The influence of personality and cognitive failures on distracted driving behaviors among young adults

Distracted driving is a major safety concern. This paper explores the role personality traits and self-reported cognitive failures play in the propensity towards distracted driving behavior (DDB) among young adults in the United States. Two independent time-separated studies (study 1 with 522 participants; study 2 with 314 participants) confirm the role of cognitive failures as a mediator between specific personality traits and DDB propensity among young adult drivers. The results of this study suggest drivers’ personality traits such as extraversion, conscientiousness, and neuroticism have a direct impact on DDB propensity. In addition, there is evidence that cognitive failure mediates the relationship between these three personality traits and DDB propensity. Lastly, based on the results, agreeableness moderates the relationship between cognitive failure and DDB propensity. Together, these findings suggest that personality traits should be considered in conjunction with driver’s cognitive failure in explaining DDB propensity. Future research using a combination of self-reported, naturalistic and simulation studies may provide additional insight into the relationships between personality traits, cognitive failures, and the propensity towards DDB.     

Multimodal travel behaviour,attitudes, and cognitive dissonance

Multimodal travel behaviour, also termed multimodality, refers to as the phenomenon of an individual using more than one mode of transport in a given period. Studies indicate that encouraging multimodality may provide a solution to induce modal shifts towards sustainable transport. In this research, we investigate the distribution of mode-specific attitudes and attitude-mode use incompatibilities across clusters and levels of multimodality using the Netherlands Mobility Panel. We find that the most positive attitude does not necessarily correspond to the mode with the highest level of use. Attitudes towards car use are most positive, independent of the cluster membership and levels of multimodality. We also find that multimodal public transport users (compared with car-dominant users) and those with a higher level of multimodality are more likely to be attitudinally incompatible with frequently-used modes and the composition of their existing mode sets of travelling. This suggests that multimodal individuals may tend to experience cognitive dissonance with their mode use. Our findings also help uncover the psychological mechanism underlying a recent important finding that multimodal individuals are inclined to change their mode use patterns over time.     

Bio-inspired task-rule retrieval model with auditory sorting test

Cognitive architectures (CAs) are currently used to bring the behavior of computer systems closer to human behavior. One of the main capacities of humans is the ability to plan and make decisions. Thus, part of the human behavior is based on rules associated with the relevant environmental stimuli. Rule management can be divided into six needed processes: rule learning, rule retrieving, rule coding, rule updating, rule reinforcement, and rule changing. A key aspect of rule processing is retrieval, which involves the use of information extracted from memory. This work deals with how rules are stored in coded form in the brain, retrieved and used as the need arises. The proposed model takes inspiration mainly from the processes in the VLPFC and MTL brain areas to extract rules from memory and create a rule-set that is sent to the DLPFC. The DLPFC and VLPFC prefrontal area operations are also described, and a process is proposed to select the appropriate rule and give a response. The experimentation of the implementation of our proposal with different configuration parameters gives rise to different approaches to human behavior in rule retrieval. Our conclusion is that after a virtual entity is endowed with this proposal, it computes in a way similar to human behavior.     

Unveiling the reasoning processes of robots through introspective dialogues in a storytelling system: A study on the elicited empathy

The work studies the empathy elicited by a storytelling system in which the characters in the story are interpreted by humanoid robots and modelled as cognitive agents. The ACT-R architecture is exploited to shape the characters’ personalities and equip them with knowledge and behaviours typical of social practices. The narration is enriched with gestures and emotional expressions obtained by setting parameters that can be correlated to some emotions, such as the pitch and speech rate, the LEDs colour and the head inclination. The system has been evaluated by comparing a simple narrative modality with an enhanced one, where an introspective dialogue is adopted to explain and let transparent the internal reasoning processes of the characters. The obtained results show that storytelling affected the cognitive component of empathy, especially through the advanced narrative mode.     

Human vs. supervised machine learning: Who learns patterns faster?

The capabilities of supervised machine learning (SML), especially compared to human abilities, are being discussed in scientific research and in the usage of SML. This study provides an answer to how learning performance differs between humans and machines when there is limited training data. We have designed an experiment in which 44 humans and three different machine learning algorithms identify patterns in labeled training data and have to label instances according to the patterns they find. The results show a high dependency between performance and the underlying patterns of the task. Whereas humans perform relatively similarly across all patterns, machines show large performance differences for the various patterns in our experiment. After seeing 20 instances in the experiment, human performance does not improve anymore, which we relate to theories of cognitive overload. Machines learn slower but can reach the same level or may even outperform humans in 2 of the 4 of used patterns. However, machines need more instances compared to humans for the same results. The performance of machines is comparably lower for the other 2 patterns due to the difficulty of combining input features.     

