Article

An empirical investigation on consumers’ intentions towards autonomous driving

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Abstract

Major steps towards implementation of autonomous and connected transport are being taken nowadays. The trend of automation technology being used in vehicles by the most important vehicle manufacturing industries is expected to move closer to high or fully Autonomous Vehicles (AVs) through technological advancements in sectors of robotics and artificial intelligence. Vehicles with autonomous driving capabilities are planning to be available on market, in full scale, in the next years. In the longer term substantial benefits are mainly expected for accessibility to transport, safety, traffic flow, emissions, fuel use and comfort. All these potential societal benefits will not be achieved unless AVs are accepted and used by a critical mass of people. Addressing these challenges, this paper: (a) proposes a technology acceptance modelling process by extending the original Technology Acceptance Model (TAM) to explain and predict consumers’ intensions towards AVs, (b) based on the proposed TAM-extended framework, a 30-question survey was conducted in order to investigate the factors influencing consumers’ intensions to use and accept AVs. Results show that the constructs of perceived usefulness, perceived ease to use, perceived trust and social influence, are all useful predictors of behavioral intentions to have or use AVs, with perceived usefulness having the strongest impact. The insights derived from this study could significantly contribute to ongoing research related to technology acceptance of AVs and are expected to allow automobile industries to improve their design and technology.

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... Thus, both Perceived Usefulness -Performance Expectancy and Perceived Ease of Use -Effort Expectancy are conceptually similar. The TAM received broad support also in the context of acceptance of autonomous vehicles (Buckley et al., 2018;Choi & Ji, 2015;Panagiotopoulos & Dimitrakopoulos, 2018;Xu et al., 2018), ADAS (Ghazizadeh et al., 2012), and navigation systems (Chen & Chen, 2011;Park & Kim, 2014). Equally, the UTAUT was investigated in different studies addressing automated vehicles (Kaye et al., 2020;Zmud et al., 2016), ADAS (Adell, 2010;Hewitt et al., 2019), and an in-car text input system (Osswald et al., 2012;Tr€ osterer et al., 2014). ...
... Thereby, it is not clear if acceptance is developed equally for different system types. For assistance systems or automated driving, for example, trust (Buckley et al., 2018;Ghazizadeh et al., 2012;Panagiotopoulos & Dimitrakopoulos, 2018;Xu et al., 2018), perceived risk, and sensation seeking (Choi & Ji, 2015) have been added to the TAM. The acceptance of navigation systems has been investigated in terms of more specific beliefs such as service and display quality, perceived locational accuracy, perceived system reliability, and satisfaction (Park et al., 2015) or navigation application affinity, a sense of direction, and distraction perceptions (Yang et al., 2021). ...
... Adj. R 2 Assistance significantly associated with usage intentions accounting for 50.6 À 50.9% of variance. This supports the findings of recent studies applying the TAM to driver assistance or autonomous driving (Buckley et al., 2018;Choi & Ji, 2015;Panagiotopoulos & Dimitrakopoulos, 2018;Xu et al., 2018) whereas only few studies examined the usage of in-vehicle information technology (e.g., Chen & Chen, 2011). ...
Article
More and more technical systems enter the vehicle impacting drivers’ experiences. In the human-centered design, an understanding of influencing factors for acceptance and usage is crucial to align in-vehicle technology with the user needs. Addressing the underlying psychological processes, this work modelled drivers’ usage intentions with motivational regulations (SDT), the TAM, and the UTAUT. An online study with 319 German drivers was conducted examining drivers’ positive or negative experiences with assistance and infotainment systems in the vehicle. In linear regressions, the TAM and UTAUT predicted the acceptance equally for assistance and navigation systems. Amotivation, identified regulation, and intrinsic regulation enhanced the prediction of usage intentions by 3.0–15.4% in addition to the UTAUT variables revealing the additional benefit of incorporating the motivational perspective into the modeling of in-vehicle technology acceptance. Future research and practitioners can build upon this theoretical basis and recommendations on improving motivation and well-being.
... A very recent study [4] used an extension of the original Technology Acceptance Model (TAM) to investigate in what extent consumers intend to use autonomous vehicles in the future. The results of the present analysis revealed that perceived usefulness, perceived ease of use, perceived trust and social influence had an impact on behavioral intentions to autonomous vehicles. ...
... Furthermore, drivers who anticipate a significant reduction in road crashes due to the introduction of autonomous vehicles are more likely to choose an autonomous vehicle over a traditional vehicle. This could be considered in line with Panagiotopoulos and Dimitrakopoulos [4] who stated that 44% of the respondents indicated that if they were to use Autonomous Vehicles they would be feeling safer. However, this variable was not significant for choosing a semi-autonomous vehicle and needs further investigation in future research. ...
... To be more specific, gender, marital status, occupation and education as well as past crash involvement appeared to have no effect on the choice of fully or semi-autonomous vehicles. Gender in particular is an interesting variable, because two similar past studies [4,30] have found opposite results. More specifically, Panagiotopoulos and Dimitrakopoulos [4] found that females were more likely to have and/or use autonomous vehicles (78%), when they become available on the market than males (59%), whereas in the study by Piao et al. [30], males (49%) were more likely buy an autonomous vehicle than females (39%). ...
Article
The advent of autonomous vehicles will soon transform transportation in a substantial way, but at the same time their public acceptance is questionable. Although there is much research carried out, studies analyzing choices of people regarding autonomous, semi-autonomous, and traditional vehicles are relatively scarce. Thus, the purpose of this paper is to add to current literature by surveying Greek drivers on their acceptance and willingness to obtain an autonomous vehicle, as well as their opinion on self-driving technology. Moreover, this study is one of the first attempts in Greece to utilize Stated Preference (SP) methods and Discrete Choice models for that purpose. In our approach, we included hypothetical scenarios of cost, time, and safety, which were distributed in a carefully developed questionnaire. By applying random parameters multinomial logistic and binary logistic models we explored drivers’ attitudes towards autonomous vehicles and accounted for unobserved heterogeneity. Results showed that the choice is associated with cost, time, level of safety, existence of driving support systems (GPS, parking assistant), attitudes towards autonomous public transport and taxis, driving experience, age and family income.
... This theoretical model highlights perceived usefulness and perceived ease of use as essential predictors of user acceptance of computer systems. Thus, researchers have used the model to predict the adoption of AI systems like autonomous vehicles [48], [52], chatbots [9], and service robots [26]. Most studies found that perceived usefulness and perceived ease of use are strong predictors of behavioural intention to use AI [9], [26], [48], [52]. ...
... Thus, researchers have used the model to predict the adoption of AI systems like autonomous vehicles [48], [52], chatbots [9], and service robots [26]. Most studies found that perceived usefulness and perceived ease of use are strong predictors of behavioural intention to use AI [9], [26], [48], [52]. However, a field experiment in the context of self-driving cars shows that perceived ease of use has no significant effect on continuance use (willingness to reride in a self-driving car) [49]. ...
... Theoretically, this antecedent has been explained using theories like 1 Frequency in parentheses. service robot acceptance model [39], and by extending established theories like UTAUT [18], [32], [34], TAM [9], [46], [48], and parasocial relationship theory [40], [41]. Furthermore, anthropomorphism is the only antecedent of AI adoption that classic technology adoption theories do not explain. ...
... Interestingly, research on AVs employing theories and models exploring behavioral intention has only recently emerged. Several studies have adopted the original Technology Acceptance Model (TAM) proposed by Davis (1989) and Venkatesh and Davis (1996) (Buckley et al. 2018;Choi and Ji 2015;Nastjuk et al. 2020;Panagiotopoulos and Dimitrakopoulos 2018;Wu et al. 2019). Although these studies developed comparable models, they reported mixed results in terms of the association between the perceived ease of use, perceived usefulness, and the intention to ride in AVs. ...
... Although these studies developed comparable models, they reported mixed results in terms of the association between the perceived ease of use, perceived usefulness, and the intention to ride in AVs. For example, Buckley et al. (2018) and Choi and Ji (2015) did not find a statistically significant association between all the components of the original TAM and the behavioral intention to ride in AVs, whereas Panagiotopoulos and Dimitrakopoulos (2018) and Wu et al. (2019) reported such associations to be significant. ...
... The component of safety perceptions herein aims to capture an individual's beliefs regarding the potential safety benefits of AVs (perceived safety benefits). Safety has been argued as one of the main driving forces for the development of AV technology (Panagiotopoulos and Dimitrakopoulos 2018), and attitudes toward safety can influence consumers' preferences towards AVs (Kyriakidis et al. 2015;Motional 2020;Zoellick et al. 2019). Previous studies have reported a significant relationship between safety perceptions (perceived safety benefits), or safety concerns related to AV technology and the behavioral intentions surrounding AVs. ...
Article
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This paper proposes a well-grounded theoretical model to assess the factors influencing the intention to ride in autonomous vehicles (AVs). The model is based on the Theory of Planned Behavior (TPB), which has been decomposed to account for key components of the Diffusion of Innovation (DoI) theory and extended to include other influential attitudinal components (such as driving-related sensation seeking, safety perceptions, environmental concerns, and affinity to innovativeness). The extent to which these factors are expected to affect the diffusion of AVs uniformly across different urban settings is also examined. Data were collected through stated preference surveys targeting adult residents in three metropolitan statistical areas, Chicago (Illinois), Indianapolis (Indiana), and Phoenix (Arizona). Confirmatory factor analysis was conducted to test the validity and reliability of the components included in the theoretical model, followed by the estimation of a multi-group structural equation model. The findings of the measurement model show that the survey questions are measured equally across the three areas, and hence, the theoretical model is transferrable. The results of the structural model suggest that the synergistic effects between TPB and DoI can better explain the behavioral intention to ride in AVs. It was also found that the effect of the TBP components is similar across various areas; however, this is not the case for the DoI components. In general, the findings reinforce the need for wider testing of AV technology in urban areas coupled with public education campaigns to harvest public awareness and acceptance.
