50 pcs/km\({}^{2}\)’] & 0.195 & 0.897 & 1.511 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Binomial association rules. POI densities less than 50 \(\mathrm{pcs}/\mathrm{km}^{2}\) for services and shopping. Motor vehicle drivers are more likely to drive at faster speeds and lower vigilance on high-grade roads due to more space, flatter road surfaces and higher speed limits, which constitute critical reasons for severe and even fatal accidents. If Lift = 2, indicating that the antecedent has already occurred, the probability of the posterior occurring is twice the probability of the posterior occurring in the database. The higher the Lift value, the more likely it is that the simultaneous occurrence of antecedent and consequent terms in an event is not coincidental. Therefore, to demonstrate that the antecedent and posterior terms of the rules are interdependent, we extracted three association rules with lift values exceeding 2, containing eight and six rules, respectively, in Table 3a,b. All posterior terms are associated with density of Service-POI and Shopping-POI. As shown in Table 3a, for traffic accidents with vulnerable road users at-fault, the posterior terms of rules #1-#4 are the density Service POI area of 50-500 \(\mathrm{pcs}/\mathrm{km}^{2}\), and the antecedent terms contain the high-density Shopping-POI densities. All four rules have the same confidence and lift values of 1 and 2.46, indicating strong correlation. Thus, several types of traffic accidents are more likely to be fatal, including crashes which occurred in urban areas with high restaurant shopping POI densities, crashes which occurred on trunk roads, crashes where non-motorized vehicles are primarily responsible for vehicle-vehicle collisions, and crashes which occurred in areas with medium to high-density Service POI. It is similar to the conclusion of the two association rules above. Therefore, for traffic accidents where the vulnerable road users are primarily responsible, separating the non-motorized lane from the pavement area in urban areas with high restaurant and shopping POI densities is necessary for minimizing the likelihood of vehicle-pedestrian collisions. Due to the instability of two-wheelers, increased efforts should be made to remind motorbike and electric bike riders to wear helmets on the road. Rules #5 and #6 point out that when the traffic accidents occur in low-density Service POI areas and Rural District or on Secondary and Tertiary Roads, the density of Shopping POI around the site of the fatal accident is low. Therefore, safety signage and surveillance should be enhanced in remote suburban areas and on low-grade roads in areas with low Service and Shopping POI densities. Consideration should be given to reduce speed limit on roads with high accident rates to prevent fatal accidents.