Transportation Safety

Effects of non-driving-related-task modality and road geometry on eye movements, lane-keeping performance, and workload while driving. Transportation Research Part F: Psychology and Behaviour, 60, 157-171. DOI: 10.1016/j.trf.2018.10.015.

Driving on horizontal, curved roads requires much research attention because it tends to result in more accidents compared to driving on straight roads. Several studies have found that non-driving-related-task (or secondary-task) sensory modality and horizontal-road geometry (e.g., curvature radius and curve direction) are major factors that affect driving performance and safety on horizontal curves. However, few studies have examined the combined effects of these factors. This paper reports a driving simulation study of the impacts of non-driving-related-task modality (4 levels), road curvature radius (4 levels), and curve direction (2 levels) on driver behaviour. Eye movements, lane-keeping performance, and subjective workload of 24 participants were measured. The results showed that drivers performing non-driving-related tasks using visual stimuli or manual responses on curved roads fixated less frequently and with shorter durations on the road and showed poorer lane-keeping performance compared to other modalities. In addition, when driving on sharper curves with a non-driving-related task, drivers looked at the road more frequently and longer, but their lane-keeping performance was poorer (i.e., higher standard deviations of lane position and of steering wheel angle). Participants reported higher visual demand when performing visual-speech types of tasks compared to auditory-manual types of tasks. The practical implications for driving safety on horizontal, curved roads are discussed.

Driver Glance Behaviors and Scanning Patterns: Applying Static and Dynamic Glance Measures to the Analysis of Curve Driving with Secondary Tasks. Human Factors and Ergonomics in Manufacturing & Service Industries. DOI: 10.1002/hfm.20798.

Performing secondary tasks (or non-driving-related tasks) while driving on curved roads may be risky and unsafe. The purpose of this study was to explore whether driving safety in situations involving curved roads and secondary tasks can be evaluated using multiple measures of eye movement. We adopted Markov-based transition algorithms (i.e., transition/stationary probabilities, entropy) to quantify drivers’ dynamic eye movement patterns, in addition to typical static visual measures such as frequency and duration of glances. The algorithms were evaluated with data from an experiment (Jeong & Liu, 2019) involving multiple road curvatures and stimulus-response secondary task types. Drivers were more likely to scan only a few areas of interest with a long duration in sharper curves. Total head-down glance time was longer in less sharp curves in the experiment, but the probability of head-down glances was higher in sharper curves over the long run. The number of reliable transitions between areas of interest varied with the secondary task type. The visual scanning patterns for visually undemanding tasks were as random as those for visually demanding tasks. Markov-based measures of dynamic eye movements provided insights to better understand drivers’ underlying mental processes and scanning strategies, compared to typical static measures. The presented methods and results can be useful for in-vehicle systems design and for further analysis of visual scanning patterns in the transportation domain.

Simulator Evaluation of an Intersection Maneuver Assist System with Connected and Automated Vehicle Technologies. Ergonomics. DOI: 10.1080/00140139.2022.2121006.

Intersection crashes can be potentially mitigated through vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) safety management systems. It is important, however, to consider some of the human factors related aspects of such systems to maximize potential safety benefits. In this study, Intersection Maneuver Assistance Systems were conceptualized and evaluated in a driving simulator. The systems were designed to assist drivers with intersection maneuvers by making use of connected infrastructure and providing real-time feedback, guidance, and active vehicle controls. The study compared drivers’ confidence, workload, glances at the instrument panel, and hazard anticipation when driving using three systems – System A (no alert or assist); System B (alert only); and System C (alert and assist). Study results show differences in drivers’ confidence in such systems and potentially degraded visual gaze behaviors.