Intention to use a fully automated car: Attitudes and a priori acceptability

Payre, William; Cestac, Julien; Delhomme, Patricia

doi:10.1016/j.trf.2014.04.009

Cited by 549 publications

(314 citation statements)

References 36 publications

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“…The introduction of automated vehicles to road traffic is motivated by several predicted, beneficial outcomes (Maurer, Gerdes, Lenz, & Winner, 2015;Stanton & Young, 1998) such as mitigating the negative effects of routine drives on drivers' health and compensating the negative effects of the predicted increase in passenger traffic by increasing traffic efficiency (Payre, Cestac, & Delhomme, 2014;Roberts, Hodgson, & Dolan, 2011). Beyond that, although advancements in passive and active safety technologies have led to a significant reduction in road accidents (Choi & Ji, 2015), European data, for example, show that 26,000 road fatalities were still reported in the European Union in 2015 (European Commission, 2016).…”

Section: Introductionmentioning

confidence: 99%

Introduction matters: Manipulating trust in automation and reliance in automated driving

2018

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Trust in automation is a key determinant for the adoption of automated systems and their appropriate use. Therefore, it constitutes an essential research area for the introduction of automated vehicles to road traffic. In this study, we investigated the influence of trust promoting (Trust promoted group) and trust lowering (Trust lowered group) introductory information on reported trust, reliance behavior and takeover performance. Forty participants encountered three situations in a 17-minute highway drive in a conditionally automated vehicle (SAE Level 3). Situation 1 and Situation 3 were non-critical situations where a take-over was optional. Situation 2 represented a critical situation where a take-over was necessary to avoid a collision. A non-driving-related task (NDRT) was presented between the situations to record the allocation of visual attention. Participants reporting a higher trust level spent less time looking at the road or instrument cluster and more time looking at the NDRT. The manipulation of introductory information resulted in medium differences in reported trust and influenced participants' reliance behavior. Participants of the Trust promoted group looked less at the road or instrument cluster and more at the NDRT. The odds of participants of the Trust promoted group to overrule the automated driving system in the non-critical situations were 3.65 times (Situation 1) to 5 times (Situation 3) higher. In Situation 2, the Trust promoted group's mean take-over time was extended by 1154 ms and the mean minimum time-to-collision was 933 ms shorter. Six participants from the Trust promoted group compared to no participant of the Trust lowered group collided with the obstacle. The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT. Introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved.

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Section: Introductionmentioning

confidence: 99%

Introduction matters: Manipulating trust in automation and reliance in automated driving

2018

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“…Although recent studies showed that a priori acceptability of CAVs could be likely for many drivers today [26,27] the universal acceptance of such a transition is not guaranteed or certain [15]. Users might need to be convinced.…”

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confidence: 99%

How Can Autonomous and Connected Vehicles, Electromobility, BRT, Hyperloop, Shared Use Mobility and Mobility-As-A-Service Shape Transport Futures for the Context of Smart Cities?

et al. 2017

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Abstract:A smarter transport system that caters for social, economic and environmental sustainability is arguably one of the most critical prerequisites for creating pathways to more livable urban futures. This paper aims to provide a state-of-the-art analysis of a selection of mobility initiatives that may dictate the future of urban transportation and make cities smarter. These are mechanisms either recently introduced with encouraging uptake so far and much greater potential to contribute in a shift to a better transport paradigm or still in an embryonic stage of their development and yet to be embraced as powerful mechanisms that could change travel behaviour norms. Autonomous and connected vehicles are set to revolutionise the urban landscape by allowing machines to take over driving that for over a century has been exclusively a human activity, while electrical vehicles are already helping decarbonising the transport sector. Bus rapid transit has been steadily reinventing and rebranding conventional bus services revitalising the use of the humblest form of public transport, while hyperloop is an entirely new, disruptive, and somewhat provocative, travel mode proposition based on the use of sealed tube systems through which pods could travel free of air resistance with speeds exceeding 1000 km/h. Shared use mobility mechanisms like car-sharing, ride-sharing, ride-sourcing and public bicycles can help establishing a culture for using mobility resources on an as-needed basis, while mobility-as-a-service will take this sharing culture a step further, offering tailored mobility and trip planning packages that could entirely replace the need for privately owned modes of transport.

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“…Audi built an AV having the capability of piloted driving (Payre et al 2014). Using piloted driving feature it can monitor the status of drivers and can avoid collisions caused by impaired driving.…”

Section: • Audimentioning

confidence: 99%

Road collisions avoidance using vehicular cyber-physical systems: a taxonomy and review

Riaz

Niazi

2016

Complex Adapt Syst Model

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Road traffic is known to have its own complex dynamics. One implication of complexity is that road traffic collisions have become an unwelcome but unavoidable part of human life. One of the major causes of collisions is the human factor. While car manufacturers have been focusing on developing feasible solutions for autonomous and semi-autonomous vehicles to replace or assist human drivers, the proposed solutions have been designed only for individual vehicles. The road traffic, however, is an interaction-oriented system including complex flows. Such a system requires a complex systems approach to solving this problem as it involves considering not only pedestrians, road environment, but also road traffic which can include multiple vehicles. Recent research has demonstrated that large-scale autonomous vehicular traffic can be better modeled using a collective approach as proposed in the form of vehicular cyber-physical systems (VCPS) such as given by Li et al. (IEEE Trans Parallel Distrib Syst 23(9):1775–1789, 2012) or Work et al. (Automotive cyber physical systems in the context of human mobility. In: National workshop on high-confidence automotive cyber-physical systems, Troy, MI, 2008). To the best of our knowledge, there is currently no comprehensive review of collision avoidance in the VCPS. In this paper, we present a comprehensive literature review of VCPS from the collision-avoidance perspective. The review includes a careful selection of articles from highly cited sources presented in the form of taxonomy. We also highlight open research problems in this domain.

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Intention to use a fully automated car: Attitudes and a priori acceptability

Cited by 549 publications

References 36 publications

Introduction matters: Manipulating trust in automation and reliance in automated driving

Introduction matters: Manipulating trust in automation and reliance in automated driving

How Can Autonomous and Connected Vehicles, Electromobility, BRT, Hyperloop, Shared Use Mobility and Mobility-As-A-Service Shape Transport Futures for the Context of Smart Cities?

Road collisions avoidance using vehicular cyber-physical systems: a taxonomy and review

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