Improved mental representation of space in beginner orienteers

The purpose of the present study was to monitor any improvement in orienteering skills attributable to acquiring a better mental representation of space. Two groups were examined: the experimental group, who attended 6 mo. of orienteering lessons, versus the control group, who did jogging training instead. Each group, consisting of 20 children, was tested on the Corsi Block-tapping Test, run Forward and Backward, and the Star-Butterfly Test. Pre- and post-tests were administered. In the experimental group, scores increased in mean complexity from pre- to post-test on the Forward and the Backward Corsi tests, while on the Star-Butterfly Test both time and mistakes had decreased after the training. In the control group, mean complexity and Star-Butterfly Test scores were unchanged from pre- to post-test. These results showed that after continual training in orienteering techniques, the orienteering group was able to remember and repeat sequences of events with greater precision than before the training, while these skills were unchanged in the control group after training in jogging.     

Dissociated deficits of visuo-spatial memory in near space and navigational space: evidence from brain-damaged patients and healthy older participants

Defects confined to spatial memory can severely affect a variety of daily life activities, such as remembering the location of objects or navigating the environment, until now the skills involved have been mostly assessed with regard to the visual domain using traditional pencil and paper tests. Our aim was to test the efficacy of a recently developed psychometric instrument (Walking Corsi Test: WalCT) to assess the specific contribution of spatial memory to the complex task of retrieving route knowledge. The WalCT is a 3 × 2.5-m version of the well-known Corsi Block-tapping Test (CBT), in which patients are required to memorize (and replicate) a sequence of body displacements. We assessed the ability of left and right brain-damaged patients, as well as healthy young and senior controls, to perform both the CBT and the WalCT. Results showed differences related to age in the healthy individuals and specific functional dissociations in the brain-damaged patients. The double dissociations found in this study demonstrate the importance of having a task able to detect navigational disorders, because virtual reality tasks are often much too difficult for aged brain-damaged patients to perform.     

Dissociated deficits of visuo-spatial memory in near space and navigational space: Evidence from brain-damaged patients and healthy older participants

ABSTRACT

Defects confined to spatial memory can severely affect a variety of daily life activities, such as remembering the location of objects or navigating the environment, until now the skills involved have been mostly assessed with regard to the visual domain using traditional pencil and paper tests. Our aim was to test the efficacy of a recently developed psychometric instrument (Walking Corsi Test: WalCT) to assess the specific contribution of spatial memory to the complex task of retrieving route knowledge. The WalCT is a 3×2.5-m version of the well-known Corsi Block-tapping Test (CBT), in which patients are required to memorize (and replicate) a sequence of body displacements. We assessed the ability of left and right brain-damaged patients, as well as healthy young and senior controls, to perform both the CBT and the WalCT. Results showed differences related to age in the healthy individuals and specific functional dissociations in the brain-damaged patients. The double dissociations found in this study demonstrate the importance of having a task able to detect navigational disorders, because virtual reality tasks are often much too difficult for aged brain-damaged patients to perform.     

Performance, workload, and fatigue changes associated with automation

The experiments discussed in this article addressed the influence of part-task automation on operator performance, workload, and fatigue in a multitask environment. The overall task environment included tracking, resource management, and multiple monitoring subtasks. Slower, more accurate monitoring and better resource management were observed when the tracking subtask was automated. Although lower workload was reported when tracking was automated, fatigue increased equally during periods of manual and automatic tracking. When participants could control workload by shifting between manual and automatic tracking, participants with 7 hr of training switched between automatic and manual tracking. Their performance during optional automation periods was superior to their performance in conditions in which only manual control or only automated control was available. The findings argue for the utility of discretionary control of automated systems.     

The role of psychological factors on the choice of different driving controls: On manual,partial, and highly automated controls

The present study investigates the role of psychological factors on the choice of three controls (modes) in driving a vehicle, namely highly automated, partially automated, and manual control. Traditional driving habits, resistance to change, and behavioural beliefs were all assessed along with individual and socioeconomic variables. Using survey data (n = 595) of car users, a model was developed to predict the share of different driving controls and determine the effects of psychological variables. Results indicate that up to 55% of people prefer driving with highly automated control, and 30% prefer partially automated control. Behavioural beliefs (e.g., attitudes toward highly automated control) are not as critical to driving control as habits. People with stronger driving habits are less likely to use highly automated controls. A one-unit increase in worry could reduce driving in highly automated control by 5.5% and increase manual control by 4.5%, and those who welcome the new technologies are more likely to prefer highly automated control. Some practical policy solutions are also provided.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Keeping the driver in the loop in conditionally automated driving: A perception-action theory approach