... Although many studies have been conducted in recent years that analysed the purchase/choice of autonomous vehicles (AVs) instead of conventional vehicles (e.g., see Gkartzonikas and Gkritza, (2019) for a thorough review), little is known about preferences for different driving controls. A number of different barriers and incentives, such as safety, distrust, convenience, and usefulness, have been reported in the use of AVs versus conventional vehicles (e.g., Kyriakidis et al., 2015;Panagiotopoulos and Dimitrakopoulos, 2018;Bansal et al., 2016;Haboucha et al., 2017;Ipsos MORI, 2014). ...
... In the literature, many studies have tested the behavioural intention of using AVs through the TAM (e.g., Wu et al., 2019;Lee et al., 2019;Zhang et al., 2019;Panagiotopoulos and Dimitrakopoulos, 2018;Xu et al., 2018). For instance, Xu et al. (2018) reported that, although PU was positively associated with the intention to use AVs, PEU was only positively associated with the intention to reuse AV after the actual first use. ...
... For instance, Xu et al. (2018) reported that, although PU was positively associated with the intention to use AVs, PEU was only positively associated with the intention to reuse AV after the actual first use. Panagiotopoulos and Dimitrakopoulos (2018) showed that both PEU and PU components significantly affect the intention to use AV, and PU had the largest effect among different variables. The second hypothesis of the study is stated as follows. ...
Article
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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.
... In addition, users were mostly influenced by family members, peers, friends and colleagues to use AVs and mobile health devices (Hoque, 2016;Walter & Abendroth, 2020;Ye et al., 2019;Yuen, Thi, et al., 2020). A negative relationship was observed between SNs and trust, implying that the more trust people have in their IU for AVs, the less will they be influenced by family members, friends and peers (Panagiotopoulos & Dimitrakopoulos, 2018). ...
... Trust has been found to exhibit strong direct and indirect effects on BI and overall acceptance of AVs and AI-based healthcare technologies. It was confirmed that trust has a significant direct effect on BI in AD and healthcare (Dirsehan & Can, 2020;Fan et al., 2020;Nadarzynski et al., 2019), while it was the most important, but not the only, direct antecedent of BI to use AVs (Panagiotopoulos & Dimitrakopoulos, 2018;Zhang, Tan, et al., 2019). and Man et al. (2020) found that trust has a stronger effect than PU and PEOU on attitudes towards AVs, which was explained by the fact that, in uncertain situations, trust is a solution for the specific problems related to the risk factors. ...
... In particular, it was found that, compared with men, women are more likely to trust and adopt AVs (J. Lee, G. Abe, et al., 2020;Panagiotopoulos & Dimitrakopoulos, 2018). Panagiotopoulos and Dimitrakopoulos (2018) identified that women (almost 78%) were more likely to have or use AVs when they became available on the market, while the corresponding percentage of men was lower (almost 59%). ...
Article
Objective: The study aimed to provide a comprehensive overview of the factors impacting technology adoption, to predict the acceptance of artificial intelligence (AI)-based technologies. Background: Although the acceptance of AI devices is usually defined by behavioural factors in theories of user acceptance, the effects of technical and human factors are often overlooked. However, research shows that user behaviour can vary depending on a system's technical characteristics and differences in users. Method: A systematic review was conducted. A total of 85 peer-reviewed journal articles that met the inclusion criteria and provided information on the factors influencing the adoption of AI devices were selected for the analysis. Results: Research on the adoption of AI devices shows that users' attitudes, trust and perceptions about the technology can be improved by increasing transparency, compatibility, and reliability, and simplifying tasks. Moreover, technological factors are also important for reducing issues related to human factors (e.g. distrust, scepticism, inexperience) and supporting users with lower intention to use and lower trust in AI-infused systems. Conclusion: As prior research has confirmed the interrelationship among factors with and without behaviour theories, this review suggests extending the technology acceptance model that integrates the factors studied in this review to define the acceptance of AI devices across different application areas. However, further research is needed to collect more data and validate the study's findings. Application: A comprehensive overview of factors influencing the acceptance of AI devices could help researchers and practitioners evaluate user behaviour when adopting new technologies.
... A variety of approaches and theoretical frameworks have been utilized in the literature to determine factors influencing users' behavioral intention to use different travel modes. For example, Panagiotopoulos and Dimitrakopoulos (2018) extended the concepts of the Technology Acceptance Model (TAM) (Davis, 1985) by adding the two factors of perceived trust (or reliability) and social influence to characterize the intention to adopt autonomous vehicles. Featherman et al. (2021) developed a Risk-Benefit model to examine the adoption of electric vehicles, and in the context of micromobility, Kopplin et al. (2021) employed UTAUT2 (i.e., Unified Theory of Acceptance and Use of Technology) to model e-scooter adoption, and reported that environmental concerns and perceived safety are two critical factors affecting usage intention toward e-scooters. ...
... On this basis, various studies have substantiated the effect of these two factors on customers' intention to adopt a service, especially in the context of information technology such as intention to use e-marketing (Kanchanatanee et al., 2014), and smartphone purchase (Suki & Suki, 2011). Furthermore, the perceived usefulness and perceived ease of use are jointly correlated with the adoption of driverless vehicles (Panagiotopoulos & Dimitrakopoulos, 2018), electric vehicles (Wolff & Madlener, 2019), and car-sharing services (Sun et al., 2021). Similar associations have been corroborated in the investigation of bike-sharing (Yu et al., 2018) and e-scooter intention adoption (Rejali et al., 2021). ...
... On this basis, the social influence may affect the individual's continuance intention. This relationship has been established in investigating the intention to use autonomous vehicles (Panagiotopoulos & Dimitrakopoulos, 2018), and continuance intention to keep adopting bike-sharing services (Eccarius and Lu, 2020;Kaplan et al., 2015). Moreover, social influence can also affect a person's perceived usefulness (Venkatesh & Bala, 2008). ...
Article
As e-scooters become more popular, service providers and policymakers are seeking ways to retain the existing customers and encourage them to continue to use e-scooters in the future. In this study, we extend the concepts of the technology acceptance model to identify the factors that affect the intention to continue using e-scooters. We build our findings based on survey data including 2126 shared e-scooter users in Chicago. Using Partial Least Squares Structural Equation Modeling, we analyzed the data and 10 proposed hypotheses. Our empirical results substantiate that the proposed model provides a theoretical framework to understand the continuance intention of shared e-scooter users. According to the findings, the most salient factor determining users’ decisions is perceived usefulness, followed by perceived reliability. The significance of reliability necessitates taking measures to guarantee the availability of e-scooters in times and places they are needed, particularly for mandatory trips. Additionally, social influence, perceived ease of use, variety seeking, and perceived enjoyment, are evinced to represent the other critical drivers of using e-scooter in the future, and in order of precedence. The insights from this study can assist shared e-scooter operators, transportation planners, and policymakers in making informed decisions and pave the way for a greater inclination to continue using shared e-scooters and move toward smart cities.
... Perceived Trust. PT indicates the degree to which consumers generally trust a particular technology system [26]. Many studies on the public adoption of AVs have focused on the effect of PT or perceived risk on user acceptance. ...
... Many studies on the public adoption of AVs have focused on the effect of PT or perceived risk on user acceptance. Safety factors have been demonstrated as strong predictors of public adoption [26][27][28]. In fact, consumers have always been concerned about the safety of robo-taxis and AVs. is safety concern includes data safety concerns and body safety concerns. ...
... SI plays an important role in public acceptance of new technologies, such as AVs [19]. Acceptance of AVs by friends or family members increased users' confidence in the technology as well as their intention to purchase or actual purchase [26,31]. SI has also been tested in other psychological models, such as UTAUT [14] and UTAUT2 [15]. ...
Article
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With the development of autonomous driving technologies, robo-taxis (shared autonomous vehicles) are being tested on real roads. In China, in particular, people in some cities such as Beijing and Shanghai can book a robo-taxi online and experience the service. To examine the influential factors on user acceptance of robo-taxi services, this study proposes and employs an extended technology acceptance model (TAM) with four external factors: perceived trust, government support, social influence, and perceived enjoyment. Data were collected through an online questionnaire in China, and responses from 403 respondents were analyzed using structural equation modeling. Both typical TAM factors—including perceived ease of use, perceived usefulness, and attitude—and external factors were found to play significant roles in predicting users’ intention to use robo-taxis. The four external factors influenced the user acceptance indirectly via typical TAM factors. Improving users’ perceived trust is important for increasing public adoption. A greater emphasis by manufacturers on safety concerns, wider dissemination of information on data protection and safety systems, and government support through incentives for manufacturers and users can help improve public adoption of robo-taxi services.
... Předpokládaná vyšší bezpečnost AV oproti konvenčním vozům je jedním z hlavních argumentů pro jejich široké přijetí. Průzkumy ukazují, že důvěra v bezpečnost AV zvyšuje jejich akceptaci (Brown et al., 2014;Casley et al., 2013;Howard and Dai, 2014;Hulse et al., 2018;Panagiotopoulos and Dimitrakopoulos, 2018;Shabanpour et al., 2018;Zmud et al., 2016;Zoellick et al., 2019). Jednotlivé studie se ale liší v tom, jakým způsobem bezpečnost konceptualizují. ...
... Další (Kyriakidis et al., 2015) bezpečnost tematizují jako kritérium, které respondenti zvažují nebo z něj mají obavy. Podobně jako jiní autoři (Panagiotopoulos and Dimitrakopoulos, 2018) zjistili, že obavy o bezpečnost AV snižují ochotu AV přimout. ...
... Obecně můžeme říci, že platí přímá úměra -tedy relativní výhoda, kompatibilita a komplexita zvyšuje pravděpodobnost akceptace AV (Brown et al., 2014;Choi and Ji, 2015;Haboucha et al., 2017;Howard and Dai, 2014;Kaur and Rampersad, 2018;König and Neumayr, 2017;Liu et al., 2018;Nielsen and Haustein, 2018;Nordhoff et al., 2018;Panagiotopoulos and Dimitrakopoulos, 2018;Payre et al., 2014;Shabanpour et al., 2018;Zmud et al., 2016). ...
