User Acceptance of Autonomous Vehicle Technologies
Summary
User acceptance of autonomous vehicle technologies hinges on a complex interplay of psychological, social and technical factors. Trust in system reliability and safety remains paramount, alongside perceived usefulness in reducing travel time, enhancing comfort and improving accessibility for diverse populations. Concerns over data privacy, cybersecurity and loss of control temper enthusiasm, while individual differences in risk tolerance, demographic background and prior experience shape readiness to adopt. Social influence from peers and media narratives, as well as opportunities for direct interaction with driverless systems, have been shown to bolster positive attitudes. As vehicles progress towards higher levels of automation, clear communication of capabilities and limitations will be critical to shaping realistic expectations and securing public confidence. The global significance of widespread acceptance spans urban planning, environmental impacts and equitable access to mobility services.
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User Acceptance of Autonomous Vehicle Technologies publication trend
The graph below shows the total number of articles in user acceptance of autonomous vehicle technologies across all publications each year (not limited to Nature Index journals).
Technical terms
Perceived usefulness: Belief that using an autonomous vehicle will enhance travel efficiency, safety or convenience.
Perceived ease of use: Degree to which operating an autonomous vehicle is expected to require minimal effort.
Social influence: Extent to which individuals perceive that important others encourage or discourage AV adoption.
Hedonic motivation: Enjoyment or pleasure anticipated from the experience of riding in an autonomous vehicle.
Performance expectancy: Anticipated benefits of automation in terms of reliability, speed or accessibility.
Behavioural intention: Individual’s readiness or plan to use autonomous vehicle technology.
Conditional automation (SAE Level 3): Driving scenario in which the system handles core tasks but may request human intervention when operational limits are reached.
References
- Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries. Transportation Research Part F Traffic Psychology and Behaviour (2020).
- Behavioural intention to use autonomous vehicles: Systematic review and empirical extension. Transportation Research Part C Emerging Technologies (2020).
- Customer Acceptance of Autonomous Vehicles in Travel and Tourism. Journal of Travel Research (2021).
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