Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.10.018
Cristian Domarchi , Quoc C. Vuong , Elisabetta Cherchi
Cognitive consistency theories offer a solid background to understand the effects of latent psychological constructs in decision-making. These theories model decision-making as the product of a dynamic and recursive process in which individual elements are evaluated toward a decision and this emerging decision returns to its individual elements. In this study, we use the Hot Coherence (HOTCO) cognitive consistency theory to analyse the choice between electric, hybrid-electric, and petrol vehicles. We apply the model to a sample of respondents from England households with one or more cars. The HOTCO model offers a more nuanced representation of the decision-making process – compared with traditional attitude-behaviour link theories – by incorporating non-linear and multidimensional interactions between its components. Our results suggest that positive attitudes and emotional appraisals for electric and hybrid-electric vehicles are shaped by similar motivators, and respondents perceive them as capable of satisfying the same set of needs. In addition, environmental awareness and pro-innovative orientation are the two motives that generate the greater differences in attitudinal evaluations of petrol vehicles, compared with alternative fuels.
{"title":"The role of emotional coherence in electric vehicle purchasing decisions","authors":"Cristian Domarchi , Quoc C. Vuong , Elisabetta Cherchi","doi":"10.1016/j.trf.2024.10.018","DOIUrl":"10.1016/j.trf.2024.10.018","url":null,"abstract":"<div><div>Cognitive consistency theories offer a solid background to understand the effects of latent psychological constructs in decision-making. These theories model decision-making as the product of a dynamic and recursive process in which individual elements are evaluated toward a decision and this emerging decision returns to its individual elements. In this study, we use the Hot Coherence (HOTCO) cognitive consistency theory to analyse the choice between electric, hybrid-electric, and petrol vehicles. We apply the model to a sample of respondents from England households with one or more cars. The HOTCO model offers a more nuanced representation of the decision-making process – compared with traditional attitude-behaviour link theories – by incorporating non-linear and multidimensional interactions between its components. Our results suggest that positive attitudes and emotional appraisals for electric and hybrid-electric vehicles are shaped by similar motivators, and respondents perceive them as capable of satisfying the same set of needs. In addition, environmental awareness and pro-innovative orientation are the two motives that generate the greater differences in attitudinal evaluations of petrol vehicles, compared with alternative fuels.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 997-1014"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.10.022
Merle Lau, Marc Wilbrink, Michael Oehl
Highly automated vehicles (HAVs) will soon be introduced into mixed urban traffic. Pedestrians might have an idea of HAVs. Nevertheless, they probably have never interacted with them before. Moreover, pedestrians will not be able to communicate with HAVs like they are used to with manual vehicles. External human–machine interfaces (eHMIs) are possible design solutions for HAVs to ensure safe interaction with other road users. Light-based eHMIs positively affected pedestrians’ trust ratings, perceived safety, and willingness to cross. However, previous studies often neglected the effect of vehicle size, although larger-sized HAVs could be potentially perceived as the more significant threat. Additionally, the relationship between vehicle kinematics and eHMIs for differently sized HAVs remains an underexplored research topic. This study investigated the effects of vehicle size (small vs. large), eHMI state (dynamic eHMI vs. static eHMI vs. no eHMI), and vehicle kinematics (yielding vs. non-yielding) on pedestrian crossing behavior and their subjective assessment. In virtual reality, we created a shared space traffic scenario, in which the eHMI and vehicle kinematics matched or did not match. For yielding conditions, the results showed that participants felt more aroused with larger HAVs than with smaller HAVs. Moreover, pedestrians initiated their crossing significantly earlier when both vehicle sizes had a dynamic eHMI compared to a static eHMI vs. no eHMI. Additionally, pedestrians evaluated a dynamic eHMI with higher trust ratings, higher perceived safety, and more positive affective reactions. The results manifested that the use of dynamic eHMIs can effectively enhance pedestrian-vehicle communication with a large and a small HAV. For non-matching conditions, the participants tended to rely on the vehicle kinematics for both vehicle sizes. Overall, the study highlighted the potential of eHMIs for pedestrian interactions with HAVs of varying sizes when they are well-coordinated with the vehicle kinematics, aiming to enhance safety and efficiency in mixed-traffic environments.