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S dynamickým vývojem automatizace v posledním desetiletí přichází do systému osobní dopravy i trend autonomní mobility (CCAM), tj. nových přepravních (mobilitních) služeb využívajících technologii autonomních vozidel. Celá vize autonomní mobility navíc funguje v synergii se službami C-ITS, elektromobilitou a systémy MaaS. Jedná se tedy o sérii inovací, na které se budou v horizontu 10 let muset města a regiony připravit. Kniha je průvodcem v tématu, poskytuje orientaci potřebnou pro rozhodování o politikách, realizaci pilotů, tvorbu strategických, koncepčních či metodických dokumentů a doplňuje metodiku zavádění AV technologií do měst o potřebný kontext. Celkově kniha postihuje historii a současnost vývoje CAD, stupně automatizace řízení SAE, společenské, technologické a spotřební trendy, lidský faktor, kontext transformace, lokální i evropskou veřejnou politiku, automatizaci řízení vozidel a autonomní mobilitu, systémy automatizace řízení a HD mapy, nové mobilitní služby, systém MaaS, proces akceptace a adopce, inteligentní dopravní systémy, jejich služby a aplikace a elektromobilitu. Full-text: https://www.shopcdv.cz/cs/autonomni-mobilita-pro-21-stoleti
... As a single theoretical perspective is insufficient for comprehensive analysis and a better understanding of the adoption decisionmaking process [17], it is necessary to integrate various theories or additional factors according to the specific background to improve the model's explanatory power [8,[17][18][19][20]. On the other hand, the dominant methodology employed in empirical studies for analyzing the relationships between independent and dependent variables is the conventional symmetric-based approaches, e.g., multiple regression analysis [12,14,[21][22][23], covariance-based structural equation modeling (CB-SEM) [11,17,[24][25][26][27][28], and partial least square (PLS-SEM) [6,16,17,[29][30][31][32]. e traditional methodologies, which are only centered on the net effects of individual variables, are criticized for multicollinearity and symmetry [33][34][35]. At the same time, the relationship between antecedents and consequences, in reality, is highly asymmetric [36,37]. ...
... For psychological studies, based on psychological or behavioral theories, many conceptual models have been proposed to study the adoption of different CAVs, e.g., Environmental concern * , green PU * , and PEOU * on BI [24] Trust and TAM Autonomous vehicles Online survey (369 German participants) & SEM Trust * , concern of giving up control * , PU * , PEOU, driving enjoyment * , and personal innovativeness * on the adoption intention of AVs autonomous delivery vehicles [46], automated shuttles [26], autonomous electric buses [54], shared autonomous vehicles [48,68,69], connected vehicles [9,31], and Robo-taxi services [23]. Various factors have been empirically found to have a significant influence on accepting CAVs among multiple regions, e.g., Korea [5,11,16,22,53], Germany [17,24,26,31,46,49,54], China [2,6,13,25,27,30,32,45], United States [7,9,15], Singapore [47], Australia [12], Vietnam [48], Hungary [28], Turkey [50], Taiwan [8], France [4], and Greece [14,21]. ...
... In terms of methodology, most empirical studies have employed the conventional symmetric-based methods, e.g., the regression model [14,[21][22][23], structural equation modeling (SEM) [2, 4, 8, 11, 13, 15, 24-28, 45-48, 50, 54], and partial least square (PLS) [6, 16, 17, 29-32, 49, 53], to investigate the effects between variables. However, these methods emphasize the net effect, while ignoring possible asymmetric relations between variables in complex contexts, resulting in the correlation coefficients and significance that may differ in various models. ...
Article
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To accelerate the widespread adoption of connected and autonomous vehicles (CAVs) and take full advantage of CAVs’ transportation safety, efficiency, and pro-environment, a deep understanding of CAVs acceptance is needed. However, little is known about the combined effects of factors influencing CAVs acceptance using traditional statistical methods. We developed an integrated model to explore how various antecedent factors work together on CAVs’ acceptance. The symmetric (Structure Equation Modeling) and asymmetric (Qualitative Comparative Analysis) techniques were utilized for analyzing data from 362 Chinese. PLS-SEM assesses the net effect of each antecedent on CAVs’ adoption, while fsQCA provides supplementary analysis by revealing the configurations of causal conditions associated with CAVs’ adoption. PLS-SEM results show that perceived usefulness, perceived ease of use, and initial trust directly influence users’ willingness to adopt CAVs, while perceived risk, social influence, and facilitating conditions do not. Meanwhile, automation, ubiquitous connectivity, structural assurance, and corporation reputation indirectly influence CAVs adoption, while environmental performance and technological uncertainty have no statistically significant indirect effect. Interestingly, fsQCA reveals five configurations resulting in a high level of CAVs’ acceptance, and seven configurations leading to the negation of CAVs’ acceptance. The complementary analysis results provide insights into both theory and practice.
... The models are often extended to include pertinent intermediary factors (i.e. mediators) such as users' perceived risk and trust, which are key considerations that affect public acceptance of AVs (Zhang et al. 2019;Choi and Ji 2015;Panagiotopoulos and Dimitrakopoulos 2018). At present, few studies have synthesised several behavioural theories which can contribute to providing a more coherent explanation to AV acceptance. ...
... Critical mass should be achieved for a society to effectively reap the benefits of AVs, and public acceptance is vital for achieving the critical mass (Panagiotopoulos and Dimitrakopoulos 2018). Researchers have been investigating public's acceptance or resistance to AVs and have found inconsistent results. ...
... These group members can influence or demand each other to use APT through conformity, socialisation, obedience, leadership, or persuasion (Panagiotopoulos and Dimitrakopoulos 2018). When an individual's groups are generally positive (or negative) about APT, their positive (or negative) expectations and information about the positive (or negative) outcomes regarding the use of the public transport would be conveyed to the individual. ...
Article
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Achieving a critical mass in the acceptance of fully autonomous public transport (APT) is crucial for a society to effectively realise APT’s intended environmental, social and economic benefits. The current study analyses the determinants contributing to user acceptance of APT through three theoretical lenses, namely, Unified Theory of Acceptance and Use of Technology (UTAUT), Perceived Value Theory and Social Exchange Theory. Survey data were collected from 476 commuters in Beijing, China. The results reveal that the five dimensions of UTAUT (i.e. performance expectancy, effort expectancy, social influence, facilitating conditions and hedonic motivation) have positive influence on users’ value perception of APT. Consequently, users’ value perception of APT exerts both direct and indirect influences on users’ acceptance of APT via trust. A key contribution of this study is the combination and synthesis of several complementary behavioural theories to explain user acceptance of autonomous vehicles. In addition, the results offer important implications for transport policymakers and operators, in particular, pertaining to areas on resource allocation, marketing, communication and education to improve user acceptance of APT.
... First, "Increased Effort" induced by the system (C4) can be a reason for disuse reflecting the PEoU (Davis, 1985) but also the output quality (Venkatesh & Bala, 2008). Thus, ADAS and IVIS should be easy to use which is supported in previous studies on acceptance of automated driving (Buckley et al., 2018;Choi & Ji, 2015;Panagiotopoulos & Dimitrakopoulos, 2018;Xu et al., 2018). However, in this study, the individual appreciation of the own and the system's capabilities was also reported as a reason for disuse of driver assistance systems. ...
... Trust or "Distrust" (C8) are not part of classic acceptance models. However, trust has been repeatedly shown to be important for invehicle technology usage (Buckley et al., 2018;Choi & Ji, 2015;Ghazizadeh et al., 2012;Panagiotopoulos & Dimitrakopoulos, 2018;Xu et al., 2018). Thus, our study supports that developing trust is important for technology acceptance. ...
... In addition, the subjective norm, image, or external control comprising organizational and technical resources (Venkatesh & Bala, 2008) were not mentioned by the drivers. In previous studies, social influences emerged as significant influence on acceptance of automated driving (Buckley et al., 2018;Kaye et al., 2020;Panagiotopoulos & Dimitrakopoulos, 2018). For IVIS usage however, drivers only mentioned social influences and discussions about IVIS use in the purchasing process while the majority of drivers never talked about safety of IVIS use while driving (Oviedo-Trespalacios et al., 2019). ...
Article
The vehicle is increasingly equipped with additional technology assisting and entertaining the driver. To improve the systems and increase their usage, it is important to understand what influences the acceptance of technology in the vehicle. An online survey was conducted assessing which systems drivers own and use in their vehicles today. For the equipped systems, the reasons why N = 304 drivers do not use their in-vehicle technology were qualitatively explored. An inductive content analysis revealed 13 categories in total. The three categories “Need”, “Context and Task”, and “Reliability” were associated with Perceived Usefulness while “Increased Effort” and “Aversion” were associated with Perceived Ease of Use (Venkatesh, 2000). In addition, the influencing factors are further extended with the “Preference for Own Action”, “Distrust”, “Safety”, “Knowledge”, and “Habit”. The findings reveal subjectively important antecedents of the acceptance of in-vehicle technology and provide new insights, especially on usage barriers. An Integrated Acceptance Model (IAM) is derived from the identified categories to inform future research and facilitate a holistic view on factors influencing technology acceptance.
... In the meantime, due to the more frequent testing, and increasing public awareness of these vehicles, attitudes are evolving as people become more familiar with the technology (Liljamo et al., 2018). Extant research calls for further studies to examine consumer attitudes toward AVs (Pettigrew et al., 2018;Panagiotopoulos & Dimitrakopoulos, 2018). Therefore, the aim of this research is to determine attitudes held towards AVs and understand their impact on the intention to use the service. ...
... A study by Panagiotopoulos and Dimitrakopoulos (2018), found that ease-of-use, perceived usefulness, and trust were the most significant factors in determining attitudes towards AVs. This has been supported by additional studies (Choi and Ji, 2015;Chen, 2019;Lee et al, 2019;Liu et al., 2019;Acheampong and Cugurullo, 2019), confirming the importance of these factors. ...
