In this paper we present a review of existing aviation safety metrics and we lay the foundation for our four-years research project entitled “Measuring Safety in Aviation – Developing Metrics for Safety Management Systems”. We reviewed state-of-the-art literature, relevant standards and regulations, and industry practice. We identified that the long-established view on safety as absence of losses has limited the measurement of safety performance to indicators of adverse events (e.g., accident and incident rates). However, taking into account the sparsity of incidents and accidents compared to the amount of aviation operations, and the recent shift from compliance to performance based approach to safety management, the exclusive use of outcomes metrics does not suffice to further improve safety and establish a proactive monitoring of safety performance. Although the academia and aviation industry have recognized the need to use activity indicators for evaluating how safety management processes perform, and various process metrics have been developed, those have not yet become part of safety performance assessment. This is partly attributed to the lack of empirical evidence about the relation between safety proxies and safety outcomes, and the diversity of safety models used to depict safety management processes (i.e. root-cause, epidemiological or systemic models). This, in turn, has resulted to the development of many safety process metrics, which, however, have not been thoroughly tested against the quality criteria referred in literature, such as validity, reliability and practicality.
Inclusive research practices can lead to progress towards an inclusive society. With this study, we aimed to gain insight into dilemmas and catalysing processes within the long-term collaboration of an inclusive research duo: one non-academic researcher who lives with the label of intellectual disabilities and visual impairment, and one academic researcher. Both researchers kept personal diaries about their collaboration process. Inductive thematic analysis, individually and as a group of authors, was employed. Our findings reveal six necessary conditions for diversity-sensitive work in inclusive research: (a) experiencing belonging within the research group, (b) empowering people in a team through growing self-awareness and competence-building, (c) having room for reflection and searching for various ways of communication, (d) sharing power and ownership of research processes, (e) having enough time to foster the above conditions, and (f) joining in a mutual engagement in accommodating vulnerability in dialogue and collaborative work. Awareness of stigma-related issues and the risk of tokenism is also required.
LINK
Although reengineering is strategically advantageous fororganisations in order to keep functional and sustainable, safety must remain apriority and respective efforts need to be maintained. This paper suggeststhe combination of soft system methodology (SSM) and Pareto analysison the scope of safety management performance evaluation, and presents theresults of a survey, which was conducted in order to assess the effectiveness,efficacy and ethicality of the individual components of an organisation’s safetyprogram. The research employed quantitative and qualitative data and ensureda broad representation of functional managers and safety professionals, whocollectively hold the responsibility for planning, implementing and monitoringsafety practices. The results showed that SSM can support the assessment ofsafety management performance by revealing weaknesses of safety initiatives,and Pareto analysis can underwrite the prioritisation of the remedies required.The specific methodology might be adapted by any organisation that requires adeep evaluation of its safety management performance, seeks to uncover themechanisms that affect such performance, and, under limited resources, needsto focus on the most influential deficiencies.
De technische en economische levensduur van auto’s verschilt. Een goed onderhouden auto met dieselmotor uit het bouwjaar 2000 kan technisch perfect functioneren. De economische levensduur van diezelfde auto is echter beperkt bij introductie van strenge milieuzones. Bij de introductie en verplichtstelling van geavanceerde rijtaakondersteunende systemen (ADAS) zien we iets soortgelijks. Hoewel de auto technisch gezien goed functioneert kunnen verouderde software, algorithmes en sensoren leiden tot een beperkte levensduur van de gehele auto. Voorbeelden: - Jeep gehackt: verouderde veiligheidsprotocollen in de software en hardware beperkten de economische levensduur. - Actieve Cruise Control: sensoren/radars van verouderde systemen leiden tot beperkte functionaliteit en gebruikersacceptatie. - Tesla: bij bestaande auto’s worden verouderde sensoren uitgeschakeld waardoor functies uitvallen. In 2019 heeft de EU een verplichting opgelegd aan automobielfabrikanten om 20 nieuwe ADAS in te bouwen in nieuw te ontwikkelen auto’s, ongeacht prijsklasse. De mate waarin deze ADAS de economische levensduur van de auto beperkt is echter nog onvoldoende onderzocht. In deze KIEM wordt dit onderzocht en wordt tevens de parallel getrokken met de mobiele telefonie; beide maken gebruik van moderne sensoren en software. We vergelijken ontwerpeisen van telefoons (levensduur van gemiddeld 2,5 jaar) met de eisen aan moderne ADAS met dezelfde sensoren (levensduur tot 20 jaar). De centrale vraag luidt daarom: Wat is de mogelijke impact van veroudering van ADAS op de economische levensduur van voertuigen en welke lessen kunnen we leren uit de onderliggende ontwerpprincipes van ADAS en Smartphones? De vraag wordt beantwoord door (i) literatuuronderzoek naar de veroudering van ADAS (ii) Interviews met ontwerpers van ADAS, leveranciers van retro-fit systemen en ontwerpers van mobiele telefoons en (iii) vergelijkend rij-onderzoek naar het functioneren van ADAS in auto’s van verschillende leeftijd en prijsklassen.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.