## 4 Intelligent Wearable Solutions for VRU Safety: Trends, Challenges, and Opportunities
### Wearable Technologies for Two-Wheeler Users
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Year** & **Wearable Technology** & **Experimental Validation Method** \\ \hline [PERSON] et al. [38] & 2023 & Simulated AR headset for pedestrian navigation and autonomous vehicle interaction & VR-based simulation studies with 18 and 24 participants, respectively, evaluating different AR interface designs for urban navigation and street crossing scenarios \\ \hline [PERSON] et al. [35] & 2024 & Wearable devices (AirPods Pro) for delivering voice-based notifications to pedestrians & Field study with eight participants in urban environments collecting sensor data and acceptance feedback through the SoNotify smartphone application \\ \hline [PERSON] et al. [39] & 2024 & AR headset (Microsoft HoloLens 2) with collision warnings and virtual traffic light displays for street crossing & Field experiment with 20 participants in a real-world vehicle crossing scenario, measuring perceived safety, workload, and system usability \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._gradually shifting from performance metrics to usability and user acceptance in real-world cycling environments, reflecting the field's transition into a more mature application phase. With the proliferation of electric micro-mobility, electric scooter safety technology has emerged as a research focus, with solutions incorporating features from both bicycle and motorcycle safety systems. [PERSON] et al. designed a helmet system specifically for elderly riders that incorporates ultrasonic sensing technology [51], precisely detecting surrounding obstacles and providing visual warnings to prompt appropriate speed reduction in hazardous situations. [PERSON] et al. developed innovative pressure-sensitive insoles [52] that monitor rider balance in real time and provide intelligent path assistance, particularly beneficial for riders with varying proficiency levels navigating complex terrain. [PERSON] et al. compared different warning mechanisms through an augmented reality environment [53], with the results indicating that combined auditory and AR visual warnings provide faster hazard reaction times and enhanced safety experiences, establishing a direction for future electric scooter safety technology development. The research progression reveals a gradual shift from simple sensing to multidimensional interactive warnings in electric scooter safety technology, with future advancements promising more intuitive and efficient safety systems through deep integration of sensing technologies and augmented reality. Similar safety enhancement principles have been applied to motorcycle applications, though with greater emphasis on rider state monitoring and proactive hazard detection. [PERSON] et al. developed a system using pressure sensors to verify proper helmet wearing as a prerequisite for engine ignition [54] while incorporating speed warning functionality. [PERSON] et al. advanced helmet intelligence by ingeniously utilizing three-axis accelerometers to sense head movements for controlling headlight direction [55], while incorporating drowsiness detection that automatically triggers alerts when riders show signs of fatigue. The system of [PERSON] et al. further integrated license plate recognition technology, using infrared transceivers and image processing to identify approaching large vehicles in real time with 75% daytime and 70% nighttime recognition accuracy [56], providing timely voice warnings to help riders address blind spot hazards. Research developments indicate that motorcycle safety technology is rapidly evolving toward multisensor fusion and intelligent warning systems, with the focus expanding from purely passive safety constraints to comprehensive safety systems that include rider physiological state monitoring and active environmental hazard identification.