... As previously identified in ride-hailing literature (Peng et al, 2014;Fleischer and Wåhlin, 2016;Zhu, So and Hudson, 2017;Min So & Jeong, 2018), subjective norms and behavioural control frequently appear in AV research (Panagiotopoulos & Dimitrakopoulos, 2018;Acheampong & Cugurullo, 2019) and are therefore key variables to explore. As such, the two hypotheses below will be used: ...
Article
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The primary aim of this research is to determine attitudes held towards autonomous vehicles (AVs) and understand their impact on intentions to use the service among ride-hailing users in the UK. Based on the Theory of Planned Behaviour model, an online, self-administered survey was used to collect data from 151 consumers (18-24-year-olds). The relationship between variables was measured using a Spearman's Rank test in SPSS. The results of this study found all categories (overall attitude, perceived ease-of-use, perceived value, perceived safety, perceived risk, technology, environmentalism, subjective norms, perceived behavioural control) received a positive mean score. From these results, it can be concluded that this sample holds positive attitudes towards AVs and intend to use the service when they are made available. A positive score for perceived risk, however, indicated that this group thought there may be safety concerns when using this technology. The main contribution of this study is providing data to a new, and rapidly evolving field of research and thus the findings of the present study contribute to ongoing research related to consumers attitudes of AVs. Managerially, companies that focus on developing and implementing AV taxis need to focus more on the safety benefits of such vehicles.
... Other psychological factors positively associated with AV usage include environmental awareness (green travel pattern, green lifestyle, or environmental concern) (Haboucha et al., 2017;Lavieri et al., 2017;Nazari et al., 2018;Rahimi et al., 2020b) and value of time (Haboucha et al., 2017). Based on behavioral theories, researchers have extensively investigated behavior intention (of adopting AVs) with its theoretical antecedents such as perceived usefulness, perceived benefits, perceived risk, subjective norm (social influence), and trust using techniques such as structural equation modeling (Buckley et al., 2018;Hewitt et al., 2019;Kaur and Rampersad, 2018;Panagiotopoulos and Dimitrakopoulos, 2018;Rahimi et al., 2020a;Waung et al., 2021;Xu et al., 2018). ...
... Another direction is to study the latent psychological constructs that shape people's attitudes towards AVs and how they change over time. For instance, perceived usefulness/ benefits is found to be positively associated with public attitudes to AVs (Buckley et al., 2018;Panagiotopoulos & Dimitrakopoulos, 2018;Rahimi et al., 2020a). Perceived safety and risk (Hewitt et al., 2019;Kaur and Rampersad, 2018;Waung et al., 2021;Xu et al., 2018), trust in AV performance, government and manufacturers (Waung et al., 2021;Xu et al., 2018), perceived behavior control (Buckley et al., 2018), social influence and subjective norm (Hewitt et al., 2019;Panagiotopoulos and Dimitrakopoulos, 2018) are also studied widely. ...
... For instance, perceived usefulness/ benefits is found to be positively associated with public attitudes to AVs (Buckley et al., 2018;Panagiotopoulos & Dimitrakopoulos, 2018;Rahimi et al., 2020a). Perceived safety and risk (Hewitt et al., 2019;Kaur and Rampersad, 2018;Waung et al., 2021;Xu et al., 2018), trust in AV performance, government and manufacturers (Waung et al., 2021;Xu et al., 2018), perceived behavior control (Buckley et al., 2018), social influence and subjective norm (Hewitt et al., 2019;Panagiotopoulos and Dimitrakopoulos, 2018) are also studied widely. The understanding of these latent variables could help validate the effectiveness of educational campaigns and policy interventions before and after they take place for greater AV penetration. ...
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A growing number of research attempts have been made to enhance our knowledge about the characteristics of the potential early Autonomous Vehicle (AV) adopters. However, little is known about whether the public attitudes towards AVs change over time and how. With a multiyear cross-sectional travel survey data of the Puget Sound Region that encompasses the Seattle metropolitan area, we analyzed the fractions of population with various levels of interest and concerns regarding AVs. A two-part model combining a binary logit model and a partial proportional odds model was utilized to investigate the change of individuals’ positions on AVs over time, controlling for their socio-demographic characteristics, travel behavior characteristics, and built environment attributes. We find that the percentage of population unfamiliar with AVs has declined over the years, which is probably due to a greater exposure to the information about AVs. All other variables being equal, individuals’ interest in AVs has not changed over time while their concerns have increased across time. The findings suggest that information campaigns or educational programs that introduce the advantages of AV adoption with a focus on the safety aspects of AVs could potentially alter public attitudes, which could help achieve greater market penetration.
... Numerous studies have established perceived usefulness as a significant predictor of behavioral intention (Baccarella et al., 2020;Jing et al., 2021;Yuen et al., 2020a;Zhu et al., 2020). Xu et al. (2018) and Panagiotopoulos and Dimitrakopoulos (2018) revealed perceived usefulness as the strongest predictor and the most important factor for AV adoption. Studies have posited that manufacturers should emphasize the utility of the AVs, such as enhanced safety (Liu et al., 2020), productivity improvement, energy savings (Baccarella et al., 2020), efficient parking space utilization, and other environmental benefits (Wu et al., 2019) to promote the usefulness of AVs. ...
... Opinions of the important social-circle members such as family, friends, colleagues, and peers were found to influence the adoption intention of AVs significantly. The car is perceived as a status symbol in the social environment and adds to the consistent support for the social influence construct (Panagiotopoulos & Dimitrakopoulos, 2018). Thus, we put forward the following hypothesis: ...
... Among the technological factors, perceived usefulness emerged as strongest determinants of intention. This result is consistent with the prior studies (Kapser & Abdelrahman, 2020;Panagiotopoulos & Dimitrakopoulos, 2018). Hypothesis H1b proposed the relationship between perceived usefulness and attitude -this was supported in our result. ...
Article
The ongoing competition between traditional vehicle manufacturers and technology companies for quickly developing autonomous vehicles (AVs) and gaining early traction in the market is well known. However, some issues need to be cleared regarding the antecedents of the behavioral intention to use AVs. In this context, we conducted a meta-analysis using the TIS (Technological, Individual, and Security) framework, to understand the convergence and divergence of the factors influencing the behavioral intention to use AV technology. This meta-analysis tested the hypotheses using a database of 65 studies obtained from 58 articles with the cumulative sample size of 37,076. The study identified perceived usefulness, attitude, trust, safety, hedonic motivation, and social influence as the critical antecedents of AV adoption. Several of the relationships investigated in the study were moderated by factors such as level of automation, vehicle ownership and culture. The results revealed fewer incentives for the public to accept AVs. Theoretical contributions and recommendations to practitioners and policymakers have also been discussed.
... The ability of AVs to operate without human intervention depends on their level of technological sophistication, in accordance with the current six-degree autonomy scale proposed by the International Society of Automotive Engineers (SAE) [68,[76][77][78][79][80][81] from Level 0 (without automation) to Level 5 (full unlimited automation); Levels 1 to 3 are considered "semi-autonomous" (Table 1). [76][77][78][79][80][81]. ...
... The ability of AVs to operate without human intervention depends on their level of technological sophistication, in accordance with the current six-degree autonomy scale proposed by the International Society of Automotive Engineers (SAE) [68,[76][77][78][79][80][81] from Level 0 (without automation) to Level 5 (full unlimited automation); Levels 1 to 3 are considered "semi-autonomous" (Table 1). [76][77][78][79][80][81]. ...
Article
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The automotive market has been developing very dynamically recently. Contemporary trends focus on the development of the so-called intelligent vehicles, often combined with modern technology and supporting systems. Cars with a large scope of operation in terms of driving autonomy can increasingly be found. These types of solutions can lead to changes in production processes through the emergence and growing importance of new concepts and technologies. The article presents the concept of BEV (Battery Electric Vehicle) and PHEV (Plug-in Hybrid Electric Vehicle) vehicles in relation to modern solutions and their levels of autonomy. The research was conducted in various groups of respondents, while the analyses were carried out mainly with the use of two grouping variables: gender and place of residence. Based on our own research, it can be concluded that due to many different factors, most respondents believe that PHEV hybrid vehicles and electric vehicles (BEV) are currently, and will most likely be in the near future, the dominant type of vehicles appearing on roads in Poland, at the same time indicating the level of advancement of autonomy as average (mainly level 1, 2 and 3).
... We supplement this model by incorporating a factor to reflect consumer trust in the technology, appropriately titled 'Trust in Technology' (TT), adapting the construct from the research of Kim et al. [16]. This inclusion is supported by the work of Panagiotopoulos and Dimitrakopoulos [20], who write [9] that "few adaptations of the technology acceptance model have considered trust as a determinant of acceptance; however, those who have done so have found trust to be a determinant of intention to use, i.e. in the context of e-services and e-government applications" pointing to the publications of Mou et al. [19] and Gupta et al. [9]. Furthermore, in a later study of Kapser et al.'s [14], also investigating autonomous delivery vehicles, the authors incorporate such a construct. ...
... Moreover, Kapser and Abdelrahman [15] bring attention to the work of Hulse et al. [12], who write that "to date, there is limited research on the psychological factors that determine public acceptance of AVs from an outside vehicle perspective". While this technology holds great potential, "societal benefits will not be achieved unless these vehicles are accepted and used by a critical mass of people; thus, it will be important to understand consumers' acceptance" [20]. In particular, we built on the original work of Kapser and Abdelrahman [15] by exploring the topic from the cultural context of the United States. ...
Preprint
This paper investigates the end-user acceptance of last-mile delivery carried out by autonomous vehicles within the United States. A total of 296 participants were presented with information on this technology and then asked to complete a questionnaire on their perceptions to gauge their behavioral intention concerning acceptance. Structural equation modeling of the partial least squares flavor (PLS-SEM) was employed to analyze the collected data. The results indicated that the perceived usefulness of the technology played the greatest role in end-user acceptance decisions, followed by the influence of others, and then the enjoyment received by interacting with the technology. Furthermore, the perception of risk associated with using autonomous delivery vehicles for last-mile delivery led to a decrease in acceptance. However, most participants did not perceive the use of this technology to be risky. The paper concludes by summarizing the implications our findings have on the respective stakeholders and proposing the next steps in this area of research.
... Education level has not always been a clear indicator in one direction, although the highly-educated tend to be less concerned about the safety of AVs (Barbour et al., 2019;Haboucha et al. 2017). Car ownership and high income, despite being found to have insignificant impacts in an analysis using TPB (Yuen et al. 2020), are often considered relevant to the acceptance of AVs in the literature (Panagiotopoulos & Dimitrakopoulos 2018;Wadud & Chintakayala 2021). There is little research devoted to the relationship between the size of a city and the intention to use AVs, although much research on the effects of this technology has been done in urban areas (Duarte and Ratti 2018) and seems to indicate that living in urban areas is positively associated with their acceptance (Liljamo et al. 2018). ...
... Income ( AECS, confirming the results from the literature indicating the high interest for AVs (Panagiotopoulos & Dimitrakopoulos 2018). ...
Article
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Electric car-sharing services (ECS) have been promoted as a solution to combat negative urban mobility externalities and are expected to be facilitated by fleets of autonomous vehicles. There is little evidence regarding the behavioral intention to use autonomous ECS (AECS), especially on the transition from using ECS. This paper investigates the behavioral intention to use AECS using psychological constructs partially from the extended unified theory of acceptance and use of technology (UTAUT2) and an additional one expressing safety concern. A novel behavioral intention model is presented to capture the transitional behavioral intention to use two adjacent generations of sharing mobility services. Results of structural equation models applied to a survey sample of 2154 respondents from France, Italy, Netherlands, and Spain show that the introduction of AECS is very likely to be accepted by ECS users. Hedonic motivation is found to be a much stronger predictor of behavioral intention to use AECS as opposed to safety concern, while performance expectancy and social influence are strong drivers of intention to use ECS and have indirect effects on the intention to use AECS. Multigroup analysis indicates heterogeneous behavioral intention across countries. The multi-faceted empirical results generate insights into the deployment and management of AECS in various contexts.
... Surveys from the American Automobile Association (Edmonds, 2018(Edmonds, , 2019 demonstrated that the negative attitudes towards the use of AVs is slowly decreasing over time. At the same time, although some studies have shown that a low level of acceptance can constitute the main barrier to the adoption of AVs (Noy et al., 2018;Xu et al., 2018;Liu et al., 2019), others found that people may wait before using the technology, identifying themselves as late adopters (Zmud and Sener, 2017;Panagiotopoulos and Dimitrakopoulos, 2018). This comes together with field research that show the positive impact of the use of shuttles on the willingness to use AVs, pointing out the impact of experience on the acceptance (Piao et al., 2016;Bernhard et al., 2020;Shi et al., 2021). ...
Article
Do citizens, media and policymakers share the same view on autonomous cars? In the present paper, we analyse data from media articles, a Eurobarometer survey, and policy documents, to understand the perspective of different stakeholders when it comes to autonomous cars. We find significant differences between the groups, with a predominance of negative sentiments in news articles and a majority of citizens being wary of autonomous cars, while the political narrative mostly carries a positive tone. The findings highlight a dichotomous perspective about this potentially disruptive technology. This may represent a problem as the benefits of adopting autonomous cars will only come to surface if all actors are engaged and see the advantages they can bring to people’s daily lives. We conclude by encouraging policymakers to promote initiatives to engage citizens in the transformation of road transport and other stakeholders to be advertised the positive implications of autonomous vehicles.
... Although the aforementioned Bayesian network includes seven input evidences (M = 7), 'i-LoDAS' functionality is highly scalable, in that it can be readily generalized to include more causes-parameters, as well as to be easily adapted to different input causes. It should be noted that the five driving automation capabilities and service parameters were selected according to the results of a large number of relative recent published surveys [26][27][28][29][30][31][32], which have been conducted in providing insight into the factors that affect potential consumers' intension to accept and use HAVs' technology. Please note that features related to the driver of the HAV (profile parameters) have not been considered in the present analysis. ...
Article
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Highly automated vehicles (HAVs) are expected to fundamentally change the on‐road transportation field by increasing traffic flow efficiency, reducing road crashes caused by human errors, and increasing comfort and driving productivity. With the help of recent developments in cognitive management techniques and machine learning analysis, intelligent on‐board computing services are gaining acceptance. The main goal of the present paper is to introduce and develop a novel on‐board cognitive decision‐making functionality that dynamically and automatically enables HAVs to operate each time in the best available level of driving automation (LoDA). The proposed functionality utilizes several attributes associated with the driving environment and the driver's personality characteristics and personal preferences. The cognitive nature of the proposed functionality is based on previous knowledge, turned into experience, by implementing the Naive Bayes classifier supervised machine learning method. The effectiveness of the proposed cognitive functionality, in terms of accuracy and speed of convergence, in proactively identifying the optimal LoDA, is illustrated by modelling and analysing three scenarios with regards to drivers with different profile data and to driving scenes with different environment characteristics. Therefore, it can operate as an in‐car intelligent personal assistant for the drivers.
... However, in general, the performance expectancy significantly affects the buyers; intention to adopt novel technologies (Venkatesh et al. 2003). Like some related studies (Panagiotopoulos and Dimitrakopoulos 2018;Choi and JI 2015;Rahman et al. 2017), the effort expectancy had a positive and significant effect on the buyers; intention (H2). The more the users feel that the use of delivery drones is an easy and trouble-free procedure, the more intention they will show to this method (Venkatesh, Thong, and XU 2012). ...
Article
This study is aimed at determining the factors influential in the acceptance of delivery drones as a new way for last-mile delivery in the future. In this regard, the study model was proposed using the UTAUT2 as the base model and adding the factors of psychological characteristics, perceived risk, and need for human interaction to it. The information about 357 Iranian buyers was collected for the PLS-SEM by designing an online questionnaire. The results indicated that all variables of UTAUT2, except for performance expectancy, had a positive and significant effect on the intention of buyers to use delivery drones. Moreover, the personal norm positively affected the users’ intention, while the need for human interaction and perceived risk had adverse effects on it. The research findings indicated that innovativeness had a significant positive effect on effort expectancy and compatibility while having an insignificant effect on performance expectancy.
... With the future commercialization of AVs, increasing attention is being paid to public perception and acceptance. Existing studies of AV acceptance have been based on theories of human behavior, with the three most common being the technology acceptance model (TAM) (e.g., Zhang et al., 2020;Lee et al., 2019;Panagiotopoulos and Dimitrakopoulos, 2018;Xu et al., 2018), theory of planned behavior (TPB) (e.g., Chen and Yan, 2019;Buckley et al., 2018) and unified theory of acceptance and use of technology (UTAUT) (e.g., Kaye et al., 2020;Madigan et al., 2017). A variety of factors have been studied, with special attention paid to perceived ease of use, perceived usefulness and trust (Jing et al., 2020;Keszey, 2020). ...
Article
Autonomous vehicles (AVs) offer the opportunity to achieve safe, efficient, accessible, affordable and productive transportation, while also enhancing the mobility of vulnerable groups. Nevertheless, the benefits associated with AVs can only be realized when the mass public have the intention to make use of this technology. This study aims to examine the impacts of several factors on general acceptance of AVs including perceived AV motion sickness, willingness to use time more efficiently in an AV, perceived value of time and perceived risk using private SAE Level-5 AVs, as well as the interrelationships between these factors. Using a sample of 1,418 respondents, partial least squares structural equation modeling (PLS-SEM) was used to test the proposed structural model. Results revealed that perceived value of time, perceived risk and willingness to use time more efficiently in an AV significantly affected the behavioral intention. Results from multi-group analysis showed that participant age also played a role in behavioral intention via the perceived value of time. It is hoped that the findings of this study can help AV policymakers and developers better understand the role that the studied factors play in shaping public intentions to use AVs.
... As a result, these cars are more environmentally friendly and cost less. In addition, self-driving cars do not emit any tailpipe, thus helping to reduce air pollution [7][8][9]. However, with the continuous development of autonomous driving, the safety issues of autonomous driving have gradually emerged [10,11]. ...
Article
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Autonomous driving is a safety-critical system, and the occupancy of its environmental resources affects the safety of autonomous driving. In view of the lack of safety verification of environmental resource occupation rules in autonomous driving, this paper proposes a verification method of automatic driving model based on functional language through CSPM. Firstly, the modeling and verification framework of an autopilot model based on CSPM is given. Secondly, the process algebra definition of CSPM is given. Thirdly, the typical single loop environment model in automatic driving is abstracted, and the mapping method from automatic driving model to CSP is described in detail for the automatic driving environment and the typical collision, overtaking, lane change and other scenes involved. Finally, the autopilot model of the single loop is mapped to CSPM, and the application effect of this method is discussed by using FDR tool. Experiments show that this method can verify the safety of autonomous driving resources, thereby improving the reliability of the autonomous driving model.
... Also, Buckley, Kaye, and Pradhan (2018) found subjective norm to be positively associated with the intention to adopt AVs. Social influence has been found to be a predictor of AVs' adoption (Nastjuk et al., 2020;Panagiotopoulos & Dimitrakopoulos, 2018). Based on the above, we suggest that: ...
Article
Autonomous Vehicles (AVs) have the potential to transform the transportation industry with significant economic, social and environmental benefits. However, the mass deployment of AVs depends on public desire to use them. This study aims to examine the effect of instrumental, symbolic, and affective motives on the behavioural intention to use fully AVs. Based on a survey of 240 U.S. residents, a structural equation modeling analysis was performed. Our results suggest the behavioural intention to use fully AVs depends on fulfilling instrumental (i.e., performance expectancy and hedonic motivation), symbolic (i.e., personal innovativeness and social influence) and affective motives (i.e., trust and performance risk). These results have implication for designing policy interventions to increase the deployment of AVs.
... Model, TAM) [7] 、计划行为理论(Theory of Planted Behavior, TPB) [8] ,以及融合了这两类模型优势 的整合型技术接受 (United Theory of Acceptance and Use of Technology, UTAUT) [ [12] 在 TAM 模型的基础上引入了感知信任和社会影 响,并证实了感知信任、社会影响和感知有用性 及感知易用性对使用意向的显著性影响。黄位 [13] 融合了 TAM 与 TPB 模型,发现感知有用性、感 知易用性、主观规范、感知行为控制均会影响我 国消费者对自动驾驶汽车的接受度。 Madigan 等 [14] 基于 [16] 、共享汽车 [17,18] 、共享单车 [19] 、 自动驾驶车辆 [13- ...
Article
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为探究自动驾驶网约车使用意向的影响因素及作用路径,以技术接受模型(TAM)为基础框架,在自动驾驶车辆感知有用性和感知易用性基础上,从出行者使用网约车经验和社会偏好两个维度分别引入网约车出行习惯、网约车平台感知可靠性、网约车出行社会影响和出行者利他性偏好四类潜变量,构建自动驾驶网约车使用意向的结构方程模型。对 367 份有效问卷进行参数拟合,结果证实了引入心理潜变量后的 TAM 模型具有良好的适配性,能够解释使用意向总方差的 59.4%。路径分析结果表明,影响自动驾驶网约车最直接的三个因素是自动驾驶车辆的感知有用性、出行者利他性偏好、网约车出行习惯,对应的直接效应分别是 0.591、0.243 和 0.146。网约车平台感知可靠性、自动驾驶车辆感知易用性、网约车出行社会影响对自动驾驶网约车使用意向的影响作用,均可被上述三类潜变量完全或部分中介。受教育程度较低的出行者,对网约车平台可靠性的认可度更高,对未来自动驾驶网约车使用意向也更为积极。研究结果对于促进自动驾驶网约车良性发展具有一定的借鉴意义。
... Earlier studies (Asnakew, 2020;Cheng et al., 2006;Kim et al., 2010;Yiu et al., 2007) have also found that in fintech, perceived ease of use has a positive effect on customers' intention towards using fintech services. Therefore, the hypotheses are proposed: Perceived usefulness is the extent to which users perceive that an IS solution could yield a positive outcome (Putritama, 2019) and possibly improve the performance of their ongoing tasks Panagiotopoulos & Dimitrakopoulos, 2018). Originating from the TAM model by Davis (1989), perceived usefulness has been proven to be a solid antecedent of intention to use, with average path coefficients toward beha-vioral intention typically exceeding 60% (Venkatesh & Davis, 2000), and is even considered as the fundamental prerequisite in designing an IS (Kim, 2012). ...
Article
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Peer-to-Peer (P2P) lending platform has enormous potential to improve financial inclusion for people in emerging countries. In this regard, the present study examined the predictors of continuance intention to borrow from P2P lending, especially as a Multi-Sided Platform (MSP) that relied heavily on critical mass to succeed. This research was among the first that analyzed the behavioral intention of P2P lending from the borrower's perspective by expanding on the technology acceptance model (TAM) Organizations and Markets in Emerging Economies with two fundamental latent constructs for MSPs, namely perceived structural assurance and perceived critical mass. This quantitative study used Partial Least Square Structural Equation Modelling (PLS-SEM). Online questionnaires were spread to P2P lending borrowers (n =174) from all over Indonesia to measure the latent constructs. The result revealed that all the exogenous constructs did not have direct relationships with continuance intention to borrow. However, perceived structural assurance and perceived ease of borrowing indirectly affected the endogenous construct through perceived usefulness as the mediating variable. This study also offers some managerial implications for the P2P lending industry.
... Trust, or the attitude that an agent (here, the vehicle) will help achieve an individual's goals [to navigate safely] in a situation characterized by uncertainty and vulnerability (Lee & See, 2004, p. 54), has been investigated as an influence on users' acceptance and use of AVs (Abe et al., 2002). Most research has evaluated initial trust of AVs via self-report questionnaires (e.g., Panagiotopoulos & Dimitrakopoulos, 2018;Zhang et al., 2019) or after experiencing vehicle functions within a simulated driving environment (e.g., Buckley et al., 2018;Gold et al., 2015). Findings suggest that self-reported trust increases after participants have experienced the technology (Gold et al., 2015), and trust has been shown to be a significant positive predictor of future intentions to use AVs (Buckley et al., 2018). ...
Article
Automated vehicles are an emerging technology that operate with differing levels of automatic control (SAE levels). The current study explored participants’ acceptance of a conditional (Level 3) automated vehicle (AV) before and after riding as a passenger for 10 min on open, public roads in uncontrolled traffic. Additionally, participants were asked to rate the riskiness (perceived risk) of a variety of vehicle maneuvers, such as turning, accelerating, and braking when approaching an intersection. We predicted that participants would report higher acceptance ratings and lower perceived risk ratings after experiencing the AV compared to pre-trip ratings. Further, we predicted that participants riding in the front-passenger seat would report higher ratings for risk compared to participants sitting in the rear-passenger or rear-driver seats. Sixty participants from South-East Queensland, Australia (aged 21–82 years; Mage = 45.78; 23 female) took part in the study. Compared to pre-trip responses, participants reported statistically higher ratings for acceptance, as well as statistically lower ratings for perceived risk with respect to specific vehicle maneuvers performed while in automated mode. Differences were detected between seats for perceived risk, but these results were less clear. Increases in acceptance and decreases in risk were also detected as the number of false hazards detected by the vehicle increased. Overall, these findings suggest that acceptance towards AVs may increase, and expectations of risk related to AV maneuvers may decrease, after participants have experienced the vehicles firsthand, on an open, public road in an uncontrolled traffic environment.
... Different levels of automation present stages or progressions of autonomy, ranging from full manual control to full autonomy. Different sequential levels of autonomy are often discussed in the literature; National Highway Traffic Safety Administration presents a taxonomy of six different levels where level 0 is categorized as no automation or full manual control, level 1 as function specific automation, level 2 as combined function automation, level 3 as limited self-driving automation, level 4 as enhanced self-driving automation and level 5 as fully self-driving automation [21]. In this research, our focus is entirely on level 5 and level 4 automation, which signifies a full to enhanced autonomous vehicle, capable of self-driving in all circumstances and requiring minimal to no human involvement. ...
Article
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Given the widespread popularity of autonomous vehicles (AVs), researchers have been exploring the ethical implications of AVs. Researchers believe that empirical experiments can provide insights into human characterization of ethically sound machine behaviour. Previous research indicates that humans generally endorse utilitarian AVs; however, this paper explores an alternative account of the discourse of ethical decision-making in AVs. We refrain from favouring consequentialism or non-consequential ethical theories and argue that human moral decision-making is pragmatic, or in other words, ethically and rationally bounded, especially in the context of intelligent environments. We hold the perspective that our moral preferences shift based on various externalities and biases. To further this concept, we conduct three Amazon Mechanical Turk studies, comprising 479 respondents to investigate factors, such as the "degree of harm," "level of affection," and "fixing the responsibility" that influences people's moral decision-making. Our experimental findings seem to suggest that human moral judgments cannot be wholly deontological or utilitarian and offer evidence on the ethical variations in human decision-making processes that favours a specific moral framework. The findings also offer valuable insights for policymakers to explore the overall public perception of the ethical implications of AV as part of user decision-making in intelligent environments.
... With employees on board, however, there is no effect as people can be assured that employees can help the passengers in case assistance is needed and therefore there is no difference between those who expect the usage to be more complex and those who do not. Effort expectancy was consistently found to directly influence acceptance of AVs and intention to use them (Buckley, et al, 2018;Panagiotopoulos & Dimitrakopoulos, 2018;Xu, et al, 2018;Acheampong & Cugurullo, 2019). Importantly, the present research distinguishes between public AVs with and without an employee on board. ...
Article
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Public autonomous vehicles (AVs) have a high potential to solve traffic related problems and environmental challenges. However, without the passengers’ acceptance, the potential to achieve these benefits will not be fulfilled. Therefore, this paper is focused on the factors that influence the acceptance of such vehicles and investigates how much the acceptance varies if different levels of supervision are provided. An online survey was conducted and factors like trust and experience were found to impact on the stated intention to use a self-driving bus. Additionally, the Unified Theory of Acceptance and Use of Technology (UTAUT) factors, such as, effort expectancy, performance expectancy and social influence were found to impact user intentions. Interestingly, socio-demographic factors appeared to be determinants of the acceptance of public AVs only if an employee was no longer present in the bus. The study highlighted the importance of paying sufficient attention to qualitative psychological factors, next to classic instrumental attributes like travel time and costs, before and during the implementation of public AVs. As experience was found to be a relatively robust factor in explaining public AV acceptance, we expect that preferences towards autonomous public transportation evolve along with the transition from hypothetical scenarios to demonstration pilots, to their deployment in regular operations. We therefore recommend the extension of this research to revealed preference studies, thereby using the results of field studies and living labs. Policy makers and researchers should allow users to access public AVs in test phases, so that users can generate positive experiences. This is expected to reduce future efforts of encouraging the use of this new technology, before its implementation.
... According to the results of Zhang et al. (2020) and Liljamo et al. (2018), trust is another key factor in social acceptance, and it may be positively influenced by increasing the perceived safety of autonomous vehicles and raising awareness of their benefits. Acheampong-Cugurullo (2019) and Panagiotopoulos-Dimitrakopoulos (2018) also demonstrated that subjective norms affect perceived usefulness, perceived ease of use, and perceived safety. According to Nordhoff et al. (2020), the strongest UTAUT2 variable regarding individuals' behavioural intentions was hedonic motivation. ...
