## 4 Intelligent Wearable Solutions for VRU Safety: Trends, Challenges, and Opportunities
### Wearable Assistive Devices for Visually Impaired Users
developed a system combining head-mounted cameras, ultrasonic sensors, and voice output [73], capable of providing comprehensive obstacle information and position navigation under various environmental conditions. The auditory display framework of [PERSON] et al. achieved efficient obstacle recognition and scene understanding in outdoor environments through computer vision and multisensor data fusion [74]. Addressing the key challenge of crossing scenarios, [PERSON] et al. designed an assistive system integrating smart glasses, waist-mounted devices, and smart canes [29], forming a complete information collection and feedback loop capable of real-time crosswalk recognition and guiding users to maintain the correct path. With the enhancement of mobile computing capabilities, [PERSON] et al. used smartphones as the core processing unit [76], working in conjunction with wearable cameras and servo motor-controlled ultrasonic sensors to achieve real-time obstacle detection and precise voice instruction generation. The AI-SenseVision system by [PERSON] et al. [78] provided more intelligent environmental perception capabilities through advanced object detection algorithms and ultrasonic sensing collaboration. In terms of sensor optimization, research by [PERSON] et al. provided important design guidance for multimodal systems, finding that high-gain antennas performed better in medium-distance obstacle detection, while low-gain antennas were more effective in short-distance imaging applications [77], which is a finding with significant reference value for integrated systems that need to simultaneously satisfy different usage scenarios. By intelligently integrating multiple perception channels and feedback methods, these systems are particularly suitable for complex and variable urban environments and high-risk traffic scenarios. Research trends indicate that the field is evolving from simple technology superposition toward deep, intelligent integration, with the popularization of mobile computing platforms, such as smartphones, providing a solid foundation for practical applications. Examining the evolution of wearable assistive technologies for visually impaired individuals (Tables 8 and 9, and Figure 11), the research focus has progressed from early basic obstacle detection and simple path navigation to intelligent systems capable of processing complex street scenarios and precisely identifying traffic signals, highly consistent with the systematic evolution from basic research on \"wearable technology\" and \"visually impaired\" to \"warning alerts\" and \"vehicle impact\" in the \"#0 street crossing\" cluster. These technical solutions flexibly select perception modalities according to usage scenarios and environmental conditions--prioritizing tactile feedback in noisy environments while integrating auditory and multimodal feedback when complex information needs to be conveyed--effectively balancing information transmission with cognitive load. Current research is advancing in three key directions: first, shifting from technology-driven approaches toward deeper user-need orientation, designing differentiated solutions for totally blind, low-vision, and light-perception capable visually impaired groups, reflecting an evolution from basic assistance to precise prevention; second, through miniaturization design and intelligent algorithm optimization, improving device wearability and long-term use experience and reducing physical and cognitive burden on users; third, integrating wearable assistive devices with smart city infrastructure to enhance synergies among environmental perception, information processing, and user feedback, echoing the technological development path from \"object detection\" toward \"artificial intelligence\" and \"active system\" in the \"#4 blind navigation\" cluster and providing more comprehensive technical support for independent and safe mobility of visually impaired individuals. Figure 11: Visually impaired pedestrians safety wearable technology framework.