## 3 Results
### Keyword Co-Occurrence and Clustering  
#### 3.4.1 Keyword Co-Occurrence Network and Evolutionary Pattern  
For the keyword selection strategy, we employed a dual-criteria approach considering both frequency and centrality metrics. Initially, we arranged keywords in descending frequency order and selected the top 26 high-frequency terms. While conducting our qualitative assessment, we noted that \"connected vehicle communication\" demonstrated a centrality value of 0.00 despite its occurrence frequency of 5, suggesting limited direct connections within the established knowledge network. However, we retained this keyword in our analysis, as it represents an emerging technological approach with a potential future impact on VRU safety despite its current peripheral position in the knowledge structure. The selected keywords (Table 4) collectively represent both established research hotspots and evolving conceptual frameworks within the field. \begin{table}
\begin{tabular}{c c c c l} \hline \hline
**No.** & **Count** & **Centrality** & **Year** & **Publication Venue** \\ \hline
1 & 17 & 0.13 & 2014 & LECT NOTES COMPUT SC \\
2 & 13 & 0.27 & 2016 & ACCCIDENT ANAL PREV \\
3 & 12 & 0.04 & 2017 & SENSORS-BASEL \\
4 & 9 & 0.14 & 2020 & MOBIEHCI 2018 \\
5 & 8 & 0.33 & 2007 & HUM FACTORS \\
6 & 8 & 0.07 & 2023 & IEEE ACCESS \\
7 & 8 & 0.02 & 2018 & PROC CVPR IEEE \\
8 & 7 & 0.00 & 2020 & ARXIV \\
9 & 6 & 0.16 & 2020 & APPL SCI-BASEL \\
10 & 5 & 0.26 & 2016 & IEEE T SYST MAN CY C \\
11 & 5 & 0.00 & 2016 & TRANSFPORT RES F-TRAF \\
12 & 5 & 0.00 & 2017 & IEEE INT VEH SYM \\
13 & 4 & 0.36 & 2000 & FDN ORIENTATION MOBI \\
14 & 4 & 0.32 & 2007 & ERGONOMICS \\
15 & 4 & 0.02 & 2019 & INT J HUM-COMPUT ST \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Top 15 journals and conferences in VRU safety wearable technology research. The co-occurrence keyword network reveals the knowledge structure and research hotspots in wearable technology for VRU safety. As shown in Figure 5 and Table 4, the network presents clear knowledge distribution characteristics and thematic associations. Nodes such as \"visually impaired,\" \"assistive technology,\" and \"wearable technology\" occupy important positions in the network, with their larger node volumes reflecting higher occurrence frequencies, indicating these concepts have received widespread attention in this research field. Several interconnected research themes can be observed in the map: visual-impairment-assistance-related topics, including \"visually impaired,\" \"assistive technology,\" and \"electronic travel aids\"; safety-protection-related topics such as \"traffic safety,\" \"pedestrian safety,\" and \"cyclist safety\"; technology-implementation-related topics, including \"wearable technology,\" \"sensor,\" and various reality technologies (\"virtual reality,\" \"augmented reality\"); as well as functional-mechanism-related topics like \"warning alerts,\" \"collision avoidance,\" and \"obstacle avoidance.\" The connecting lines in the map demonstrate the close associations between concepts, with high centrality nodes such as \"performance\" (centrality = 0.30) and \"collision avoidance\" (centrality = 0.25) playing key roles in connecting different research directions. The network structure reflects the evolution of research in this field from initial assistive technologies for visually impaired people to a comprehensive safety technology system for multiple categories of VRUs.