{"title":"Matching vs. Mismatching Signals of External Human-Machine Interface and Vehicle Kinematics: An Examination of Pedestrian Crossing Behavior and Trust, Safety, and Affective Ratings in Interactions with Differently Sized Automated Vehicles","authors":"Merle Lau, Marc Wilbrink, Michael Oehl","doi":"10.1016/j.trf.2024.10.022","DOIUrl":"10.1016/j.trf.2024.10.022","url":null,"abstract":"<div><div>Highly automated vehicles (HAVs) will soon be introduced into mixed urban traffic. Pedestrians might have an idea of HAVs. Nevertheless, they probably have never interacted with them before. Moreover, pedestrians will not be able to communicate with HAVs like they are used to with manual vehicles. External human–machine interfaces (eHMIs) are possible design solutions for HAVs to ensure safe interaction with other road users. Light-based eHMIs positively affected pedestrians’ trust ratings, perceived safety, and willingness to cross. However, previous studies often neglected the effect of vehicle size, although larger-sized HAVs could be potentially perceived as the more significant threat. Additionally, the relationship between vehicle kinematics and eHMIs for differently sized HAVs remains an underexplored research topic. This study investigated the effects of vehicle size (small vs. large), eHMI state (dynamic eHMI vs. static eHMI vs. no eHMI), and vehicle kinematics (yielding vs. non-yielding) on pedestrian crossing behavior and their subjective assessment. In virtual reality, we created a shared space traffic scenario, in which the eHMI and vehicle kinematics matched or did not match. For yielding conditions, the results showed that participants felt more aroused with larger HAVs than with smaller HAVs. Moreover, pedestrians initiated their crossing significantly earlier when both vehicle sizes had a dynamic eHMI compared to a static eHMI vs. no eHMI. Additionally, pedestrians evaluated a dynamic eHMI with higher trust ratings, higher perceived safety, and more positive affective reactions. The results manifested that the use of dynamic eHMIs can effectively enhance pedestrian-vehicle communication with a large and a small HAV. For non-matching conditions, the participants tended to rely on the vehicle kinematics for both vehicle sizes. Overall, the study highlighted the potential of eHMIs for pedestrian interactions with HAVs of varying sizes when they are well-coordinated with the vehicle kinematics, aiming to enhance safety and efficiency in mixed-traffic environments.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1092-1104"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.10.025
Ole Aasvik , Pål Ulleberg , Marjan Hagenzieker
The primary aim of this study was to develop an accurate measure of acceptance for shared autonomous vehicles (SAVs) and to assess whether this measure can predict intentions to use SAVs. One leading model for explaining technology uptake is the UTAUT (Unified theory of acceptance and use of technology). This model is extensive and has received numerous suggested extensions and revisions, even being developed into a Multi-Level Model of Autonomous Vehicle Acceptance (MAVA). The challenge is to consolidate a model that effectively measures SAV acceptance and to determine which extensions capture the unique social situation within SAVs.
The current study used survey data from 1902 respondents. The sample was split into two: one half underwent a principal component analysis (PCA) and the other half a confirmatory factor analysis (CFA). We found that the 24 items we included were reducible to a single general acceptance factor (GAF), with three additional factors measuring interpersonal security, sociability, and attractivity. The GAF was, by a large margin, the most efficacious predictor of intention to use SAVs. The GAF could be further reduced to as little as two predictors, trust and usefulness, accounting for over 70 % of the variance in intention to use. However, there is also an argument to be made that the other components of SAV acceptance may capture different nuances of the service, particularly relating to the social situation. Interaction terms show differences between genders in their rating of sociability and how this impacts intentions to use SAVs.
Our findings carry significant implications for future research in this field. They underscore the pivotal roles of trust and usefulness while corroborating the notion that SAV acceptance is best represented by a single latent component. However, further investigation is warranted to explore individual-level moderating effects on the other components, potentially offering novel insights for the design of future SAV services.
