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Visual information for a driver is predominant during driving. Linking drivers’ visual search patterns with motor behaviour helps understand how drivers perceived spatial and hazardous information to regulate their physical movements. Visual-motor coordination performance can be a sensitive indicator for driver competency assessment. Due to age-related cognitive decline, older drivers are likely inefficient in visual-motor coordination. While poor visual-motor coordination can cause risky behaviour behind the wheel, it is yet challenging to examine it owing to the complexity of driving behaviour. By reviewing how vision guides driving, we proposed a gaze-based integrated driving assessment approach. The empirical data were from 38 older drivers aged 60 to 81 years, who completed an on-road driving assessment recorded by eye tracking and vehicle movement tracking. Their visual search attributes were extracted from eye tracking video frames and linked to vehicle positions. Driving data, drivers’ cognitive condition and driving section were encapsulated into an integrated database, allowing interrogating multi-faceted driver-vehicle-environment interactions. Exploratory analysis results show that older drivers’ performed different visual search patterns at roundabout and intersection manoeuvres. Older drivers with better executive function skills performed more frequent eye fixations on the curves and inside vehicle features. The investigation of visual-motor coordination performance demonstrated the feasibility and effectiveness of using the integrated approach in assessing older drivers’ performance. [ABSTRACT FROM AUTHOR]

Older drivers experience difficulties in lane maintenance under challenging driving sections due to age-related cognitive declines, yet there is little comprehensive evidence on associations between cognitive functions and the lane maintenance in this population. In this study, fifty older drivers completed an on-road driving assessment and a battery of standard neuropsychological tests. Mean Lane Position (MLP), Standard Deviation of Lane Position (SDLP) and manoeuvre time calculated from precise vehicle movement trajectories were used as the lane maintenance parameters. The GNSS tracking vehicle movement presents comprehensive and reliable vehicle position data, which is more sensitive for detecting subtle variations of lane maintenance in older drivers. Statistical analysis results show that lower visual attention (selective and divided attention) was associated with higher MLP and SDLP; MLP was also correlated to spatial abilities, executive function, and motor speed; manoeuvre time was negatively correlated with drivers’ risk-taking personality (all p < .01). Selective attention was found to be the best predictor of MLP in lane maintenance. A combined eight variables from three neuropsychological tests, UFOV 2 and 3, BD and BJLO, D-KEFS TMT 1, 2, 3, and 4, correctly classified 80.4% of participants with good versus low-performing lane maintenance. [ABSTRACT FROM AUTHOR]