Bibliographic Details
| Title: |
A Human-Centered Multimodal Framework for Characterizing Safety-Relevant Driver Functional Domains: An Exploratory Study of Professional Bus Drivers †. |
| Authors: |
Kuo, Ting-An, Lin, Chiuhsiang Joe, Liu, Po-Hsiang |
| Source: |
Sensors (14248220); Jun2026, Vol. 26 Issue 12, p3664, 22p |
| Subject Terms: |
Bus drivers, Functional assessment, Ergonomics, Neuropsychological tests, Psychology of movement, Traffic safety, Age differences |
| Abstract: |
Highlights: This study proposes a human-centered framework for characterizing safety-relevant driver functional domains by integrating self-perception, psychomotor performance, and cognitive–perceptual assessment. The findings suggest that multidimensional human-performance measures may help reveal meaningful differences in driver-related functional capacities and may provide candidate constructs for future driver monitoring research. What are the main findings? Multidimensional human-performance measures revealed selected age- and gender-related differences and descriptive tendencies across self-perception, psychomotor, and cognitive–perceptual domains. Older drivers showed slower and less efficient performance tendencies in several cognitive–perceptual tasks, with the clearest age-related pattern observed in the tachistoscopic traffic test. What are the implications of the main findings? The proposed framework highlights safety-relevant human-factor domains that may serve as candidate target constructs for future driver monitoring research. The findings support a more explainable and human-centered perspective on driver-related assessment in intelligent transportation systems, beyond surface-level symptom detection alone. This study proposes a human-centered multimodal framework for characterizing safety-relevant driver functional domains in professional bus drivers. Unlike conventional approaches that rely on isolated psychological or physical assessments, the proposed framework integrates self-perception, psychomotor performance, and cognitive–perceptual assessment to provide an exploratory, structured characterization of driver-related functional capacities. Eighteen professional bus drivers participated in this study. Self-perception data were obtained from all 18 participants, whereas psychomotor and cognitive–perceptual assessments were completed by 16 participants. These measurements were used to examine multiple domains relevant to driving safety, including behavioral awareness, motor coordination, attention, visual tracking, and hazard-perception-related processing. Given the modest sample size, the study should be regarded as an exploratory pilot investigation. Data were analyzed using a laboratory-based cross-sectional between-subjects design to examine age- and gender-related differences across the assessed domains. The findings suggested that selected age- and gender-related differences and descriptive tendencies were observable across multiple domains. Male drivers descriptively showed higher self-rating scores, female drivers showed different performance tendencies in selected psychomotor tasks, and male drivers demonstrated substantially greater grip strength. Older drivers showed slower and less efficient performance in several cognitive–perceptual measures, with the clearest age-related effect observed in the tachistoscopic traffic test, where older participants showed a higher error tendency under time-constrained traffic-scene processing conditions. The constructs and measures proposed in this study are intended as general laboratory-based assessments of driver-related capabilities rather than direct measures of actual driving performance, real-time driver-state indicators, or validated sensor-based monitoring indicators. As candidate human-factor constructs, they may inform future driver monitoring research by helping clarify how driver-related signals or behaviors could eventually be linked to underlying functional and safety-related meaning in intelligent transportation environments. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |