A multi-level model on automated vehicle acceptance (MAVA): a review-based study

Abstract

Automated vehicle acceptance (AVA) is a necessary condition for the realisation of higher-level objectives such as improvements in road safety, reductions in traffic congestion and environmental pollution. On the basis of a systematic literature review of 124 empirical studies, the present study proposes MAVA, a multi-level model to predict AVA. It incorporates a process-oriented view on AVA, considering acceptance as the result of a four-stage decision-making process that ranges from the exposure of the individual to automated vehicles (AVs) in Stage 1, the formation of favourable or unfavourable attitudes towards AVs in Stage 2, making the decision to adopt or reject AVs in Stage 3, to the implementation of AVs into practice in Stage 4. MAVA incorporates 28 acceptance factors that represent seven main acceptance classes. The acceptance factors are located at two levels, i.e., micro and meso. Factors at the micro-level constitute individual difference factors (i.e., sociodemographics, personality and travel behaviour). The meso-level captures the exposure of individuals to AVs, instrumental domain-specific, symbolic-affective and moral-normative factors of AVA. The literature review revealed that 6% of the studies investigated the exposure of individuals to AVs (i.e., knowledge and experience). 22% of the studies investigated domain-specific factors (i.e., performance and effort expectancy, safety, facilitating conditions, and service and vehicle characteristics), 4% symbolic-affective factors (i.e., hedonic motivation and social influence), and 12% moral-normative factors (i.e., perceived benefits and risks). Factors related to a person's socio-demographic profile, travel behaviour and personality were investigated by 28%, 15% and 14% of the studies, respectively. We recommend that future studies empirically verify MAVA using longitudinal or experimental studies.

Understanding Autonomous Road Public Transport Acceptance: A Study of Singapore

“…Further analysis suggests that an individual's perception of benefits partially mediates the relationship between the perception of concerns and acceptance. This reflects moral-normative system evaluation between the perception of potential benefits and risk (concerns) in the cognitive process preceding AV acceptance proposed in the recently published Multi-Level Model on Autonomous Vehicle Acceptance, and further suggests the existence of a partial mediation [28]. Individuals who perceive greater levels of benefits arising from the implementation of autonomous road public transport report a correspondingly greater acceptance even after considering their concerns.…”

“…Nevertheless, there remains a need to understand how these perceptions form, the underlying mechanisms with acceptance and eventual adoption, and potential intervention levers for encouraging acceptance and adoption during implementation. A useful guiding framework is the Multi-Level Model on Autonomous Vehicle Acceptance [28]. Future work should also consider conducting similar studies using this framework and include population segments with specific transport requirements (e.g., children, the elderly and people with disability) as their perceptions and acceptance of AVs may differ.…”

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

“…Given the importance of garnering public acceptance towards AVs, much research has been undertaken to examine the components affecting public acceptance of AVs [8,9]. The existing research can be classified into two streams.…”

“…Although previous theoretical studies have enhanced understanding of public acceptance of AVs, relatively fewer studies have analysed the importance of attitude's impact on public acceptance [5,8,18]. In social psychology, attitude is an individual's cognitive and affective assessment of an object, which in this context, refers to AVs.…”

Navigating a fad or the future? Opportunities and limitations in integrating carshare membership and automated vehicle propensity in travel demand forecasting

“…A mix of various types of automated and conventional vehicles and different ownership models may operate in conjunction with other transportation system users (Levine et al 2018;Combs et al 2019). To explore the implications, an AV ownership model (either private ownership or shared 'pass' membership) may be central for forecasts to capture AVs' impacts on the transportation system (El Zarwi, Vij, and Walker 2017;Nordhoff et al 2019). Several initiatives to integrate new technologies in modeling have already suggested a need to more flexibly reflect household travel and location decisions (Ciari, Balmer, and Axhausen 2007;Ciari, Schuessler, and Axhausen 2013;Katoshevski et al 2015).…”