Off-road fitness-to-drive assessment using driving simulator (Effect of fatigue level on fitness-to-drive)

• Main Author: Woo, Sabrina Jia Ling
• Other Authors: Wong Yiik Diew
• Format: Final Year Project
• Language: English
• Published: 2016
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/68042
• Institution: Nanyang Technological University

Motor vehicle crashes attributing to human causes have long been a controversial topic as to whether these human factors play a significant role in the result of these crashes. Fitness-to-drive, measured by performance indicators, is an excellent tool to assess the driving ability of a driver. Based on research done in the past, there is a lack of empirical evidence to prove that the fitness-to-drive of an individual is significantly related to the fatigue level (human factor) of that individual. Little has been done to address this issue, and thus, in this research project, we aimed to find out the relationship between the fitness-to-drive and fatigue level. Twenty-six consenting male and female participants belonging to different driving categories (active or inactive drivers), and whom were in a state of approximately zero fatigue level were randomly selected to participate in the two hour-long experimental session. The participants went through two sessions of the virtual driving course on a driving simulator situated at the laboratory. The former session was driven while they were in a fresh state of mind, while the latter was of them being in a fatigued state of mind, in which in between the two sessions there was a non-physical fatigued-induction session to adjust the participants’ fatigue level. Valuable experimental data were extracted from the four driving performance indicators (speed, variance of steering wheel position, mistakes made on navigational messages, collisions made), which govern the fitness to drive. For both the active and inactive drivers’ category, the results for the four driving performance indicators reflected a decrease in driving performance conditions (fitness-to-drive). For example, on the basis that higher vehicle speed means a more unstable condition for driving, the results obtained for the 11 active drivers showed that the average speed of the vehicle increased from the fresh to the fatigued state, implying that the fatigued state of the participants resulted in decrease in their fitness-to-drive. As for the other indicators, it was noted that there was lower variance of the steering wheel position, more mistakes made on navigational messages, and more collisions made, all of which implied that the fitness-to-drive of participants have decreased. However, for majority of the findings obtained, despite being evidently different in values, the difference between the results in the fresh and fatigued states was not statistically significant (from t-test results). Overall, the results showed that fatigue indeed does have a negative impact on one’s driving performance. This finding is vital and gives practical advancement to the transportation field of study. Future research on this area could explore other components of driving and cognitive performance, such as eye-gaze spread, response latency, etc.