Cognitive, motor and sensory deficits associated with aging, and with some neurological conditions such as acquired brain injury, may lead to severe driving performance impairment. While rehabilitation and driver assistance technologies may improve driving performance, the assessment of the actual fitness-to-drive of these people is challenging. Office-based neuropsychological/physical tests are considered insufficient to understand one’s ability to drive. The gold standard is the on-road assessment with dual control cars, superior in ecological validity, but expensive, stressful, and potentially unsafe. Valid, more cost-effective solutions for a safer, more accurate, standardized assessment of fitness-to-drive are currently needed. Modern and sensorized driving simulators offer key advantages, such as the possibility of exposing drivers to several relevant driving scenarios, including hazard situations, and of assessing their driving performance without being physically at risk. However, the extraction and direct interpretation of existing simulator-produced data may require specialized data processing skills or simulation expertise. To overcome this, we have developed an easy-to-use, pencil-and-paper observational instrument. The Sim-DOS is an adaptation of the widely used instrument to assess “natural driving”, the Driving Observation Schedule (DOS; Vlahodimitrakou et al., 2013).

Via expert consensus, DOS targeted behaviors were adapted to a simulated-based environment (signaling, observation of environment, speed regulation, slow or unsafe reaction, distance interpretation, vehicle/lane positioning), and the Sim-DOS scores calculation (based on errors while doing such behaviors) was adapted from DOS to include hazard situations (HS, 0-100) and free driving (FD, 0-°°) scores. The instrument was then piloted with a sample of 35 older adults, along with the collection of simulator-produced data on number of harsh events and driving speed. Participants drove two consecutive 20-minutes long scenarios, with low and high traffic density (LTD, HTD). In each scenario, there were periods with and without potentially hazard situations.

Assessments were performed by two independent trained observers, producing substantial inter-rater reliability (intra-class correlation coefficients above 0.94). Participants (70.7±4.1 years old, 60% male, 46.1±6.7 years of driving experience) were mostly regular drivers (74%). However, psychomotor skills of the majority were compromised, with only one participant being above the 80th percentile in the reaction times test of the national mandatory driving assessment. When exposed to hazard situations, most of the participants (94.1%) did not perform well, independently of traffic density, with average Sim-DOS-HS scores of 87.1±9.7 (out of 100, t-values>7.3, p-values<.05).

Compared to LTD scenarios, in HTD scenarios participants drove less smoothly (HTD:0.97±1.24 vs. LTD:0.33±0.58 of harsh events, Z=3.1, p<.05). However, they also drove slower (HTD:82.41±27.43 vs. LTD:103.55±14.61 km/h, t=5.2, p<.05), improving their ability to manage hazard situations, and therefore producing higher than expected Sim-DOS scores (HTD:87.05±10.28). During free driving, participants performed worse under LTD conditions (Sim-DOS-FD scores: HTD:11.68±6.20 vs. LTD:14.40±9.58, t=2.15, p<.05) as they drove at higher speed (HTD:85.01±24.28 vs. LTD:104.70±11.94 km/h, t=5.8, p<.05), although they did it more smoothly (HTD:1.94±3.74 vs. LTD:0.45±0.74 harsh events, Z=2.65, p<.05).

Our study provides a validated driving assessment tool for use in driving simulators that will allow a safer, more ecologic, holistic and informative evaluation of the fitness-to-drive of older adults and neurological patients.