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Who is in responsible for automated driving? A macro-level insight into automated driving in the United Kingdom using the Risk Management Framework and Social Network Analysis

Who is in responsible for automated driving? A macro-level insight into automated driving in the United Kingdom using the Risk Management Framework and Social Network Analysis
Who is in responsible for automated driving? A macro-level insight into automated driving in the United Kingdom using the Risk Management Framework and Social Network Analysis

To date, vehicle manufacturers have largely been left to their own initiatives when it comes to the design, development and implementation of automated driving features. Whilst this has enabled developments within the field to accelerate at a rapid pace, we are also now beginning to see the negative aspects of automated design (e.g., driver complacency, automation misuse and ethical dilemmas). It is therefore becoming increasingly important to identify systemic aspects that can address some of these Human Factors challenges. This paper applies the principles of the Risk Management Framework to explore the wider systemic issues associated with automated driving in the United Kingdom through the novel application of network metrics. The authors propose a number of recommendations targeted at each level of the Risk Management Framework that seek to shift the power of influence away from vehicle manufacturers and back into the hands of governing bodies.

Driving automation, Network analysis, Risk management framework, Social network analysis
0003-6870
1-9
Banks, Victoria A.
0dbdcad0-c654-4b87-a804-6a7548d0196d
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Plant, Katherine L.
3638555a-f2ca-4539-962c-422686518a78
Banks, Victoria A.
0dbdcad0-c654-4b87-a804-6a7548d0196d
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Plant, Katherine L.
3638555a-f2ca-4539-962c-422686518a78

Banks, Victoria A., Stanton, Neville A. and Plant, Katherine L. (2019) Who is in responsible for automated driving? A macro-level insight into automated driving in the United Kingdom using the Risk Management Framework and Social Network Analysis. Applied Ergonomics, 81, 1-9, [102904]. (doi:10.1016/j.apergo.2019.102904).

Record type: Article

Abstract

To date, vehicle manufacturers have largely been left to their own initiatives when it comes to the design, development and implementation of automated driving features. Whilst this has enabled developments within the field to accelerate at a rapid pace, we are also now beginning to see the negative aspects of automated design (e.g., driver complacency, automation misuse and ethical dilemmas). It is therefore becoming increasingly important to identify systemic aspects that can address some of these Human Factors challenges. This paper applies the principles of the Risk Management Framework to explore the wider systemic issues associated with automated driving in the United Kingdom through the novel application of network metrics. The authors propose a number of recommendations targeted at each level of the Risk Management Framework that seek to shift the power of influence away from vehicle manufacturers and back into the hands of governing bodies.

Full text not available from this repository.

More information

Accepted/In Press date: 19 July 2019
e-pub ahead of print date: 31 July 2019
Published date: 1 November 2019
Keywords: Driving automation, Network analysis, Risk management framework, Social network analysis

Identifiers

Local EPrints ID: 437494
URI: http://eprints.soton.ac.uk/id/eprint/437494
ISSN: 0003-6870
PURE UUID: af09990b-8935-440c-a847-50a6fe91899a
ORCID for Neville A. Stanton: ORCID iD orcid.org/0000-0002-8562-3279
ORCID for Katherine L. Plant: ORCID iD orcid.org/0000-0002-4532-2818

Catalogue record

Date deposited: 31 Jan 2020 17:36
Last modified: 18 Feb 2021 17:14

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