本研究的主要目的是开发一种准确的共享自动驾驶汽车（SAV）接受度测量方法，并评估该测量方法能否预测使用 SAV 的意向。解释技术吸收的一个主要模型是UTAUT（技术接受和使用统一理论）。该模型内容广泛，并得到了许多扩展和修订建议，甚至被发展成为自主车辆接受的多层次模型（MAVA）。目前的挑战是整合一个能有效衡量 SAV 接受度的模型，并确定哪些扩展模型能捕捉到 SAV 独特的社会状况。样本被一分为二：一半进行主成分分析（PCA），另一半进行确证因子分析（CFA）。我们发现，我们所包含的 24 个项目可还原为一个单一的总体接受因子（GAF），另外还有三个衡量人际安全感、交际能力和吸引力的因子。GAF 是最有效的预测 SAV 使用意向的因素。GAF 可以进一步缩减到只有两个预测因子，即信任度和有用性，占使用意向差异的 70% 以上。不过，也有一种观点认为，SAV 接受度的其他组成部分可能捕捉到了服务的不同细微差别，尤其是与社会环境有关的细微差别。我们的研究结果对该领域未来的研究具有重要意义。我们的研究结果对这一领域的未来研究具有重要意义。研究结果强调了信任和有用性的关键作用，同时证实了SAV接受度最好由一个潜在成分来代表的观点。然而，我们还需要进一步研究个人层面对其他因素的调节作用，从而为未来SAV服务的设计提供新的见解。
{"title":"Simplifying acceptance: A general acceptance factor predicting intentions to use shared autonomous vehicles","authors":"Ole Aasvik , Pål Ulleberg , Marjan Hagenzieker","doi":"10.1016/j.trf.2024.10.025","DOIUrl":"10.1016/j.trf.2024.10.025","url":null,"abstract":"<div><div>The primary aim of this study was to develop an accurate measure of acceptance for shared autonomous vehicles (SAVs) and to assess whether this measure can predict intentions to use SAVs. One leading model for explaining technology uptake is the UTAUT (Unified theory of acceptance and use of technology). This model is extensive and has received numerous suggested extensions and revisions, even being developed into a Multi-Level Model of Autonomous Vehicle Acceptance (MAVA). The challenge is to consolidate a model that effectively measures SAV acceptance and to determine which extensions capture the unique social situation within SAVs.</div><div>The current study used survey data from 1902 respondents. The sample was split into two: one half underwent a principal component analysis (PCA) and the other half a confirmatory factor analysis (CFA). We found that the 24 items we included were reducible to a single general acceptance factor (GAF), with three additional factors measuring interpersonal security, sociability, and attractivity. The GAF was, by a large margin, the most efficacious predictor of intention to use SAVs. The GAF could be further reduced to as little as two predictors, trust and usefulness, accounting for over 70 % of the variance in intention to use. However, there is also an argument to be made that the other components of SAV acceptance may capture different nuances of the service, particularly relating to the social situation. Interaction terms show differences between genders in their rating of sociability and how this impacts intentions to use SAVs.</div><div>Our findings carry significant implications for future research in this field. They underscore the pivotal roles of trust and usefulness while corroborating the notion that SAV acceptance is best represented by a single latent component. However, further investigation is warranted to explore individual-level moderating effects on the other components, potentially offering novel insights for the design of future SAV services.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1125-1143"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.11.006
Rémy Le Boennec , Stéphane Roger , Stéphanie Cœugnet
This study aims to test the sensitivity of five personality tendencies to levers of carpooling to work. We launched a large-scale online questionnaire targeting daily car drivers in France (N = 1,134 respondents) to test the link between levers to engage in carpooling (environmental awareness, confidence in others, relationship to time, economic gain and easy access to carpooling) and five personality tendencies of car drivers’ (feeling of ecological responsibility/ FER, social affinity as a measure of level of extraversion/ SA, saving time tendency to individual with a time-pressure sensitivity/ ST, sensitivity to reward/ SR, and technophilia/ TECH). Respondents were questioned about their home-to-work carpooling habits and motives, their preferences according to some carpooling options, their assessments of a new carpooling to work concept and their projected use of it. The results show a strong link between the five chosen personality tendencies and carpooling practice, perception and overall acceptance, except for the sensitivity to reward (SR). Economic gain is a strong lever for the entire population, and this must be maintained for all and rendered more visible. Our results also reveal that a carpooling to work service, adaptable to all the driver’s requests at each step of carpooling would meet the various needs of the different personality tendencies. In addition, a carpooling application must allow adaptability to specific personality tendencies (FER, ST, SA as a minimum) regarding the choices to be made at each stage of carpooling, while ensuring user-friendliness to facilitate access to those who are least comfortable with new technologies.
