Development and validation of the organisational cooperation questionnaire

IntroductionCooperation is an essential framework for the functioning of organisations and society. The limitations of current measures of organisational cooperation led us to construct the measure herein presented.ObjectiveThe paper aims to describe the development and psychometric validation of an organisational cooperation measure based on how the cooperating members view and experience the cooperation process.MethodBased on relevant literature, the items were built and submitted to a panel of experts and fine-tuning procedures. The instrument (31 items) was applied to 1354 employees in local authorities. Exploratory and confirmatory factor analysis were performed (2 sub-samples), as well as validation procedures through Pearson correlation with the Knowledge Management Questionnaire.ResultsResults showed good statistical indicators of a 22-items three-factor structure: principles of cooperative relationship; formal regulation of cooperation; and cooperation focused on organisational mission. The factors are interpreted theoretically and present high internal consistency. The validation process suggests the suitability of the instrument for the population studied.ConclusionThis instrument can be used as a starting point for organisational intervention when cooperation-intensive processes are relevant. It can be useful to characterize the existing cooperation in organisations and to foster cooperation in organisations, especially in the intended dimensions. Future studies can apply the instrument to various sectors of activity. It will also be worth studying cooperation in its relationship with other organisational variables, namely those concerning cooperation-intensive processes.     

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians’ crossing decisions are significantly affected by the participants’ age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.     

Effects of explanation types and perceived risk on trust in autonomous vehicles

Despite technological advances, trust still remains as a major issue facing autonomous vehicles. Existing studies have reported that explanations of the status of automation systems can be an effective strategy to increase trust, but these effects can differ depending on the forms of explanations and autonomous driving situations. To address this issue, this study examines the effects of explanation types and perceived risk on trust in autonomous vehicles. Three types of explanations (i.e., no, simple, and attributional explanations) are designed based on attribution theory. Additionally, four autonomous driving situations with different levels of risk are designed based on a simulator program. Results show that explanation type significantly affects trust in autonomous vehicles, and the perceived risk of driving situations significantly moderates the effect of the explanation type. At a high level of perceived risk, attributional explanations and no explanations lead to the lowest and highest values in trust, respectively. However, at a low level of perceived risk, these effects reverse.     

The effect of visual HMIs of a system assisting manual drivers in manoeuvre coordination in system limit and system failure situations

Ambiguous situations in traffic often require communication and cooperation between road users. In order to resolve these situations and increase cooperative driving behavior in situations of merging or turning left, manual drivers could be assisted by an advanced driver assistance system (ADAS) for cooperative driving. This simulator study investigated the behavior of drivers confronted with system limits and failures of such a system. The ADAS used in this study informed the driver about an upcoming cooperation situation and gave advice on how to behave (e.g. reduce speed, change lane). Two test situations were implemented: a system freeze and an unexpected event, which could not be detected by the system. In order to find the most fitting HMI solution, the place of presentation (head-up display (HUD) vs. instrument cluster) as well as the form of presentation (dynamic vs. symbolic) were varied. The results indicated that the most fitting HMI solution to support the driver in a complex coordinated driving situation is a dynamic HUD, mainly due to the positive effect on glance behavior. However, advantages of both forms of presentation were revealed, as each form of presentation increased the probability of recognition for one of the test situations. The fewest collisions took place with the dynamic form of presentation.     

Public perception of autonomous vehicles: A qualitative study based on interviews after riding an autonomous shuttle

Autonomous vehicles (AVs) can potentially compensate for human error whilst driving. Thus, the number of accidents and the amount of congestion, emissions and fuel consumption could be reduced. For such reduction to occur, insights into public acceptance of AVs must be considered because they are a crucial factor for the successful implementation of AVs in existing traffic systems.PurposeThis study aims to explore (1) the mobility behaviour of current passengers, (2) the perception of the public of how AVs can be applied, (3) the perceived challenges of AVs in terms of integration into existing traffic systems, (4) the general attitude of the public towards AVs and (5) the perceived safety of passengers after riding an autonomous shuttle with a maximum SAE level of 3 in the setting of mixed traffic.MethodThis qualitative study was conducted in Carinthia (Austria) in September 2018. Interviews were conducted with 19 participants aged between 20 and 75 years. The participants were recruited through purposeful sampling, and data were collected through in-depth, semistructured interviews which were recorded, transcribed, organised and analysed using systematic, qualitative content analysis.ResultsResults show that transport mobility plays an important role in social life. In rural areas, AVs can shift transportation modes from private cars to public transportation. The respondents perceive AVs as an alternative more than as a substitute for existing means of transportation. With the integration of AVs into existing traffic systems, the transportation of goods and people could be improved despite related uncertainties. This study explores different aspects of societal, technical, legal and economic challenges. Overall, the respondents feel positive about AVs. Responses regarding safety show that experience with AVs and speed are key factors.Originality/ValueThis study is one of the first to explain qualitatively public perceptions of AVs after an actual ride in an AV under real-life conditions. The results, which help understand AVs from the public’s perspective, may also provide guidelines for the successful integration of AVs in Austria.     