In this paper we investigated if keeping the driver in the perception–action loop during automated driving can improve take-over behavior from conditionally automated driving. To meet this aim, we designed an experiment in which visual exposure (perception) and manual control exposure (action) were manipulated. In a dynamic driving simulator experiment, participants (n = 88) performed a non-driving related task either in a head-up display in the windshield (high visual exposure) or on a head-down display near the gear shift (low visual exposure). While driving, participants were either in an intermittent control-mode with four noncritical take-over situations (high manual control exposure), or in a continuous automation-mode throughout the ride (low manual control exposure). In all conditions, a critical take-over had to be carried out after an approximately 13 min ride. Measurements of take-over behavior showed that only high visual exposure had an effect on hands-on reaction time measurements. Both visual exposure and manual control exposure had small to medium sized main effects on time to system deactivation, the maximum velocity of the steering wheel, and the standard deviation of the steering wheel angle. The combined high visual – and high manual control exposure condition led to 0.55 s faster reaction time and 37% less steering variability in comparison to the worst case low visual – and low manual control exposure condition. Together, results corroborate that maintaining visual exposure and manual control exposure during automated driving can be efficacious and suggest that their positive effects are additive.     

Correlation between tests of attention and performance on grooved and Purdue pegboards in normal subjects

This study investigated the relation between tests of manual dexterity and attentional functions with 49 normal, right-handed medical students (26 women, 23 men, ages 19-30 years) who were assessed with a Purdue Pegboard Test, Grooved Pegboard Test, and a Test for Attentional Performance, comprising measures of tonic and phasic alertness and divided attention. Weak to moderately high partial correlations controlling for finger size were obtained between pegboard test performance of the left hand and phasic alertness (r = .31-.50). Purdue Pegboard Assembly subtest scores were weakly correlated with divided attention (r = -.39). These findings suggest that attention is an important determinant of performance for manual dexterity tests of the nondominant hand.     

Assessing the effect of long-automated driving operation,repeated take-over requests,and driver’s characteristics on commercial motor vehicle drivers’ driving behavior and reaction time in highly automated vehicles

Automated Commercial Motor Vehicles (CMVs) have the potential to reduce the occurrence of crashes, enhance traffic flow, and reduce the stress of driving to a larger extent. Since fully automated driving (SAE Level 5) is not yet available, automated driving systems cannot perform all driving tasks under all road conditions. Drivers need to regain the vehicle’s control when the system reaches its maximum operational capabilities. This transition from automated to manual is referred to as Take-Over Request (TOR). Evaluating driver’s performance after TORs and assessing effective parameters have gained much attention in recent years. However, few studies have addressed CMV drivers’ driving behavior after TOR and the effect of long-automated driving and repeated TORs. This paper aims to address this gap and gain behavioral insights into CMV drivers’ driving behavior after TOR and assess the effect of the duration of automated operation before TOR, repeated TORs, and driver characteristics (e.g., age, gender, education, and driving history). To accomplish this, we designed a 40-minutes experiment on a driving simulator and assessed the responses of certified CMV drivers to TORs. Drivers’ reaction time and driving behavior indices (e.g., acceleration, velocity, and headway) are compared to continuous manual driving to measure driving behavior differences. Results showed that CMV drivers’ driving behavior changes significantly after the transition to manual regardless of the number of TORs and the duration of automated driving. Findings suggest that 30 min of automated operation intensifies the effect of TOR on driving behaviors. In addition, repeated TOR improves reaction times to TOR and reduces drivers' maximum and minimum speed after TORs. Driver’s age and driving history showed significant effects on reaction time and some driving behavior indices. The findings of this paper provide valuable information to automotive companies and transportation planners on the nature of driver behavior changes due to the carryover effects of manual driving right after automated driving episodes in highly automated vehicles.     

Take-over requests in highly automated driving: A crowdsourcing survey on auditory,vibrotactile, and visual displays

An important research question in the domain of highly automated driving is how to aid drivers in transitions between manual and automated control. Until highly automated cars are available, knowledge on this topic has to be obtained via simulators and self-report questionnaires. Using crowdsourcing, we surveyed 1692 people on auditory, visual, and vibrotactile take-over requests (TORs) in highly automated driving. The survey presented recordings of auditory messages and illustrations of visual and vibrational messages in traffic scenarios of various urgency levels. Multimodal TORs were the most preferred option in high-urgency scenarios. Auditory TORs were the most preferred option in low-urgency scenarios and as a confirmation message that the system is ready to switch from manual to automated mode. For low-urgency scenarios, visual-only TORs were more preferred than vibration-only TORs. Beeps with shorter interpulse intervals were perceived as more urgent, with Stevens’ power law yielding an accurate fit to the data. Spoken messages were more accepted than abstract sounds, and the female voice was more preferred than the male voice. Preferences and perceived urgency ratings were similar in middle- and high-income countries. In summary, this international survey showed that people’s preferences for TOR types in highly automated driving depend on the urgency of the situation.     