本研究旨在测试五种人格倾向对拼车上班杠杆的敏感性。我们针对法国的日常汽车驾驶员（1,134 名受访者）进行了大规模在线问卷调查，以检验参与拼车的杠杆（环境意识、对他人的信任、与时间的关系、经济收益和拼车的便利性）与汽车驾驶员的五种人格倾向（生态责任感/ FER、作为外向程度衡量标准的社会亲和力/ SA、对时间压力敏感的个人的节约时间倾向/ ST、对奖励的敏感性/ SR 和技术癖/ TECH）之间的联系。受访者被问及他们从家到单位的拼车习惯和动机、他们对一些拼车选择的偏好、他们对新的拼车上班概念的评估以及他们对这一概念的预计使用情况。结果表明，除了对奖励的敏感性（SR）之外，所选的五种个性倾向与拼车做法、看法和总体接受度之间存在密切联系。经济收益对所有人来说都是一个强有力的杠杆，必须对所有人都保持这一杠杆作用，并使其更加明显。我们的研究结果还表明，拼车上班服务如果能在拼车的每个步骤中适应所有司机的要求，就能满足不同性格倾向的各种需求。此外，拼车应用程序必须能够适应拼车每个阶段所做选择的特定个性倾向（至少是 FER、ST、SA），同时确保用户友好性，以方便那些最不适应新技术的人使用。
{"title":"The impact of personality on the propensity of carpooling to work","authors":"Rémy Le Boennec , Stéphane Roger , Stéphanie Cœugnet","doi":"10.1016/j.trf.2024.11.006","DOIUrl":"10.1016/j.trf.2024.11.006","url":null,"abstract":"<div><div>This study aims to test the sensitivity of five personality tendencies to levers of carpooling to work. We launched a large-scale online questionnaire targeting daily car drivers in France (N = 1,134 respondents) to test the link between levers to engage in carpooling (environmental awareness, confidence in others, relationship to time, economic gain and easy access to carpooling) and five personality tendencies of car drivers’ (feeling of ecological responsibility/ FER, social affinity as a measure of level of extraversion/ SA, saving time tendency to individual with a time-pressure sensitivity/ ST, sensitivity to reward/ SR, and technophilia/ TECH). Respondents were questioned about their home-to-work carpooling habits and motives, their preferences according to some carpooling options, their assessments of a new carpooling to work concept and their projected use of it. The results show a strong link between the five chosen personality tendencies and carpooling practice, perception and overall acceptance, except for the sensitivity to reward (SR). Economic gain is a strong lever for the entire population, and this must be maintained for all and rendered more visible. Our results also reveal that a carpooling to work service, adaptable to all the driver’s requests at each step of carpooling would meet the various needs of the different personality tendencies. In addition, a carpooling application must allow adaptability to specific personality tendencies (FER, ST, SA as a minimum) regarding the choices to be made at each stage of carpooling, while ensuring user-friendliness to facilitate access to those who are least comfortable with new technologies.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1144-1161"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.10.023
Senkai Xie, Feixiong Liao
Electric micromobility-sharing services (EMS) have emerged as a promising mobility tool for tackling transportation problems. Understanding the drivers of user acceptance of EMS is essential for proper deployment. However, there is no consensus in the literature on the effects of psychological factors on EMS adoption, and little research has considered personality traits to capture individual differences. To fill this research gap, we administered a survey through a Dutch panel that integrated the Big Five personality traits into a user acceptance framework and applied structural equation modeling (SEM) to investigate user acceptance of EMS. The quantitative analysis reveals that three UTAUT factors (social influence, performance expectancy, and hedonic motivation) have strong positive direct effects on user acceptance. Among the Big Five personality traits, openness and extraversion have significant but weaker total effects, while other personality traits (conscientiousness, agreeableness, and neuroticism) have no significant effects. It is also found that young people and residents of large cities have a higher intention to adopt EMS, while the majority who are highly satisfied with the status quo transportation modes have a lower intention to use EMS for short trips. The analysis results offer crucial insights into crafting tailored strategies to deploy EMS.
