Return-to-driving following acquired brain injury: A neuropsychological perspective

BACKGROUND: Return to driving after an acquired brain injury (ABI) has been positively associated with return to employment, maintenance of social relationships, and engagement in recreational and other community activities. Safe driving involves multiple cognitive abilities in a dynamic environment, and cognitive dysfunction resulting from ABI can negatively impact driving performance. OBJECTIVE: This manuscript examines the post-injury return-to-driving process, including performances on the in-office and on-road assessments, and the role of a rehabilitation neuropsychologist in helping patients resume driving. METHOD: In this study, 39 of 200 individuals (approximately 20%) treated at an outpatient neurorehabilitation facility, who performed satisfactorily on a pre-driving cognitive screening, completed a behind-the-wheel driving test. RESULTS: Of the 200 individuals, 34 (87%) passed the road test. Among the remaining five individuals who did not pass the road test, primary reasons for their failure included inability to follow or retain examiner directions primarily about lane position, speed, and vehicle control. The errors were attributable to cognitive difficulties with information processing, memory, attention regulation, and dual tasking. CONCLUSION The rehabilitation neuropsychologist contributed to the process by assessing cognition, facilitating self-awareness and error minimization, providing education about driving regulations and safety standards, and preparing for the road test and its outcomes.

Configuration development and optimization of hydraulically interconnected suspension for handling and ride enhancement

In this study, among 180 possible hydraulically interconnected suspension configurations, non-symmetric cases were eliminated and 24 potential configurations were selected for further investigation. A 14-DOF vehicle model capable of generating handling and ride motions is developed. At different manoeuvres and road inputs, the handling and ride performances are investigated for 24 configurations. Six hydraulic parameters are then optimized by the application of genetic algorithm in order to improve the ride. The handling performance is also investigated and results have shown that only four configurations provide better ride and handling performances simultaneously. The bounce acceleration response is shown to be reduced up to 47% for the four selected configurations. The roll and pitch angle responses were also reduced around 3% and 18% respectively. Four optimized configurations were also investigated under two sever ride and handling manoeuvres. It is shown that, for the vehicle with the optimized interconnected hydraulic suspension, the bounce acceleration response for a random road test is reduced up to 27% and the roll angle is reduced up to 18% for a side wind test.

Retraction: Loiselle-Lapointe et al. Chevrolet Volt On-Road Test Programs in Canada Part 1: Effects of Drive Cycle, Ambient Temperature and Accessory Usage on Energy Consumption and Electric Range. World Electr. Veh. J. 2015, 7, 142–153

The journal retracts the article, “Chevrolet Volt on-road test programs in Canada part 1: Effects of drive cycle, ambient temperature and accessory usage on energy consumption and electric range” [...]

The SIMARD-MD is not an Effective Driver Screening Tool for Determining Fitness-To-Drive

Background Studies have reported poor sensitivity and specificity of the Screen for the Identification of Cognitively Impaired Medically At-Risk Drivers, a modification of the DemTech (SIMARD-MD) to screen for drivers with cognitive impair­ment. The purpose of this study was to determine whether the SIMARD-MD can accurately predict pass/fail on a road test in drivers with cognitive impairment (CI) and healthy drivers. Methods Data from drivers with CI were collected from two compre­hensive driving assessment centres (n=86) and compared with healthy drivers (n=30). All participants completed demo­graphic measures, clinical measures, and a road rest (pass/fail). Analyses consisted of correlations between the SIMARD-MD and the other clinical measures, and a receiver-operating-characteristic (ROC) curve to determine the predictive ability of the SIMARD-MD. Results All healthy drivers passed the road test compared with 44.2% of the CI sample. On the SIMARD-MD, the CI sample scored significantly worse than healthy drivers (p < .001). The ROC curve showed the SIMARD-MD, regardless of any cut-point, misclassified a large number of CI individuals (AUC=.692; 95% CI = 0.578, 0.806). Conclusions Given the high level of misclassification, the SIMARD-MD should not be used with either healthy drivers or those with cognitive impairment for making decisions about driving.