Alternative options for dealing with automation failures: Automated stopping vs. Taking over manual control

Previous research has investigated the driver’s ability to resume control after an automation failure. This study considers situation criticality, safety and difficulty between take-over and automated stop scenarios. Findings are reported of an experimental study investigating different strategies to take back control of an automated road vehicle. The study had a mixed factorial design with automation being the between-participants factor with two levels, SAE Level 1 vs. SAE Level 3. Urgency (High vs Low) and Take-Over Mode (Manual, Automated Stop) were the within participants factors. Dependent variables were: i) Minimum Time-to-Collision (TTC), ii) Self-reported Situation Criticality and Perceived Safety and iii) Percentage of Gazes to [the] Road Centre. Overall, 36 participants took part, with half assigned to either level of the Automation factor. The automated driving experience was designed to fail during participation. This required the driver to take-over manual control or have the system bring the vehicle to an automated stop. Results revealed that during manual take-over of control, measures of time-to-collision, perceived criticality and safety were worse and fixations to the forward view increased when compared to the Automated stop condition. Manual take-over of control in a high-urgency situation revealed higher criticality (shorter time-to-collision and lower perceived safety) and more difficulty (increasing fixations to the road centre) than in a low-urgency situation. The study points to an automated stopping manoeuvre being the preferable strategy to manual take-over of control.     

APDA: A discontiguous S-R automated primate discrimination apparatus

The present paper describes a discontiguous S-R automated primate discrimination apparatus (APDA) designed to eliminate the stimulus sampling biases associated with previous manual and automated testing procedures and at the same time to provide greater specification of the S's intratrial discrimination behavior. Data from two simultaneous color discrimination problems are summarized as an evaluation of the current design.     

Measuring drivers’ takeover performance in varying levels of automation: Considering the influence of cognitive secondary task

Mixed control by driver and automated system will remain in use for decades until fully automated driving is perfected. Thus, drivers must be able to accurately regain control of vehicles in a timely manner when the automated system sends a takeover request (TOR) at its limitation. Therefore, determining the factors that affect drivers’ takeover quality at varying levels of automated driving is important. Previous studies have shown that visually distracting secondary tasks impair drivers’ takeover performance and increase the subjective workload. However, the influence of purely cognitive distracting secondary tasks on drivers’ takeover performance and how this influence varies at different levels of automation are still unknown. Hence, a 5 (driving modes) × 3 (cognitive secondary tasks) factorial design with the within-subject factors was adopted for this driving simulator experiment. The sample consisted of 21 participants. The participants’ subjective workloads were recorded by the NASA-Task Load Index (NASA-TLX). Results showed that compared to manual driving conditions, the drivers’ subjective workloads were significantly reduced in both partially and highly automated driving conditions, even with a TOR, confirming the benefit of the automated driving system in terms of reducing the driving workload. Moreover, the drivers exhibited a lower takeover behavior quality at high levels of automation than manual driving in terms of increased reaction time, abnormal performance, standard deviation of lane position, lane departure probability, and reduced minimum of time to collision. However, at the highly automated driving condition, the drivers’ longitudinal driving safety and ability to follow instructions improved when performing a highly cognitive secondary task. This phenomenon possibly occurred because automated driving conditions lead to an underload phenomenon, and the execution of highly cognitive tasks transfers drivers into moderate load, which helps with the drivers’ takeover performance.     

Automatic stimulus presentation for the proboscis extension reflex in diptera

An apparatus is described that automates the elicitation of the proboscis extension reflex (PER) in dipterans. The PER has been used as a measure of both classical conditioning and central excitation. Most studies of PER have employed manual stimulation, which adds inter- and intraexperimenter differences in technique as another source of variance. The advantages of this apparatus are (1) elimination of individual differences in manual techniques of experimenters as a possible source of error variance and (2) capability of stimulating several flies individually during a single session. An experiment is reported comparing the manual and automated methods.     

On-Road vehicle study of the experience of automated driving

Prior studies of automated driving have focused on drivers’ evaluations of advanced driving assistance systems and their knowledge of the technology. An on-road experiment with novice drivers who had never used automated systems was conducted to examine the effects of the automation on the driving experience. Participants drove a Tesla Model 3 sedan with level 2 automation engaged or not engaged on a 4-lane interstate freeway. They reported that driving was more enjoyable and less stressful during automated driving than manual driving. They also indicated that they were less anxious and nervous, and able to relax more with the automation. Their intentions to use and purchase automated systems in the future were correlated with the favorableness of their automated driving experiences. The positive experiences of the first-time users suggest that consumers may not need a great deal of persuading to develop an appreciation for partially automated vehicles.     

