The relationship between mental workload and driving performance of ageing drivers / Nurul Izzah Abd Rahman

• Main Author: Nurul Izzah , Abd Rahman
• Format: Thesis
• Published: 2020
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://studentsrepo.um.edu.my/12450/2/Nurul_Izzah.pdf; http://studentsrepo.um.edu.my/12450/1/Nurul_Izzah.pdf; http://studentsrepo.um.edu.my/12450/

The population of ageing drivers is increasing rapidly. As ageing happened, they are exposed to disabilities due to degenerative processes, thus affecting their driving performance. For changes in driving method or design to occur, ageing drivers’ driving tasks need to be monitored, designed and tested. Comprehensive research needs to be conducted to investigate how to integrate mental workload with driving performance of ageing people. Moreover, there has been no study yet that develop a model to predict overall driving performance in Malaysia. Hence, the main objective of this study is to develop and validate a model which quantifies the mental workload on the driving performance of ageing drivers. In this study, the methodology consisted of database observations, survey and on-the-road experimental tasks. For the experimental tasks, the measurements involved were subjective ratings using NASA Task Load Index (NASA TLX), physiological measure using electroencephalogram, number of traffic violations (NTVs), speed variability, and reaction time of peripheral detection. The accident database showed that the accident occurrences appear to be much higher among male drivers. From the survey on 182 drivers, about 60% of ageing drivers have been involved in accidents previously; driving experience has significant association with accident involvement. They have driving difficulties during rain (72%), rush hour (57%) and nighttime (59%). From the experimental tasks, the NASA-Task Load Index scores revealed that the ageing drivers’ subjective workload ratings increased with higher complexity situation. Their mean physical demand score was the highest compared to others in Moderately Complex Situation (MCS) and Very Complex Situation (VCS); scoring 37.25 and 43.50 respectively. Meanwhile, for Electroencephalogram signals’ fluctuation, results showed that situation complexity had significant effects on RPθ and RPα of channel locations FZPZ and O1O2. Both frequencies were lower in VCS compared to MCS. In addition, RPθ and RPα were significantly higher among male drivers compared to female, regardless of the situation complexity and ToT. Findings revealed that the highest mean number of traffic violations was in VCS where it was 35% higher compared to Simple Situation (SS). Furthermore, results showed that the mean speed in SS was significantly higher than MCS (42%) and VCS (38%), while the mean speed variability in MCS was significantly lower than SS (25%) and VCS (35%). The maximum reaction time was in VCS where it was 6% slower than the minimum reaction time obtained in MCS. Regression models were developed to determine Overall Driving Performance Score (ODPS) of each situation complexity based on the strong correlation and linear relationship between mental workload and driving performance elements. The relationship among these variables is significantly linear in SS (R=0.861), MCS (R=0.813) and VCS (R=0.749). All three models have been validated using data from different groups of drivers. The models would be beneficial as a guideline for designers, manufacturers, developers and policy makers in designing better driving environment for ageing drivers. They will be able to integrate safety and transportation to optimize and sustain driving performance while minimizing accident risks for ageing drivers as well as other road users.