Article
The majority of social science studies on self-driving vehicles has focused on accepting technology using a methodology that investigates direct relationships only. However, there is an increasing demand for an in-depth social analysis of self-driving vehicle acceptance, exploring more complex relationships. Here, this challenge is responded to by the statistical modelling of the acceptance of self-driving technology, allowing for an exploration of the direct and indirect relationships among the relevant variables. Most previous studies have also been conducted in developed countries, and limited information is available on the acceptance of self-driving technology in less-developed countries. The present study constructs an explanatory statistical model of the Hungarian population's concept of self-driving vehicles based on a representative sample of 1,001 participants. Furthermore, a graphical representation of the model is provided. The main results include the determination of the most influential factors on the acceptance of self-driving vehicles and the attribution of direct and indirect relationships among the variables, thus providing deeper knowledge than that previously obtained and complementing the currently available research results. Based on results, the expected advantages of self-driving technology have the greatest direct and total impact on the acceptance of this technology in Hungary. The enthusiasm for new technologies and the expected disadvantages of self-driving technology has a slightly weaker direct and second-largest total impact. Information needs on self-driving
... Recent developments in vehicle automation technology are moving us closer to increasingly autonomous and selfdriving vehicles (Panagiotopoulos & Dimitrakopoulos, 2018). The annual global road crash statistics shows that nearly 1.25 million people die in road crashes each year, on average 3,287 deaths a day as well as an additional 20-50 million are injured or disabled (ASIRT, 2019). ...
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Background: The key factor for breakthrough of autonomous driving is the acceptance of the public. Social media platforms may offer an opportunity to assess public acceptance and opinion towards automated vehicle technology. Methods: Using Twitter Archiving Google Sheet, tweets were collected with the specific hashtags. Tableau and Gephi were used to visualize and aggregate the social media network. By using R Studio, the word frequency, association and sentiment analysis was carried out. Results: The social media network and sentiment analysis provide many new discoveries of public perceptions about autonomous driving. Conclusions: Information from social media can complement data sources and provide direct insights into public intentions. Besides, more complex machine learning technology is needed to gauge changes in public opinion on autonomous driving precisely.
Article
Integrating automated buses (ABs) into the public transport system may have potentials of providing more environment-friendly and cost-efficient mobility solutions by improving travel safety, reducing cost and decreasing congestion. However, the realization of the potentials depends not only on innovative technologies but also on users’ acceptance of the ABs service. Whilst there has been a number of studies exploring the acceptance and adoption of ABs services, hardly any longitudinal studies have analyzed the long-term changes of individuals’ behavior in adopting AB services. This paper aims to add knowledge on user acceptance of ABs in public transport based on empirical evidence in a real-life deployment context. Three waves of surveys that investigated users’ travel attitudes and behaviors towards the automated bus were conducted at three different time points (six months, 11 months, and 14 months after the launch). The relationship between socio-demographic variables, travel experience variables, and attitude variables is modeled using structural equation modelling (SEM). Factors that influence experienced users to continue using the service were found to dynamically change over time. Initially, people were attracted to use the service if they perceived the information of the service to be sufficient, but they were demotivated to continue using the service if the comfort was worse, frequency was lower, or travel time was longer than expected. The results show that previous experience of adopting the ABs has impacts on different attitude variables. In order to promote individuals’ continued use of ABs, the public transport authorities and operators should work closely to increase the frequency of the services. It is also necessary to enhance the comfort of the ABs.
Article
As the widespread usage of autonomous vehicles is closer to becoming a reality, substantial consideration should be paid to the extent to which individuals choose vehicular mobility tools. The purpose of this study is to examine vehicle ownership models to better understand the adoption of vehicles by considering some factors such as liability issues, cost, safety, and environmental characteristics. 323 respondents were recruited from Istanbul, Turkey to complete the stated choice experiment through a web-based survey. Multinomial logit and Heteroskedastic mixed logit models were estimated to unravel users’ preferences concerning the selection of autonomous vehicles with distinction among private, shared, and ride-hailing vehicles. Results indicate that the adoption of those vehicles varied concerning the aforementioned characteristics, and these findings could help decision-makers to develop a vehicular mobility system for future transportation dynamics.
Article
As machines become increasingly intelligent, the HCI community is presented with new challenges regarding methods to capture and understand user experience (UX). In the case of autonomous driving (AD), this involves new scenarios where humans and intelligent vehicles need to act together in real-life traffic situations with other road users. This article responds to this context by 1) outlining a longitudinal design ethnography method whereby participants drove semiautonomous cars in their everyday environments to capture such human-machine relations in real-life settings, 2) demonstrating the complexities of the relations between humans and AD vehicles, 3) engaging theories of socio-materiality and entanglement to understand the human-machine relations of AD cars, and 4) identifying anticipatory experiences that emerge from these relations and their implications for informing UX design.
Article
Full-text available
Fully automated vehicles (AVs) are set to become a reality in future decades and changes are to be expected in user perceptions and behavior. While AV acceptability has been widely studied, changes in human drivers’ behavior and in passengers’ reactions have received less attention. It is not yet possible to ascertain the risk of driver behavioral changes such as overreaction, and the corresponding safety problems, in mixed traffic with partially AVs. Nor has there been proper investigation of the potential unease of car occupants trained for human control, when exposed to automatic maneuvers. The conjecture proposed in this paper is that automation Level 2 vehicles do not induce potentially adverse effects in traditional vehicle drivers’ behavior or in occupants’ reactions, provided that they are indistinguishable from human-driven vehicles. To this end, the paper proposes a Turing approach to test the “humanity” of automation Level 2 vehicles. The proposed test was applied to the results of an experimental campaign carried out in Italy: 546 car passengers were interviewed on board Level 2 cars in which they could not see the driver. They were asked whether a specific driving action (braking, accelerating, lane keeping) had been performed by the human driver or by the automatic on-board software under different traffic conditions (congestion and speed). Estimation results show that in most cases the interviewees were unable to distinguish the Artificial Intelligence (AI) from the human driver by observing random responses with a 95% significance level (proportion of success statistically equal to 50%). However, in the case of moderate braking and lane keeping at >100 km/h and in high traffic congestion, respondents recognized AI control from the human driver above pure chance, with 62–69% correct response rates. These findings, if confirmed in other case studies, could significantly impact on AVs acceptability, also contributing to their design as well as to long-debated ethical questions. AI driving software could be designed and tested for “humanity”, as long as safety is guaranteed, and autonomous cars could be allowed to circulate as long as they cannot be distinguished from human-driven vehicles in recurrent driving conditions.
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With global interest in environmental concerns, the importance of sustainable development has consistently increased. With this trend, the concept of sustainable transportation is an urgent issue in both developed and developing countries. Thus, the current study examines user adoption of sustainable transportation and proposes an integrated model of two theoretical frameworks: the innovation diffusion theory and technology acceptance model. The structural results with 250 respondents in Korea find a sequential connection for users' intention to use, while two main determinants of intention—perceived usefulness and attitude—as well as the roles of their environmental knowledge and perceived compatibility, are also highlighted. Based on these findings, both practical and theoretical implications were presented.
Article
This study synthesizes 91 peer-reviewed survey studies examining the public acceptance of Autonomous Vehicles (AVs). The framework of the study is informed by three questions: (1) How well do the collected samples represent the acceptance of the general population? (2) How often does bias exist in measuring public acceptance in AV’s questionnaires? (3) How much bias persists in reporting public acceptance of AV’s research? The findings indicate that (1) people with disabilities and racial minorities are only included in 10% and 20% of the studies, respectively (2) 50% of the studies present their questionnaire, and most are perceived to be biased as a result of systematic errors such as leading questions, missing questions, and suggestive information, and (3) 72% of the studies suffer from the sentiment bias, where the positive tone in the title and abstract is more significant than in the result. This leads to imprecise findings and unrealistic depictions of acceptance of autonomous vehicles by the public. The analysis alerts researchers and practitioners to empirical evidence of bias in public acceptance of autonomous vehicles and recommends preventive actions.
Chapter
Successful dissemination of a new technology requires broad acceptance in society. This is no different with autonomous vehicles. Despite the benefits that autonomous driving promises to bring with it, many people remain skeptical about letting a computer control a car. In recent years, numerous studies have therefore investigated when, how and why people would (or would not) be willing to make use of autonomous vehicles. This chapter gives an overview of the relevant scientific literature. After a summary of essential theoretical frameworks, the variables that were found by empirical research to predict or correlate with the acceptance of autonomous vehicles are organized into three categories: user-specific determinants (e.g., socio-demographics and personality traits), car-specific determinants (e.g., perceived safety, predictability and appearance), and contextual determinants (e.g., road conditions). Based on this review, limitations of previous work, open research questions and practical implications are discussed, which leads to the ultimate conclusion that the obstacles on the road to autonomous mobility are not merely technical, but also psychological.
Article
This study investigated the effect of perceived usefulness, perceived ease of use, social influence, facilitating conditions, compatibility, and perceived trust on the intention and adoption of electronic wallet (eWallet) among working adults in Malaysia. The cross-sectional research design was adopted to gather quantitative data from 1,156 working adults via Google form link shared across the social media platform. The collected data were analyzed with partial least square structural equation modeling (PLS-SEM) tool using SmartPLS 3.1. The study outcomes revealed that perceived usefulness, perceived ease of use, facilitating conditions, compatibility, and perceived trust displayed significantly positive effect on both the intention to use and the adoption of eWallet. Additionally, the intention to use eWallet mediated the relationships of perceived usefulness, perceived ease of use, social influence, facilitating conditions, compatibility, and perceived trust with adoption to use eWallet. Household income significantly moderated the relationship between compatibility and intention to use eWallet. eWallet service providers and financial development policy making in Malaysia should focus on promoting the application of eWallet to uplift its social influence, besides enhancing consumer security to harness the adoption of eWallet amidst the public. Essentially, the intention-behavior gap needs to be bridged by exploring new factors that can affect the behavior.