What and how to tell beforehand: The effect of user education on understanding,interaction and satisfaction with driving automation

The success of introducing automated driving systems to consumers will depend on an appropriate understanding and human-automation interaction with this technology. Educating users on driving automation technology bears the potential to attain these two requirements. In a driving simulator study, we investigated the effects of user education on mental models, human-automation interaction performance (i.e., time on task, error rate, experimenter rating) and satisfaction with a Human-Machine Interface (HMI) for automated driving. N = 80 participants were randomly assigned to one of three different user education conditions or to a baseline. Subsequently, they completed several driver-initiated control transitions between manual, Level 2 (L2), and Level 3 (L3) automated driving. The results revealed that user education promoted an accurate evolution of mental models for driving automation. These, in turn, facilitated interaction performance in transitions from manual to both L2 and L3 automated driving. There was no comparable influence of prior education on performance in transitions between the automation levels. Due to the performance enhancing effects of user education, no further improvements of interaction performance were observed for educated users in comparison to uneducated users. There was no effect of user education on satisfaction. The current findings emphasize the necessity to provide information about automated vehicle HMIs to first-time users to support accurate understanding and behavior. Based on the current findings, we propose conceptual approaches to teach users and derive implications for user studies on automated vehicle HMIs.     

Impact of automation on aircrew communication and decision-making performance

Increasing levels of automation are being introduced into the cockpit. Yet, it is difficult to predict the impact of these automatic systems on other elements of flight, such as crew communication and the ability to arrive at an effective decision. This study attempted to clarify the relation among these variables. Forty-eight pilots were assigned to two-person crews and asked to fly a simulated mission in either automated or manual conditions using a low-fidelity simulator. The scenario was designed to require crewmembers to arrive at a collective decision based on information obtained about an evolving simulated disaster. The results indicated that the introduction of automation was not associated with better performance. However, several significant differences were observed in the communications of crews flying in the automated versus manual conditions. The results are discussed in terms of their implications for communications training for advanced technology aircraft.     

The semiautomatic Wisconsin general test apparatus

A semiautomatic version of the Wisconsin General Test Apparatus is described along with circuitry. Comparison data are provided for the semiautomatic and manual WGTA obtained under comparable procedures and conditions. Response latencies are given for go/no-go object discrimination problems and subsequent retention tests.     

The potential of gamification for user education in partial and conditional driving automation: A driving simulator study

Drivers must establish adequate mental models to ensure safe driver-vehicle interaction in combined partial and conditional driving automation. To achieve this, user education is considered crucial. Since gamification has previously shown positive effects on learning motivation and performance, it could serve as a measure to enhance user education on automated vehicles. We developed a tablet-based instruction involving gamified elements and compared it to instruction without gamification and a control group receiving a user manual. After instruction, participants (N = 57) experienced a 30-minute automated drive on a motorway in a fixed-base driving simulator. Participants who received the gamified instruction reported a higher level of intrinsic motivation to learn the provided content. The results also indicate that gamification promotes mental model formation and trust during the automated drive. Taken together, including gamification in user education for automated driving is a promising approach to enhance safe driver-vehicle interaction.     

Effects of secondary tasks and display position on glance behavior during partially automated driving

The driving task is becoming increasingly automated, thus changing the driver’s role. Moreover, in-vehicle information systems using different display positions and information processing channels might encourage secondary task engagement. During manual driving scenarios, varying secondary tasks and display positions could influence driver’s glance behavior. However, their impact on the driver’s capability to monitor the partially automated driving system has not yet been determined. The current study assessed both the effects of different secondary tasks (Surrogate Reference Task (SuRT) vs. text reading) and display positions (head-up display (HUD) vs. center console) on driver’s glance behavior during partially automated driving in a simulated car following task. Different automation system failures regarding the lateral and longitudinal control occurred while driving. Furthermore, participants’ reported advantages, disadvantages and preferences regarding the investigated display positions as well as regarding the secondary task engagement during partially automated driving in general. Mixed design ANOVAs revealed that the HUD yielded considerably longer eyes-on display time (total and mean glance durations) than the center console. Moreover, the text reading task resulted in longer total and mean glance durations than the SuRT. Similar to manual driving scenarios, the results showed a consistent effect of display position and secondary task on the driver’s glance behavior. Despite the longer eyes-on display time for the HUD, its proximity to the driving environment might enable a faster identification of and reaction to critical situations (e.g., due to system failures). Participants would prefer the HUD as display position compared to the center console. Regarding secondary task engagement during partially automated driving participants seemed to be aware of the benefits but also of the risks.