{"title":"Incorporating personality traits for the study of user acceptance of electric micromobility-sharing services","authors":"Senkai Xie, Feixiong Liao","doi":"10.1016/j.trf.2024.10.023","DOIUrl":"10.1016/j.trf.2024.10.023","url":null,"abstract":"<div><div>Electric micromobility-sharing services (EMS) have emerged as a promising mobility tool for tackling transportation problems. Understanding the drivers of user acceptance of EMS is essential for proper deployment. However, there is no consensus in the literature on the effects of psychological factors on EMS adoption, and little research has considered personality traits to capture individual differences. To fill this research gap, we administered a survey through a Dutch panel that integrated the Big Five personality traits into a user acceptance framework and applied structural equation modeling (SEM) to investigate user acceptance of EMS. The quantitative analysis reveals that three UTAUT factors (social influence, performance expectancy, and hedonic motivation) have strong positive direct effects on user acceptance. Among the Big Five personality traits, openness and extraversion have significant but weaker total effects, while other personality traits (conscientiousness, agreeableness, and neuroticism) have no significant effects. It is also found that young people and residents of large cities have a higher intention to adopt EMS, while the majority who are highly satisfied with the status quo transportation modes have a lower intention to use EMS for short trips. The analysis results offer crucial insights into crafting tailored strategies to deploy EMS.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1015-1030"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.10.020
Christian Bretter , Hemant Sharma , Kate Pangbourne
Examinations into the psychological drivers of car-sharing have to date focused on short-term cognitions such as attitudes, norms, and intentions. In this paper, we integrate such short-term cognitions with medium-term cognitions (e.g., goals) and long-term cognitions (e.g., values), thereby providing a more comprehensive understanding of the psychological drivers of car-sharing. We surveyed a broadly representative sample of the UK population (N = 1,294) and found that values underlie medium-term cognitions (e.g., goals) and short-term cognitions, thereby ultimately influencing car-sharing intentions and behaviour. Moreover, our results show that environmental consciousness and the desire for luxury are important yet opposing goals that affect both intentions to engage in car-sharing and to actually use car-sharing. Overall, we demonstrate that car-sharing may be more complex than previously anticipated and should be understood as a behaviour that results from a complex web of long-, medium-, and short-term cognitions. We discuss practical and theoretical implications.
{"title":"Understanding car-sharing by integrating long-, medium- and short-term cognitions","authors":"Christian Bretter , Hemant Sharma , Kate Pangbourne","doi":"10.1016/j.trf.2024.10.020","DOIUrl":"10.1016/j.trf.2024.10.020","url":null,"abstract":"<div><div>Examinations into the psychological drivers of car-sharing have to date focused on short-term cognitions such as attitudes, norms, and intentions. In this paper, we integrate such short-term cognitions with medium-term cognitions (e.g., goals) and long-term cognitions (e.g., values), thereby providing a more comprehensive understanding of the psychological drivers of car-sharing. We surveyed a broadly representative sample of the UK population (N = 1,294) and found that values underlie medium-term cognitions (e.g., goals) and short-term cognitions, thereby ultimately influencing car-sharing intentions and behaviour. Moreover, our results show that environmental consciousness and the desire for luxury are important yet opposing goals that affect both intentions to engage in car-sharing and to actually use car-sharing. Overall, we demonstrate that car-sharing may be more complex than previously anticipated and should be understood as a behaviour that results from a complex web of long-, medium-, and short-term cognitions. We discuss practical and theoretical implications.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 985-996"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.09.021
Sina Nordhoff , Marjan Hagenzieker
Introduction: Partially automated cars are on the road. Trust in automation and perceived safety are critical factors determining use of automation. Background: Drivers misuse partially automated driving systems. Misuse is associated with mis-calibrated trust in the automation. Research gap: Little is known about the factors impacting the perceived safety when using partial driving automation. Research objective: The main objective of the present study is to provide a comprehensive driver perspective on the psychological aspects of automation use pertaining to trust in automation, perceived safety, and its relationship with use of automation. Method: Semi-structured interviews (n = 103) were conducted with users of partially automated driving systems. Supplemented with content analysis, natural language processing (NLP) techniques were applied to perform automatic text processing. Guided seed-term analysis was conducted to identify the number of occurrences of the subcategories in the dataset. Main results: We identified human operator-related, automation-related, and environmental factors of trust and perceived safety. The identified factors were more strongly associated with perceived safety than with trust. Participants with physical and visual impairments reported to feel safer using the automation compared to driving manually. Neurotic behavior during manual driving contributed to lower trust and perceived safety using the automation. A correct mental model of the capabilities and limitations of the automation did not guarantee proper automation use. A novel conceptual, process-oriented model, titled PTS-a (predicting trust in and perceived safety of automation use), synthesizes the results of the data analysis. Informed by the cognition-leads-to-emotions approach, the model posits that trust as cognition precedes perceived safety as affective construct. Trust and perceived safety determine how human operators (mis-, dis-)use the automation. Future research: We recommend future research to perform experimental studies to identify cognitive-related thoughts and beliefs pertaining to trust in automation and perceived safety to contribute to the operationalization of these constructs, and unravel the nature of their relationship.