Article
Purchase likelihood Unobserved heterogeneity Heterogeneity in means and variances Random parameters logit model A B S T R A C T Determining the likelihood of consumers purchasing automated vehicles (AVs) is extremely important for policymakers, researchers, and automobile manufacturers. Successful penetration of AVs into the market depends on the end-user's perception and their affinity towards these vehicles. In this study, a comprehensive statewide data has been used to determine the factors affecting the purchase likelihood of AVs. A wide range of potential factors are evaluated, including attributes related to safety and consumer's perception, socioeconomic and demographic factors, carsharing and ridesharing habits, types of housing and parking, types of owned and future vehicles, consumers' preferences for buying or leasing a vehicle, and their residential region. A random parameters logit model with three outcomes of consumer's affinity (i.e., agree, neither agree nor disagree, disagree) towards purchasing either partially (Levels 3 and 4) or fully (Level 5) AVs is considered. Moreover, to account for different layers of unobserved heterogeneity and to obtain a better statistical fit, the means and variances of random parameters are allowed to vary across the observations. The estimations results reveal significant differences between the determinants of consumer's affinity towards partially and fully AVs. For partially AVs, the effect of certain variables related to the status of owing hybrid vehicles, education level, parking type, gender, and consumer's opinion about the future of carsharing and ridesharing programs represented significant degrees of heterogeneity. For fully AVs, however, variables related to education level, parking type, housing type, and ethnicity were found to produce random parameters. The findings from this study can be used to estimate AV penetration and promote AV adoption.
Article
Experiments with autonomous vehicles continue to proliferate. And yet, their broader public profile remains low. Commissioned by the French Ministry for Transport, this research examines the image of autonomous vehicles with the public at large. The methodology employed includes a thorough review of the French media discourse, in order to analyse the ways in which autonomous vehicles are presented and perceived in the press and social media. Over 2,600 press articles and 43,000 tweets in French were gathered and analysed in a period stretching from December 2017 to May 2018, supplementing a historical corpus of 2,200 articles appearing in the national press in the period 2012-2017. Analysis of this material yielded quantitative and qualitative information on autonomous vehicles. We attain a statistical description of the dissemination of information relating to autonomous vehicles and a dynamic analysis of the content shining a light on the process by which opinions are formed. The results reveal steadily growing but fluctuating media interest. Peaks correspond to widespread press coverage and substantial interest on Twitter, but never attained the critical mass required to constitute a media-hype. We also observed a significant homogenisation of content at these times. The same sources of information were widely shared. Economic stakeholders are at the centre of discussions, and they are also the principal sources of information. This predominance of the views espoused by private stakeholders shapes the prevalent framing of all of the subjects considered here. It leads us to conclude that autonomous vehicles are yet to achieve the level of general public interest that we associate with real issues of public interest. This point is of particular importance to the government agencies concerned with the deployment of autonomous vehicles and the social acceptability of such technologies.
Thesis
In the era of smart and sustainable cities, autonomous vehicles (AVs) are gaining significant attention from both researchers and local decisionmakers. AVs are expected to significantly shape mobility in the future, which would have a huge impact on urban development. The development of AVs covers not only technological and industrial evolutions but also territorial innovations which are now reaching maturity. Indeed, several experiments are currently being carried out by Tesla and Google. Not far from us, the UTC made the first test with a car traveling with a driver not interacting with the steering wheel or the pedals. This intelligent vehicle or AV is the next innovation in urban transport modifying both the use of private vehicles and the functionality of urban transport. However, to what extent(s) the use of AVs will effectively influence, positively or negatively, urban spaces and sustainable development policies. In this context, and through the example of the Agglomeration of the region of Compiegne (ARC), this thesis work focuses on the integration of AVs into urban space from the point of view of users. Through this prism, this research work will seek to better understand and extract the factors that can influence the adoption of these AVs as a fully-fledged mode of transport, or not, with a view to anticipating their impacts on the urban system. In the absence of normative data on this subject, the construction of an ad-hoc survey is necessary. Hereby, this work is based on an ad-hoc questionnaire administered to the residents of the ARC, concerning their travel habits, their perceptions and their willingness to use the AVs. Using a descriptive quantitative approach, the data collected was used to distinguish and identify different profiles of potential AVs users. Next, a multinomial logistic regression was performed to investigate the relationship between variables associated with acceptance and intention to use VAs in different modes. The results revealed that the sample can be divided into four subgroups of users: i. potential users of private autonomous vehicles(43.7%), ii. potential users of public autonomous transport (24.5%), iii. potential users of shared autonomous vehicles (22%) and iv. non-users of autonomous vehicles (9.8%). Data analysis has shown that confidence in AVs, perceived usefulness and past mobility behaviors significantly influence the adoption of AVs as private, shared or public modes of transport while socio-demographic status influences only the acceptance of autonomous shared and public transport. In general, AVs could improve shared mobility and appear to be able to reduce vehicle ownership and the places dedicated to vehicles. This could lead to major changes in urban areas: less congestion, fewer pollutant emissions and vehicle accidents. In addition, the inclusion of autonomy in the transport system will have a radical impact on the current transport system and on the location of resident populations. This study shows that nearly 30% of the population could change their place of residence with the arrival of AVs. These elements are important data to consider in preparing for the arrival of the AVs in the urban areas.
Article
Automated Vehicles (AVs) will change the transportation landscape in still-uncertain ways. The timeline for this change depends not just on the pace of technological advancement, but also on public attitudes about AVs. These attitudes include perceptions of safety and tolerance of new vehicle ownership structures that will likely emerge when and if fully self-driving models are available. This study aims to determine the extent to which young people are open to using AVs and forgoing ownership of conventional personal vehicles in favor of AV-based shared mobility. With the potential for widespread AV deployment in the near term, the perspectives of this age group are important for understanding the impacts of AVs on the mobility landscape. An online survey was distributed through professional networks across the country in early 2020 to gauge comfort levels in riding in AVs, relying on shared mobility, and owning an AV. Univariate and bivariate chi-square tests were performed to test the correlation between explanatory variables and perceptions of AVs. The responses revealed ambivalence toward AVs. Significant relationships indicate that gender identity and urbanicity matter when it comes to willingness to use AVs and shared mobility. Results also show that young adults may not be as ready for AVs as some have hypothesized. The results of this study help address gaps in AV perception research and gauge current attitudes of young adults toward a future of transportation that includes connected and automated vehicles.
Article
Shared autonomous vehicles (SAVs) are one of the important development directions of smart and green transportation. However, relevant researches are not sufficient at present. The factors influencing the intention to use SAVs and their parking choice behaviors need to be further analyzed. First, in order to better explain, predict, and improve travelers’ intention to use SAVs, the conceptual framework based on technology acceptance model was developed to establish the relationships between the travelers’ intention to use SAVs, social influence of SAVs, attitude toward behavior of SAVs, perceived risk of SAVs, perceived usefulness of SAVs and perceived ease of these use. Then structural equation model (SEM) was established to analyze the relationship between various variables. The results show that the perceived usefulness, behavior attitude, social influence, perceived ease of use, and perceived risk are the main factors that determine the intention to use SAVs. Through the test of direct effect, indirect effect, and total effect in the model, it is found that perceived usefulness has the largest total impact on intention to use SAVs, with a standardized coefficient of 0.765, followed by behavior attitude (0.732), social influence (0.597), perceived ease of use (0.462) and perceived risk of SAVs (−0.452). In addition, through the study of observed indicator variables ATB2 and BI3, it is found that perceived usefulness, perceived ease of use, social influence, perceived risk, attitude toward behavior, and behavior intention all have an impact on parking behavior. In order to study the specific influencing factors of parking choice behavior, a multinomial logit (MNL) model was established to analyze the relationships between travelers’ parking choice behaviors and the influential factors, which include travelers’ individual characteristics, travel attributes, and parking modes’ attributes by extracting from a questionnaire. The results show that the travel time, travel fees, parking charge, cruising fees, parking time and traffic emission are the main factors that determine travelers’ choices of parking. This paper provides advice for operators of SAVs.
Chapter
The trust issue between intelligent system and humans is faced with more complex challenges. As the intelligent systems are gaining more autonomy, new modes and frameworks are required to investigate human-computer interaction in the days to come. This article aims to explore the trust repair strategies of intelligent vehicle system after a traffic accident from the perspective of social cognition, specifically, by comparing the impact of different trust repair strategies including admission and denial, comfort and promise, on the participants’ perceived warmth, perceived competence, trust and intention to use. An online research based on video material with 432 participates in total was conducted. As indicated by the results, trust repair strategies had a significant impact on the perception and attitudes of users. Comforting and apologizing after the accident increased the perceived warmth of participants on the vehicle system. More importantly, their trust and intention to use were supported. Promising to avoid the accident in the future increased the perceived competence, which supported users’ intention to use it indirectly. The trust repair strategy of intelligent vehicle system based on the social cognition theory has a significant influence on the cognition and attitudes of users, which provides not only a new perspective for the relevant practitioners in the field of human-computer interaction but also direct reference for the design of personified and anthropomorphic vehicle system agent.
Article
One of the most notable global transportation trends is the accelerated pace of development in vehicle automation technologies. Uncertainty surrounds the future of automated mobility as there is no clear consensus on potential adoption patterns, ownership versus shared use status, and travel impacts. Adding to this uncertainty is the impact of the COVID-19 pandemic which has triggered profound changes in mobility behaviors as well as accelerated the adoption of new technologies at an unprecedented rate. Accordingly, this study examines the impact of the COVID-19 pandemic on people’s intention to adopt the emerging technology of autonomous vehicles (AVs). Using data from a survey disseminated in June 2020 to 700 respondents in the United States, a difference-in-difference regression is performed to analyze the shift in willingness to use AVs as part of an on-demand mobility service before and during the pandemic. The results reveal that the COVID-19 pandemic had a positive and highly significant impact on the intention to use AVs. This shift is present regardless of tech-savviness, gender, or urban/rural household location. Results indicate that individuals who are younger, politically left-leaning, and frequent users of on-demand modes of travel are expected to be more likely to use AVs once offered. Understanding the systematic segment and attribute variation determining the increase in consideration of AVs is important for policy making, as these effects provide a guide to predicting adoption of AVs—once available—and to identify segments of the population likely to be more resistant to adopting AVs.
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