•We explored the opinion of 5000 people across the globe on automated driving.•69% of respondents stated that fully automated driving will reach a 50% market share before 2050.•Respondents were ...concerned about software hacking/misuse, legal issues, and safety.•The more developed countries were less comfortable with vehicle data transmission.
This study investigated user acceptance, concerns, and willingness to buy partially, highly, and fully automated vehicles. By means of a 63-question Internet-based survey, we collected 5000 responses from 109 countries (40 countries with at least 25 respondents). We determined cross-national differences, and assessed correlations with personal variables, such as age, gender, and personality traits as measured with a short version of the Big Five Inventory. Results showed that respondents, on average, found manual driving the most enjoyable mode of driving. Responses were diverse: 22% of the respondents did not want to pay more than $0 for a fully automated driving system, whereas 5% indicated they would be willing to pay more than $30,000, and 33% indicated that fully automated driving would be highly enjoyable. 69% of respondents estimated that fully automated driving will reach a 50% market share between now and 2050. Respondents were found to be most concerned about software hacking/misuse, and were also concerned about legal issues and safety. Respondents scoring higher on neuroticism were slightly less comfortable about data transmitting, whereas respondents scoring higher on agreeableness were slightly more comfortable with this. Respondents from more developed countries (in terms of lower accident statistics, higher education, and higher income) were less comfortable with their vehicle transmitting data, with cross-national correlations between ρ=−0.80 and ρ=−0.90. The present results indicate the major areas of promise and concern among the international public, and could be useful for vehicle developers and other stakeholders.
mmod is a library for the R programming language that allows the calculation of the population differentiation measures Dest, G″ST and φ′ST. R provides a powerful environment in which to conduct and ...record population genetic analyses but, at present, no R libraries provide functions for the calculation of these statistics from standard population genetic files. In addition to the calculation of differentiation measures, mmod can produce parametric bootstrap and jackknife samples of data sets for further analysis. By integrating with and complimenting the existing libraries adegenet and pegas, mmod extends the power of R as a population genetic platform.
This is a masterful volume on remembrance and war in the twentieth century. Jay Winter locates the fascination with the subject of memory within a long-term trajectory that focuses on the Great War. ...Images, languages, and practices that appeared during and after the two world wars focused on the need to acknowledge the victims of war and shaped the ways in which future conflicts were imagined and remembered. At the core of the memory boom is an array of collective meditations on war and the victims of war, Winter says.The book begins by tracing the origins of contemporary interest in memory, then describes practices of remembrance that have linked history and memory, particularly in the first half of the twentieth century. The author also considers theaters of memoryfilm, television, museums, and war crimes trials in which the past is seen through public representations of memories. The book concludes with reflections on the significance of these practices for the cultural history of the twentieth century as a whole.
A human factors perspective on automated driving Kyriakidis, M.; de Winter, J. C. F.; Stanton, N. ...
Theoretical issues in ergonomics science,
05/2019, Letnik:
20, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Automated driving can fundamentally change road transportation and improve quality of life. However, at present, the role of humans in automated vehicles (AVs) is not clearly established. Interviews ...were conducted in April and May 2015 with 12 expert researchers in the field of human factors (HFs) of automated driving to identify commonalities and distinctive perspectives regarding HF challenges in the development of AVs. The experts indicated that an AV up to SAE Level 4 should inform its driver about the AV's capabilities and operational status, and ensure safety while changing between automated and manual modes. HF research should particularly address interactions between AVs, human drivers and vulnerable road users. Additionally, driver-training programmes may have to be modified to ensure that humans are capable of using AVs. Finally, a reflection on the interviews is provided, showing discordance between the interviewees' statements - which appear to be in line with a long history of HFs research - and the rapid development of automation technology. We expect our perspective to be instrumental for stakeholders involved in AV development and instructive to other parties.
•Vibrotactile stimuli can effectively convey a take-over request in highly automated driving.•Participants could not reliably recognize directional cues presented via a vibrotactile seat.•Static ...vibrotactile patterns seemed to evoke faster reaction times than dynamic ones.