{"title":"“I will raise my hand and say ‘I over-trust Autopilot’. I use it too liberally” – Drivers’ reflections on their use of partial driving automation, trust, and perceived safety","authors":"Sina Nordhoff , Marjan Hagenzieker","doi":"10.1016/j.trf.2024.09.021","DOIUrl":"10.1016/j.trf.2024.09.021","url":null,"abstract":"<div><div><strong>Introduction:</strong> Partially automated cars are on the road. Trust in automation and perceived safety are critical factors determining use of automation. <strong>Background:</strong> Drivers misuse partially automated driving systems. Misuse is associated with mis-calibrated trust in the automation. <strong>Research gap:</strong> Little is known about the factors impacting the perceived safety when using partial driving automation. <strong>Research objective:</strong> The main objective of the present study is to provide a comprehensive driver perspective on the psychological aspects of automation use pertaining to trust in automation, perceived safety, and its relationship with use of automation. <strong>Method:</strong> Semi-structured interviews (n = 103) were conducted with users of partially automated driving systems. Supplemented with content analysis, natural language processing (NLP) techniques were applied to perform automatic text processing. Guided seed-term analysis was conducted to identify the number of occurrences of the subcategories in the dataset. <strong>Main results:</strong> We identified human operator-related, automation-related, and environmental factors of trust and perceived safety. The identified factors were more strongly associated with perceived safety than with trust. Participants with physical and visual impairments reported to feel safer using the automation compared to driving manually. Neurotic behavior during manual driving contributed to lower trust and perceived safety using the automation. A correct mental model of the capabilities and limitations of the automation did not guarantee proper automation use. A novel conceptual, process-oriented model, titled PTS-a (predicting trust in and perceived safety of automation use), synthesizes the results of the data analysis. Informed by the cognition-leads-to-emotions approach, the model posits that trust as cognition precedes perceived safety as affective construct. Trust and perceived safety determine how human operators (mis-, dis-)use the automation. <strong>Future research:</strong> We recommend future research to perform experimental studies to identify cognitive-related thoughts and beliefs pertaining to trust in automation and perceived safety to contribute to the operationalization of these constructs, and unravel the nature of their relationship.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1105-1124"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.11.016
Lei Han , Zhigang Du , Xuejian Kang
The visual attractions present in the access zones of highway tunnels can exert a detrimental effect on drivers’ visual performance and mental workload, thereby posing a significant risk to driving safety. This study aims to evaluate the impact of these eye-catching elements on driving safety performance by comparing and analyzing the influence of various visual attraction conditions in tunnel access zones on both the objective visual performance and subjective mental workload assessments of novice and experienced drivers. Four distinct visual attraction scenarios were selected for implementation in the access zones of highway tunnels: baseline, landscape-inspired architecture, informational tip slogans, and commercial billboards. Naturalistic driving experiments were conducted, supplemented by subjective mental workload measurements, to analyze a range of factors, including drivers’ first fixation duration (FFD), mean fixation duration (MFD), distance from tunnel portal when first fixation occurs at visual attraction (DTP), number of fixations (NOF), pupil diameter (PD), and visual sample entropy (SampEn). Subjective mental workload was assessed using the NASA-TLX scale. The results revealed that visual attractions within tunnel access zones significantly affected drivers’ objective visual performance and subjective mental workload evaluations. Different visual attractions exerted varied effects on visual attention, stability, cognitive workload, and subjective mental workload. Specifically, billboards were found to rapidly capture drivers’ attention, leading to unstable visual performance. Informational tip slogans demanded greater attention and cognitive effort, resulting in increased cognitive workload. Furthermore, novice drivers demonstrated poorer visual performance, stability, and higher workload compared to their experienced counterparts. This research highlights the intricate relationship between visual attractions and their impact on drivers’ visual performance and mental workload, emphasizing the need for targeted interventions and enhancements in visual strategies particularly tailored for novice drivers. The findings contribute to the domain of transportation psychology and offer practical implications for improving the safety and efficiency of tunnel access zones through evidence-based design strategies. Ultimately, the insights gained from this study can guide the design of visual attractions in highway tunnel access zones to optimize drivers’ visual performance and mitigate mental workload.
