Safety in Vehicle Platooning: A Systematic Literature Review

Axelsson, Jakob

doi:10.1109/tits.2016.2598873

Cited by 117 publications

(58 citation statements)

References 37 publications

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“…Previous studies have shown that control transition requires a necessary amount of time that varies per driver and per moment (Merat et al 2014), and the level of awareness for the driver is also variable at the moment of control transition (Hjälmdahl, Krupenia, and Thorslund 2017). This poses questions in regard to safety at the point of the transition of control (Axelsson 2017), and also the design of the ADS to allow a driver this time while still maintaining an acceptable level of control. Further consideration can be given to the legislative aspect of where responsibility lies during a control transition and design conditions that may be set by the vehicle approval authority.…”

Section: Transition Of Control In Truck Platooningmentioning

confidence: 99%

A human centric framework for the analysis of automated driving systems based on meaningful human control

Calvert

Heikoop

Mecacci

2019

Theoretical Issues in Ergonomics Science

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The future adoption of automated vehicles poses many challenges, with one of the more important being the preservation of control over vehicles that are no longer (fully) operated by drivers. There is consensus that vehicles should not perform actions that are unacceptable to humans. In this paper, we introduce the concept of Meaningful Human Control (MHC) as a function of a framework of the Automated Driving System (ADS). This framework is constructed through the core components that make up the ADS, primarily considered within the categories of the vehicle and driver. Identification of these components and the chain of control allow traceability of MHC to be performed, and aids vehicle manufacturers, software developers, other vehicle component designers, and vehicle-and driver licensing authorities to address many challenges related to the design and preservation of human control in automated vehicles. Operationalisation of MHC is discussed in the paper including a suggested approach that should aid understanding and the application of the concept. Four application examples are given and recommendations are made in regard to vehicle design, human machine interaction, transition of control, driver training, vehicle approval, and other topics. The framework and presented concept also allow researchers to identify areas to perform more explicit and relevant research and develop models that can be applied to perform projections of future impacts. Relevance to human factors/Relevance to ergonomics theory The preservation of control over vehicles that are no longer (fully) operated by drivers is of major importance and a highly relevant topic in human factors and ergonomics research. This paper introduces the concept of Meaningful Human Control (MHC) as a function of a framework of the Automated Driving System (ADS) to address some of these challenges. The framework is essential for the construction of the theory of MHC and the operationalisation in various field connected to human factors, HMI, automated vehicle software design. This aids vehicle manufacturers, software developers, other vehicle component

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Section: Transition Of Control In Truck Platooningmentioning

confidence: 99%

A human centric framework for the analysis of automated driving systems based on meaningful human control

Calvert

Heikoop

Mecacci

2019

Theoretical Issues in Ergonomics Science

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“…Platooning, Intersections and Safety. Vehicles can opportunistically platoon to improve travel times, road usage, and safely do so [26]. Vehicle platooning on highways has been widely explored [27].…”

Section: A Vehicle-to-vehicle Cooperation and Reasoningmentioning

confidence: 99%

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Loke

2019

IEEE Trans. Intell. Veh.

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The connected automated vehicle has been often touted as a technology that will become pervasive in society in the near future. One can view an automated vehicle as having Artificial Intelligence (AI) capabilities, being able to self-drive, sense its surroundings, recognise objects in its vicinity, and perform reasoning and decision-making. Rather than being stand alone, we examine the need for automated vehicles to cooperate and interact within their socio-cyber-physical environments, including the problems cooperation will solve, but also the issues and challenges. We review current work in cooperation for automated vehicles, based on selected examples from the literature. We conclude noting the need for the ability to behave cooperatively as a form of social-AI capability for automated vehicles, beyond sensing the immediate environment and beyond the underlying networking technology.5 At https://www.sae.org/standardsdev/dsrc/ and in particular the message set dictionary SAE J2735 at https

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“…A specific concept that combines longitudinal and lateral automated driving is a platoon, a group of vehicles that drive closely together in a coordinated automated manner (Bergenhem et al, 2012;Ren & Green, 1994). Platooning of automated vehicles offers advantages compared to manual driving in terms of safety, road capacity, and fuel economy (e.g., Axelsson, 2017;Kunze et al, 2011;Larson, Liang, & Johansson, 2015).…”

Section: Emergence Of Automated Platooningmentioning

confidence: 99%

Effects of mental demands on situation awareness during platooning: A driving simulator study

Heikoop

Winter

Stanton

2018

Transportation Research Part F: Traffic Psychology and Behaviou

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Previous research shows that drivers of automated vehicles are likely to engage in visually demanding tasks, causing impaired situation awareness. How mental task demands affect situation awareness is less clear. In a driving simulator experiment, 33 participants completed three 40-min runs in an automated platoon, each run with a different level of mental task demands. Results showed that high task demands (i.e., performing a 2-back task, a working memory task in which participants had to recall a letter, presented two letters ago) induced high self-reported mental demands (71% on the NASA Task Load Index), while participants reported low levels of self-reported task engagement (measured with the Dundee Stress State Questionnaire) in all three task conditions in comparison to the pre-task measurement. Participants' situation awareness, as measured using a thinkout-loud protocol, was affected by mental task demands, with participants being more involved with the mental task itself (i.e., to remember letters) and less likely to comment on situational features (e.g., car, looking, overtaking) when task demands increased. Furthermore, our results shed light on temporal effects, with heart rate decreasing and self-constructed mental models of automation growing in complexity, with run number. It is concluded that mental task demands reduce situation awareness, and that not only type-of-task, but also time-on-task, should be considered in Human Factors research of automated driving.

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Safety in Vehicle Platooning: A Systematic Literature Review

Abstract: PostprintThis is the accepted version of a paper published in IEEE transactions on intelligent transportation systems (Print). This paper has been peer-reviewed but does not include the final publisher proofcorrections or journal pagination.

Cited by 117 publications

References 37 publications

A human centric framework for the analysis of automated driving systems based on meaningful human control

A human centric framework for the analysis of automated driving systems based on meaningful human control

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Effects of mental demands on situation awareness during platooning: A driving simulator study

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