Vibrotactile stimuli can be effective as warning signals, but their effectiveness as directional take-over requests in automated driving is yet unknown. This study aimed to investigate the correct response rate, reaction times, and eye and head orientation for static versus dynamic directional take-over requests presented via vibrating motors in the driver seat. In a driving simulator, eighteen participants performed three sessions: 1) a session involving no driving (Baseline), 2) driving a highly automated car without additional task (HAD), and 3) driving a highly automated car while performing a mentally demanding task (N-Back). Per session, participants received four directional static (in the left or right part of the seat) and four dynamic (moving from one side towards the opposite left or right of the seat) take-over requests via two 6×4 motor matrices embedded in the seat back and bottom. In the Baseline condition, participants reported whether the cue was left or right, and in the HAD and N-Back conditions participants had to change lanes to the left or to the right according to the directional cue. The correct response rate was operationalized as the accuracy of the self-reported direction (Baseline session) and the accuracy of the lane change direction (HAD & N-Back sessions). The results showed that the correct response rate ranged between 94% for static patterns in the Baseline session and 74% for dynamic patterns in the N-Back session, although these effects were not statistically significant. Steering wheel touch and steering input reaction times were approximately 200ms faster for static patterns than for dynamic ones. Eye tracking results revealed a correspondence between head/eye-gaze direction and lane change direction, and showed that head and eye-gaze movements where initiated faster for static vibrations than for dynamic ones. In conclusion, vibrotactile stimuli presented via the driver seat are effective as warnings, but their effectiveness as directional take-over requests may be limited. The present study may encourage further investigation into how to get drivers safely back into the loop.
•This meta-analysis compares social desirability between paper and computer surveys.•Social desirability in computer (Internet/offline) and paper surveys is the same.•Some of the large effects found ...in the past may have been due to sampling error.
The aim of this meta-analysis was to compare social desirability scores between paper and computer surveys. Subgroup analyses were conducted with Internet connectivity, level of anonymity, individual or group test setting, possibility of skipping items, possibility of backtracking previous items, inclusion of questions of sensitive nature, and social desirability scale type as moderators. Subgroup analyses were also conducted for study characteristics, namely the randomisation of participants, sample type (students vs. other), and study design (between- vs. within-subjects). Social desirability scores between the two administration modes were compared for 51 studies that included 62 independent samples and 16,700 unique participants. The overall effect of administration mode was close to zero (Cohen’s d=0.00 for fixed-effect and d=−0.01 for random-effects meta-analysis). The majority of the effect sizes in the subgroup analyses were not significantly different from zero either. The effect sizes were close to zero for both Internet and offline surveys. In conclusion, the totality of evidence indicates that there is no difference in social desirability between paper-and-pencil surveys and computer surveys. Publication year and sample size were positively correlated (ρ=.64), which suggests that certain of the large effects that have been found in the past may have been due to sampling error.
An analysis of article-level metrics of 27,856 PLOS ONE articles reveals that the number of tweets was weakly associated with the number of citations (
β
= 0.10), and weakly negatively associated ...with citations when the number of article views was held constant (
β
= −0.06). The number of tweets was predictive of other social media activity (
β
= 0.34 for Mendeley and
β
= 0.41 for Facebook), but not of the number of article views on PubMed Central (
β
= 0.01). It is concluded that the scientific citation process acts relatively independently of the social dynamics on Twitter.
Principal axis factoring (PAF) and maximum likelihood factor analysis (MLFA) are two of the most popular estimation methods in exploratory factor analysis. It is known that PAF is better able to ...recover weak factors and that the maximum likelihood estimator is asymptotically efficient. However, there is almost no evidence regarding which method should be preferred for different types of factor patterns and sample sizes. Simulations were conducted to investigate factor recovery by PAF and MLFA for distortions of ideal simple structure and sample sizes between 25 and 5000. Results showed that PAF is preferred for population solutions with few indicators per factor and for overextraction. MLFA outperformed PAF in cases of unequal loadings within factors and for underextraction. It was further shown that PAF and MLFA do not always converge with increasing sample size. The simulation findings were confirmed by an empirical study as well as by a classic plasmode, Thurstone's box problem. The present results are of practical value for factor analysts.
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