TY - JOUR
T1 - Transport safety and human factors in the era of automation
T2 - What can transport modes learn from each other?
AU - Papadimitriou, Eleonora
AU - Schneider, Chantal
AU - Aguinaga Tello, Juan
AU - Damen, Wouter
AU - Lomba Vrouenraets, Max
AU - ten Broeke, Annebel
PY - 2020
Y1 - 2020
N2 - One of the main aims of introducing automation in transport is to improve safety by reducing or eliminating human errors; it is often argued however that this may induce new types of errors. There is different level of maturity with automation in different transport modes (road, aviation, maritime and rail), however no systematic research has been conducted on the lessons learned in different sectors, so that they can be exploited for the design of safer automated systems. The aim of this paper is to review the impact of key human factors on the safety of automated transport systems, with focus on relevant experiences from different transport sectors. A systematic literature review is carried out on the following topics: the level of trust in automation – in particular the impact of mis-aligned trust, i.e. mistrust vs overreliance, the resulting impact on operator situation awareness (SA), the implications for takeover control from machine to human, and the role of experience and training on using automated transport systems. The results revealed several areas where experiences from the aviation and road domain can be transferable to other sectors. Experiences from maritime and rail transport, although limited, tend to confirm the general patterns. Remarkably, in the road sector where higher levels of automation are only recently introduced, there are clearer and more quantitative approaches to human factors, while other sectors focus only on mental modes. Other sectors could use similar approaches to define their own context-specific metrics. The paper makes a synthesis of key messages on automation safety in different transport sectors, and presents an assessment of their transferability.
AB - One of the main aims of introducing automation in transport is to improve safety by reducing or eliminating human errors; it is often argued however that this may induce new types of errors. There is different level of maturity with automation in different transport modes (road, aviation, maritime and rail), however no systematic research has been conducted on the lessons learned in different sectors, so that they can be exploited for the design of safer automated systems. The aim of this paper is to review the impact of key human factors on the safety of automated transport systems, with focus on relevant experiences from different transport sectors. A systematic literature review is carried out on the following topics: the level of trust in automation – in particular the impact of mis-aligned trust, i.e. mistrust vs overreliance, the resulting impact on operator situation awareness (SA), the implications for takeover control from machine to human, and the role of experience and training on using automated transport systems. The results revealed several areas where experiences from the aviation and road domain can be transferable to other sectors. Experiences from maritime and rail transport, although limited, tend to confirm the general patterns. Remarkably, in the road sector where higher levels of automation are only recently introduced, there are clearer and more quantitative approaches to human factors, while other sectors focus only on mental modes. Other sectors could use similar approaches to define their own context-specific metrics. The paper makes a synthesis of key messages on automation safety in different transport sectors, and presents an assessment of their transferability.
KW - Aviation
KW - Human factors
KW - Maritime
KW - Rail
KW - Road
KW - Safety
KW - Transport automation
UR - http://www.scopus.com/inward/record.url?scp=85087340285&partnerID=8YFLogxK
U2 - 10.1016/j.aap.2020.105656
DO - 10.1016/j.aap.2020.105656
M3 - Article
AN - SCOPUS:85087340285
SN - 0001-4575
VL - 144
JO - Accident Analysis and Prevention
JF - Accident Analysis and Prevention
M1 - 105656
ER -