Effects of Task-Induced Fatigue in Prolonged Conditional Automated Driving.

OBJECTIVE: The aim of this study was to investigate the effects of task-induced fatigue in prolonged conditional automated driving on takeover performance. BACKGROUND: In conditional automated driving, the driver can engage in non-driving related tasks (NDRTs) and does not have to monitor the system and the driving environment. In the event that the system hits its limits, the human driver must regain control of the car. To ensure safety, adequate driver fallback performance is necessary. Effects of the drivers' state and the engagement in NDRTs need to be investigated. METHOD: Seventy-three participants experienced prolonged conditional automated rides and simultaneously had to engage in either an activating quiz or a fatiguing monitoring task (between subjects). After 50 minutes, a takeover situation occurred, and participants had to regain control of the car. RESULTS: Prolonged conditional automated driving and simultaneously engaging in NDRTs affected the driver's state and the takeover performance of the participants. Takeover performance was impaired when participants had to deal with monotonous NDRTs. CONCLUSION: An engagement in monotonous monitoring tasks in conditional automated driving affects the driver's state and takeover performance when it comes to takeover situations. Especially in prolonged automated driving, an adequate driver state seems to be necessary for safety reasons. APPLICATION: The results of this study demonstrate that engagement in monotonous NDRTs while driving conditionally automated may negatively affect takeover performance. A monitoring of the driver state and adapted assistance in a takeover situation seems to be a good opportunity to ensure safety.

Can We Study Autonomous Driving Comfort in Moving-Base Driving Simulators? A Validation Study.

OBJECTIVE: To lay the basis of studying autonomous driving comfort using driving simulators, we assessed the behavioral validity of two moving-base simulator configurations by contrasting them with a test-track setting. BACKGROUND: With increasing level of automation, driving comfort becomes increasingly important. Simulators provide a safe environment to study perceived comfort in autonomous driving. To date, however, no studies were conducted in relation to comfort in autonomous driving to determine the extent to which results from simulator studies can be transferred to on-road driving conditions. METHOD: Participants ( N = 72) experienced six differently parameterized lane-change and deceleration maneuvers and subsequently rated the comfort of each scenario. One group of participants experienced the maneuvers on a test-track setting, whereas two other groups experienced them in one of two moving-base simulator configurations. RESULTS: We could demonstrate relative and absolute validity for one of the two simulator configurations. Subsequent analyses revealed that the validity of the simulator highly depends on the parameterization of the motion system. CONCLUSION: Moving-base simulation can be a useful research tool to study driving comfort in autonomous vehicles. However, our results point at a preference for subunity scaling factors for both lateral and longitudinal motion cues, which might be explained by an underestimation of speed in virtual environments. APPLICATION: In line with previous studies, we recommend lateral- and longitudinal-motion scaling factors of approximately 50% to 60% in order to obtain valid results for both active and passive driving tasks.

The critical tracking task: a potentially useful method to assess driver distraction?

OBJECTIVE: We report on four experiments that investigated the critical tracking task's (CTT) potential as a tool to measure distraction. BACKGROUND: Assessment of the potential of new in-vehicle information systems to be distracting has become an important issue. An easy-to-use method, which might be a candidate to assess this distraction, is the CTT. The CTT requires an operator to stabilize a bar, which is displayed on a computer screen, such that it does not depart from a predefined target position. As the CTT reflects various basic aspects of the operational level of the driving task, we used it as a simple surrogate for driving to assess the CTT's capabilities. METHOD: We employed secondary tasks of varying demand, artificial tasks as well as tasks representative of secondary tasks while driving, and asked participants to perform them together with the CTT in parallel. CTT performance, secondary task performance, and subjective ratings of load were recorded and analyzed. RESULTS: Overall, the CTT was able to differentiate between different levels of demand elicited by the secondary tasks. The results obtained corresponded with our a priori assumptions about the respective secondary tasks' potential to distract. CONCLUSION: It appears that the CTT can be used to assess in-vehicle information systems with regard to their potential to distract drivers. Additional experiments are necessary to further clarify the relationship between driving and CTT performance. APPLICATION: The CTT can provide a cost-effective solution as part of a battery of tests for early testing of new in-vehicle devices.