Objective The aim of this paper was to synthesize the experimental research on factors that affect takeover performance during conditionally automated driving. Background For conditionally automated driving, the automated driving system (ADS) can handle the entire dynamic driving task but only for limited domains. When the system reaches a limit, the driver is responsible for taking over vehicle control, which may be affected by how much time they are provided to take over, what they were doing prior to the takeover, or the type of information provided to them during the takeover. Method Out of 8446 articles identified by a systematic literature search, 48 articles containing 51 experiments were included in the meta-analysis. Coded independent variables were time budget, non-driving related task engagement and resource demands, and information support during the takeover. Coded dependent variables were takeover timing and quality measures. Results Engaging in non-driving related tasks results in degraded takeover performance, particularly if it has overlapping resource demands with the driving task. Weak evidence suggests takeover performance is impaired with shorter time budgets. Current implementations of information support did not affect takeover performance. Conclusion Future research and implementation should focus on providing the driver more time to take over while automation is active and should further explore information support. Application The results of the current paper indicate the need for the development and deployment of vehicle-to-everything (V2X) services and driver monitoring.

Despite ample research on the effects of cell phone conversations on driving, the effects of such conversations on the looming threshold for an immediate hazard are not known. Prior research on the looming threshold for an immediate hazard in the absence of cell phone conversation indicated that the rate of optical expansion at threshold was .006 radians per second. We measured the rate of optical expansion and headway distance at first driving input when participants encountered a stopped lead vehicle while completing a car-following task. Half of them concurrently completed the Last Letter Task, a cognitive task that emulates a cell phone conversation. When compared to the second, third, and fourth scenario exposures to the stopped lead vehicle, the participant’s response on the first scenario exposure occurred when the lead vehicle’s optical expansion rate was relatively smaller and headway distance was larger. However, this effect of scenario exposure occurred only when drivers were engaged in a cell phone conversation. Additionally, participants started to initiate a response when the rate of optical expansion was much lower than the looming threshold reported in previous research. Our results indicate that the first driver input, as operationalized in the current study, does not indicate when drivers first perceive an immediate hazard.

Objective To measure the looming threshold for when drivers perceive closing and an immediate hazard and determine what factors affect these thresholds. Background Rear-end collisions are a common type of crash. One key issue is determining when drivers first perceive they need to react. The looming threshold for closing and an immediate hazard are critical perceptual thresholds that reflect when drivers perceive they need to react. Method Two driving simulator experiments examined whether engaging in a cell phone conversation and whether the complexity of the roadway environment affect these thresholds for the perception of closing and immediate hazard. Half of the participants engaged in a cognitive task, the last letter task, to emulate a cell phone conversation, and all participants experienced both simple and complex roadway environments. Results Drivers perceived an immediate hazard later when engaged in a cell phone conversation than when not engaged in a conversation but only when the driving task was relatively less demanding (e.g., simple roadway, slow closing velocity). Compared to simple scenes, drivers perceived closing and an immediate hazard later for complex scenes but only when closing velocity was 30 mph (48.28 km/h) or greater. Conclusion Cell phone conversation can affect when drivers perceive an immediate hazard when the roadway is less demanding. Roadway complexity can affect when drivers perceive closing and an immediate hazard when closing velocity is high. Application Results can aid accident analysis cases and the design of driving automation systems by suggesting when a typical driver would respond.

Phishing emails pose a serious threat to individuals and organizations. Users’ ability to identify phishing emails is critical to avoid becoming victims of these attacks. The current study examined the effectiveness of a short online phishing training program designed to help users identify phishing emails. Half of the participants were in the training group and the other half worked on a control filler task. The training group’s sensitivity ( d′) at correctly classifying emails as legitimate or phishing increased by 1.14 whereas the control group’s sensitivity increased by only 0.48. This difference in d' changes was significant, t(38) = 2.05, p = .048. This improvement in performance was likely due to users learning how to check reliable cues and interpret them. Despite a sizeable improvement in detecting phishing emails, the training group correctly classified only about two-thirds of phishing emails. Accordingly, a short training program appears beneficial, but a more comprehensive training program would be needed to reduce vulnerability to an acceptable level.

The aim of the current study was to determine whether drivers’ responses to stopped and slow-moving lead vehicles transition gradually in phases, each associated with a distinct optical expansion rate. We also examined whether results were affected by a cell phone conversation and expectancy. We used a driving simulator to assess six response inputs of (1) begins to release the accelerator, (2) releases accelerator completely, (3) starts to press brake (4) comfort-level braking (5) unanticipated-level braking and (6) brake pedal pressed more than 90 percent. Optical expansion rate differed among the first four inputs (the fifth and sixth did not occur enough to analyze), meaning drivers respond to lead vehicles in phases. When drivers were not engaged in a cell phone conversation, optical expansion rate for the perceptual event preceding unanticipated braking was greater when the lead vehicle was stopped compared to slowed. Expectancy did not affect optical expansion rates.