{"title":"The impact of visual attractions on drivers’ visual performance and mental workload in highway tunnel access zones","authors":"Lei Han , Zhigang Du , Xuejian Kang","doi":"10.1016/j.trf.2024.11.016","DOIUrl":"10.1016/j.trf.2024.11.016","url":null,"abstract":"<div><div>The visual attractions present in the access zones of highway tunnels can exert a detrimental effect on drivers’ visual performance and mental workload, thereby posing a significant risk to driving safety. This study aims to evaluate the impact of these eye-catching elements on driving safety performance by comparing and analyzing the influence of various visual attraction conditions in tunnel access zones on both the objective visual performance and subjective mental workload assessments of novice and experienced drivers. Four distinct visual attraction scenarios were selected for implementation in the access zones of highway tunnels: baseline, landscape-inspired architecture, informational tip slogans, and commercial billboards. Naturalistic driving experiments were conducted, supplemented by subjective mental workload measurements, to analyze a range of factors, including drivers’ first fixation duration (FFD), mean fixation duration (MFD), distance from tunnel portal when first fixation occurs at visual attraction (DTP), number of fixations (NOF), pupil diameter (PD), and visual sample entropy (SampEn). Subjective mental workload was assessed using the NASA-TLX scale. The results revealed that visual attractions within tunnel access zones significantly affected drivers’ objective visual performance and subjective mental workload evaluations. Different visual attractions exerted varied effects on visual attention, stability, cognitive workload, and subjective mental workload. Specifically, billboards were found to rapidly capture drivers’ attention, leading to unstable visual performance. Informational tip slogans demanded greater attention and cognitive effort, resulting in increased cognitive workload. Furthermore, novice drivers demonstrated poorer visual performance, stability, and higher workload compared to their experienced counterparts. This research highlights the intricate relationship between visual attractions and their impact on drivers’ visual performance and mental workload, emphasizing the need for targeted interventions and enhancements in visual strategies particularly tailored for novice drivers. The findings contribute to the domain of transportation psychology and offer practical implications for improving the safety and efficiency of tunnel access zones through evidence-based design strategies. Ultimately, the insights gained from this study can guide the design of visual attractions in highway tunnel access zones to optimize drivers’ visual performance and mitigate mental workload.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1232-1256"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.11.002
Mengjiao Wu , Xuesong Wang , Jiawen Chen , Xiang Ji , Yiran Sun
Distracted driving is one of the most important causes of traffic crashes, leading 162 countries to establish regulations to control distracted driving, mainly by prohibiting or limiting the use of mobile phones. At present, there is no standard for regulating cellphones or other distractions. Understanding the specific risk characteristics of common distracted driving behaviors is crucial for regulatory development. However, research has been limited in comparing the risk characteristics of common distractions. Hence, this study aims to analyze and compare the risk characteristics of several auditory-cognitive and visual-manual distractions, as well as factors specific to individual drivers. Two crash surrogate indicators, lateral position and acceleration, were categorized into three risk levels. The partial proportional odds model was used to analyze lane keeping events, and the mixed-effects logit model was used for speed control events. Model results showed that, compared with the no-distraction baseline, visual-manual distraction tasks undermined both driver lane control and speed control, while auditory-cognitive distraction had little effect on lane keeping; auditory-cognitive distractions showed less risk of max deceleration than visual-manual distractions, but showed more risk of max acceleration. Additionally, it was found that older and female drivers have a higher risk of max acceleration when distracted, and older drivers have a higher risk of lane departure when distracted. These results provide data support for the development of distracted driving regulations.