Situational influencing factors on understanding cooperative actions in automated driving

Cooperative interacting vehicles are a promising approach in the context of automated driving. To ensure understanding and acceptance of such systems, the underlying mechanisms of human cooperation in the context of traffic must be understood. In a driving simulator study, we investigated how situational factors influence cooperative behaviour in a lane change situation on a two-lane German highway during automated driving in the left lane. When another car in the right lane was approaching a slower truck, participants (N = 32) were asked by an automated system to either accelerate, decelerate or maintain speed. The driver’s scope of action, the situation’s criticality for the lane-changing vehicle and the display of intention to change lanes were manipulated. A hierarchical multinomial logistic regression revealed that a wider scope of action, a higher situation’s criticality and signalling the intention to change lanes positively influenced cooperative behaviour by accelerating and decelerating. These results might be applied to design user-centred automated cooperatively interacting vehicles.     

External HMI for self-driving vehicles: Which information shall be displayed?

The objective of this study was to investigate pedestrians’ informational needs towards self-driving vehicles (SDVs). Previous research has shown that external human-machine interfaces (eHMIs) compensate for pedestrian-driver communication when SDVs are integrated into traffic. However, detailed insights on which information the eHMI shall provide lack so far. In a mixed design study, N = 59 participants encountered a simulated driverless vehicle in different traffic scenarios (a. unsignalized intersection vs. b. parking lot; between-subject factor). We investigated the effect of no eHMI (baseline) vs. eHMIs displaying the automated driving system (ADS) status, and informing subsequently about its perception of the pedestrian and/or its intent for the next maneuver ((1) no eHMI, (2) status eHMI, (3) status + perception eHMI, (4) status + intent eHMI, (5) status + perception + intent eHMI; within-subject factor). A mixed-methods design was used to explore participants’ subjective feelings, traffic behavior, and underlying attitudes. The findings reveal that any eHMI contributes to a more positive feeling towards SDVs compared to the baseline condition without eHMI, consistent among traffic scenarios: participants felt significantly safer, reflected greater trust and user experience ratings, and perceived the SDV as more intelligent and transparent. The status indicator mainly drives these beneficial effects on subjective measures. Participants reported that the status information explains the absence of a driver steering the vehicle. Compared to the status eHMI, the status + perception eHMI reflects no further benefit regarding subjective feelings and even has a negative impact on traffic flow. Moreover, participants regarded the additional information on the vehicle’s perception as an obvious gimmick. On the contrary, the status + intent eHMI increases user experience, perceived intelligence, and transparency for pedestrians more than the mere status eHMI. Participants reported that additionally informing about the vehicle’s intent adds a further sense of safety. The present study failed to show any improvements in traffic flow but found evidence for individual crossing and clearing strategies among pedestrians. This work can inform the future design of eHMIs.     

Construct validation of the Self-Control Schedule

The present paper describes an investigation of the construct validity of the English version of M. Rosenbaum's (1980, Behavior Therapy, 11, 109–121) Self-Control Schedule (SCS). A total of 121 Brigham Young University students took the SCS and several other measures. t tests were conducted between the Brigham Young University student SCS means and the SCS means of samples from two midwestern universities. Pearson correlations between the SCS, the SCS subscales, Rotter's I-E scale, the Manifest Anxiety scale, and the Religious Orientation scale were computed. Reliability analyses were conducted on the SCS subscales. The results (a) provide additional normative data about the SCS, (b) further establish the comparability of the Hebrew and English versions of the SCS, (c) expand the nomological network and support the construct validity of the SCS, and (d) indicate that the SCS may have potential as a multidimensional instrument.