# Enhancing Street-Crossing Safety for Visually Impaired Pedestrians with Haptic and Visual Feedback
## 6 Conclusions  
This study investigated the effectiveness of haptic and visual feedback in assisting visually impaired individuals with safe street-crossing decisions. Through two controlled experiments, we examined how different feedback modalities influenced decision-making efficiency, user confidence, and perceived urgency across distinct crossing scenarios: traffic signal-controlled intersections and vehicle-based crossings. Key findings indicate that, in signal-controlled crossings, visual feedback significantly reduced decision time, enabling quicker and more confident decisions, though some users experienced perceptual fatigue. Haptic feedback, while slightly slower, was preferred for its intuitive and comfortable nature. In vehicle-based crossings, haptic feedback was more effective, particularly in dynamic conditions, enhancing situational awareness and enabling faster decisions. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Feedback Modality**} & \multirow{2}{*}{**State**} & \multirow{2}{*}{**Size (Direction)**} & \multirow{2}{*}{**Confidence Level**} & \multicolumn{4}{c}{**Frequency**} \\ \cline{5-8}  & & & & **0.5 Hz** & **1.0 Hz** & **2.0 Hz** & **4.0 Hz** \\ \hline \multirow{8}{*}{Visual Feedback} & \multirow{8}{*}{Static} & \multirow{8}{*}{Medium (Right)} & 100\% & 3.39 & 3.47 & 2.85 & 2.72 \\  & & 90–99\% & 5.37 & 3.81 & 2.76 & 2.07 \\  & & \textless{}90\% & 2.69 & 3.37 & 2.42 & 2.08 \\ \cline{2-8}  & & \multirow{8}{*}{Medium (Left)} & 100\% & 3.10 & 3.20 & 3.19 & 2.61 \\  & & 90–99\% & 5.56 & 3.68 & 2.94 & 1.87 \\  & & \textless{}90\% & 3.47 & 3.49 & 2.52 & 2.49 \\ \cline{2-8}  & & \multirow{8}{*}{Small (Right)} & 100\% & 4.46 & 3.91 & 4.28 & 2.85 \\  & & \textless{}90\% & 5.16 & 3.21 & 3.04 & 2.37 \\  & & \textless{}90\% & 3.86 & 3.57 & 2.81 & 2.19 \\ \cline{2-8}  & & \multirow{8}{*}{Small (Left)} & 100\% & 4.05 & 3.41 & 3.94 & 2.81 \\ \cline{2-8}  & & \textless{}90\% & 4.93 & 3.57 & 2.99 & 2.38 \\ \cline{2-8}  & & \textless{}90\% & 3.30 & 3.36 & 3.07 & 1.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: _Cont._These findings underscore the importance of tailoring assistive feedback to specific street-crossing environments. Future research should explore hybrid feedback systems that integrate both modalities to optimize safety and user experience. We acknowledge the limitations of our study, particularly the use of simulated environments, rather than real-world settings and the lack of participants with actual visual impairments. Future studies should expand to real-world urban environments with larger, more diverse participant groups, particularly individuals with varying degrees of visual impairment, including those with residual light perception. Field testing should occur across multiple intersection types under various traffic and environmental conditions, followed by longitudinal studies to assess adaptation and long-term benefits. This ecological approach would significantly enhance the system's validation and generalizability. By leveraging multimodal feedback systems, we can significantly improve the mobility independence and safety of visually impaired pedestrians across various urban settings. Conceptualization, G.R., J.H.L. and G.W. ; methodology, G.R. and T.H. ; software, G.R. ; validation, T.H. and J.H.L. ; formal analysis, Z.H. ; investigation, Z.H. and W.L. ; resources, G.W. ; data curation, Z.H. ; writing--original draft preparation, G.R. and Z.H. ; writing--review and editing, G.R., J.H.L. and G.W. ; visualization, W.L. ; supervision, G.W. ; project administration, G.R. and G.W. ; funding acquisition, G.W. and J.H.L. All authors have read and agreed to the published version of the manuscript. This study was supported by (1) the Korea Institute of Police Technology (KIPoT; Police Lab 2.0 program) grant funded by MSIT (RS-2023-00281194), (2) a research grant (2024-0035) funded by HAII Corporation, (3) the Fujian Province Social Science Foundation Project (No.