{"title":"Analysis and comparison of auditory-cognitive and visual-manual distraction risk characteristics and their effect on driving","authors":"Mengjiao Wu , Xuesong Wang , Jiawen Chen , Xiang Ji , Yiran Sun","doi":"10.1016/j.trf.2024.11.002","DOIUrl":"10.1016/j.trf.2024.11.002","url":null,"abstract":"<div><div>Distracted driving is one of the most important causes of traffic crashes, leading 162 countries to establish regulations to control distracted driving, mainly by prohibiting or limiting the use of mobile phones. At present, there is no standard for regulating cellphones or other distractions. Understanding the specific risk characteristics of common distracted driving behaviors is crucial for regulatory development. However, research has been limited in comparing the risk characteristics of common distractions. Hence, this study aims to analyze and compare the risk characteristics of several auditory-cognitive and visual-manual distractions, as well as factors specific to individual drivers. Two crash surrogate indicators, lateral position and acceleration, were categorized into three risk levels. The partial proportional odds model was used to analyze lane keeping events, and the mixed-effects logit model was used for speed control events. Model results showed that, compared with the no-distraction baseline, visual-manual distraction tasks undermined both driver lane control and speed control, while auditory-cognitive distraction had little effect on lane keeping; auditory-cognitive distractions showed less risk of max deceleration than visual-manual distractions, but showed more risk of max acceleration. Additionally, it was found that older and female drivers have a higher risk of max acceleration when distracted, and older drivers have a higher risk of lane departure when distracted. These results provide data support for the development of distracted driving regulations.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1042-1061"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.trf.2024.11.010
Steven Love , Petra Unger , Bevan Rowland , Kerry Armstrong
Research has suggested that problematic cannabis use is associated with self-regulatory impairments, psychopathology, and the tendency to engage in risk taking behaviours. However, no research has applied the combined dynamics of these factors to the topic of risky driving behaviour specifically. This study investigated whether specific cannabis use patterns (i.e., use onset, duration, frequency, and quantity) and likely dependence influenced driving styles, via their effects towards emotional dysregulation and psychopathology (i.e., anxiety, depression, anger), among an online sample of active Australian cannabis users (N = 200). Group comparisons showed that likely dependent cannabis users reported significantly greater difficulties regulating their emotions, greater incidence of psychopathological symptoms (i.e., anxiety, depression, and anger), and more frequent engagement in risky driving styles (i.e., anxious driving, aggressive driving, dissociative driving, and reckless driving), compared to non-dependent cannabis users. Examination of bivariate correlations demonstrated significant and positive associations between specific cannabis use patterns, emotional regulation difficulties, psychopathology, and risky driving styles. Structural equation modelling highlighted that cannabis use patterns indirectly predicted participants self-reported engagement in risky driving styles via their effects towards self-regulatory difficulties and psychopathology. The findings of this study have highlighted driving related risks associated with cannabis use, outside of typical acute-related impairments. In addition, the study has emphasised the importance of psychological dysfunctioning in the engagement of both substance use and risky driving styles. Understanding this in combination is important for future interventions targeting aberrant driving behaviours.
{"title":"Is cannabis associated with more than just driving impairment? An investigation into the psychological dysfunctioning and driving behaviours of active cannabis users","authors":"Steven Love , Petra Unger , Bevan Rowland , Kerry Armstrong","doi":"10.1016/j.trf.2024.11.010","DOIUrl":"10.1016/j.trf.2024.11.010","url":null,"abstract":"<div><div>Research has suggested that problematic cannabis use is associated with self-regulatory impairments, psychopathology, and the tendency to engage in risk taking behaviours. However, no research has applied the combined dynamics of these factors to the topic of risky driving behaviour specifically. This study investigated whether specific cannabis use patterns (i.e., use onset, duration, frequency, and quantity) and likely dependence influenced driving styles, via their effects towards emotional dysregulation and psychopathology (i.e., anxiety, depression, anger), among an online sample of active Australian cannabis users (<em>N</em> = 200). Group comparisons showed that likely dependent cannabis users reported significantly greater difficulties regulating their emotions, greater incidence of psychopathological symptoms (i.e., anxiety, depression, and anger), and more frequent engagement in risky driving styles (i.e., anxious driving, aggressive driving, dissociative driving, and reckless driving), compared to non-dependent cannabis users. Examination of bivariate correlations demonstrated significant and positive associations between specific cannabis use patterns, emotional regulation difficulties, psychopathology, and risky driving styles. Structural equation modelling highlighted that cannabis use patterns indirectly predicted participants self-reported engagement in risky driving styles via their effects towards self-regulatory difficulties and psychopathology. The findings of this study have highlighted driving related risks associated with cannabis use, outside of typical acute-related impairments. In addition, the study has emphasised the importance of psychological dysfunctioning in the engagement of both substance use and risky driving styles. Understanding this in combination is important for future interventions targeting aberrant driving behaviours.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 1162-1174"},"PeriodicalIF":3.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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