Positive affect moderates inhibitory control and positive affect following a single bout of self-select aerobic exercise

PurposeResearch suggests that individual differences in baseline cognitive performance moderates subsequent cognitive benefits following a single bout of exercise. The present study seeks to evaluate additional moderating mental states – specifically positive affect – on inhibitory control and affect following exercise.MethodsUsing a within- and between-participants pre-post cross-over design, eighty university students (54 females; 21.7 ± 2.7 years old) completed a flanker task and affect measures before and after a single bout of aerobic exercise at a self-selected intensity or studying for class (15-min) on separate days. Groups of high-positive affect (HPA; n = 41) and low-positive affect (LPA; n = 39) were determined based on a median split of positive affect measures prior to the exercise bout.ResultsThe HPA group revealed shorter reaction time (RT) from before to after exercise and rest with no difference observed between exercise and rest. The LPA group revealed shorter RT after exercise compared to before exercise and after rest. For accuracy, the LPA group improved performance during the exercise session compared to the rest session to a level comparable to the HPA group. Lastly, positive affect decreased in the LPA and HPA groups from before to after rest; however, only the LPA group’s positive affect increased from before to after exercise.ConclusionIndividuals with low positive affect experience greater cognitive and positive affect improvements following acute aerobic exercise at a self-select intensity, further supporting intraindividual differences in mental states as a mechanism for subsequent cognitive and affective benefits encompassing healthy behaviors of exercise.     

Decision processes in temporal discrimination

The processing dynamics underlying temporal decisions and the response times they generate have received little attention in the study of interval timing. In contrast, models of other simple forms of decision making have been extensively investigated using response times, leading to a substantial disconnect between temporal and non-temporal decision theories. An overarching decision-theoretic framework that encompasses existing, non-temporal decision models may, however, account both for interval timing itself and for time-based decision-making. We sought evidence for this framework in the temporal discrimination performance of humans tested on the temporal bisection task. In this task, participants retrospectively categorized experienced stimulus durations as short or long based on their perceived similarity to two, remembered reference durations and were rewarded only for correct categorization of these references. Our analysis of choice proportions and response times suggests that a two-stage, sequential diffusion process, parameterized to maximize earned rewards, can account for salient patterns of bisection performance. The first diffusion stage times intervals by accumulating an endogenously noisy clock signal; the second stage makes decisions about the first-stage temporal representation by accumulating first-stage evidence corrupted by endogenous noise. Reward-maximization requires that the second-stage accumulation rate and starting point be based on the state of the first-stage timer at the end of the stimulus duration, and that estimates of non-decision-related delays should decrease as a function of stimulus duration. Results are in accord with these predictions and thus support an extension of the drift–diffusion model of static decision making to the domain of interval timing and temporal decisions.     

Visual content of words delays negation

Many studies have shown the advantage of processing visualizable words over non-visualizables due to the associated image code. The present paper reports the case of negation in which imagery could slow down processing. Negation reverses the truth value of a proposition from false to true or vice versa. Consequently, negation works only on propositions (reversing their truth value) and cannot apply directly to other forms of knowledge representation such as images (although they can be veridical or not). This leads to a paradoxical hypothesis: despite the advantage of visualizable words for general processing, the negation of clauses containing words related to the representation of an image would be more difficult than negation containing non-visualizable words. Two experiments support this hypothesis by showing that sentences with a previously negated visualizable word took longer to be read than sentences with previously negated non-visualizable words. The results suggest that a verbal code is used to process negation.     

When two actions are easier than one: How inhibitory control demands affect response processing

Numerous studies showed that the simultaneous execution of multiple actions is associated with performance costs. Here, we demonstrate that when highly automatic responses are involved, performance in single-response conditions can actually be worse than in dual-response conditions. Participants responded to peripheral visual stimuli with an eye movement (saccade), a manual key press, or both. To manipulate saccade automaticity, a central fixation cross either remained present throughout the trial (overlap condition, lower automaticity) or disappeared 200 ms before visual target onset (gap condition, greater automaticity). Crucially, single-response conditions yielded more performance errors than dual-response conditions (i.e., dual-response benefit), especially in gap trials. This was due to difficulties associated with inhibiting saccades when only manual responses were required, suggesting that response inhibition (remaining fixated) can be even more resource-demanding than overt response execution (saccade to peripheral target).