The objective of the study described in this paper is to define safety metrics that are based on the effectiveness of risk controls. Service providers define and implement such risk controls in order to prevent hazards developing into an accident. The background of this research is a specific need of the aviation industry where small and medium-sized enterprises lack large amounts of safety-related data to measure and demonstrate their safety performance proactively. The research department of the Aviation Academy has initiated a 4-year study, which will test the possibility to develop new safety indicators that will be able to represent safety levels proactively without the benefit of large data sets. As part of the development of alternative safety metrics, safety performance indicators were defined that are based on the effectiveness of risk controls. ICAO (2013) defines a risk control as “a defence with specific mitigation actions, preventive controls or recovery measures put in place to prevent the realization of a hazard or its escalation into an undesirable consequence”. Examples of risk controls are procedures, education and training, a piece of equipment etc. It is crucial for service providers to determine whether the introduced risk controls are indeed effective in reducing the targeted risk. ICAO (2013) describes the effectiveness of risk control as "the extent to which the risk control reduces or eliminates the safety risks”, but does not provide guidance on how to measure the effectiveness of risk control. In this study, a generic metrics for the effectiveness of risk controls based on their effectiveness was developed. The definition of the indicators allows, for each risk control, derivation of specific indicators based on the generic metrics. The suitability of the metrics will subsequently be tested in pilot studies within the aviation industry.
Literature and industry standards do not mention inclusive guidelines to generate safety recommendations. Following a literature review, we suggest nine design criteria as well as the classification of safety recommendations according to their scope (i.e. organisational context, stakeholders addressed and degree of change) and their focus, the latter corresponding to the type of risk barrier introduced. The design and classification criteria were applied to 625 recommendations published by four aviation investigation agencies. The analysis results suggested sufficient implementation of most of the design criteria. Concerning their scope, the findings showed an emphasis on processes and structures (i.e. lower organisational contexts), adaptations that correspond to medium degree of changes, and local stakeholders. Regarding the focus of the recommendations, non-technical barriers that rely mostly on employees’ interpretation were introduced by the vast majority of safety recommendations. Also, statistically significant differences were detected across investigation authorities and time periods. This study demonstrated how the application of the suggested design and classification frameworks could reveal valuable information about the quality, scope and focus of recommendations. Especially the design criteria could function as a starting point towards the introduction of a common standard to be used at local, national and international levels.
As part of their SMS, aviation service providers are required to develop and maintain the means to verify the safety performance of their organisation and to validate the effectiveness of safety risk controls. Furthermore, service providers must verify the safety performance of their organisation with reference to the safety performance indicators and safety performance targets of the SMS in support of their organisation’s safety objectives. However, SMEs lack sufficient data to set appropriate safety alerts and targets, or to monitor their performance, and no other objective criteria currently exist to measure the safety of their operations. The Aviation Academy of the Amsterdam University of Applied Sciences therefore took the initiative to develop alternative safety performance metrics. Based on a review of the scientific literature and a survey of existing safety metrics, we proposed several alternative safety metrics. After a review by industry and academia, we developed two alternative metrics into tools to help aviation organisations verify the safety performance of their organisations.The AVAV-SMS tool measures three areas within an organisation’s Safety Management System:• Institutionalisation (design and implementation along with time and internal/external process dependencies).• Capability (the extent to which managers have the capability to implement the SMS).• Effectiveness (the extent to which the SMS deliverables add value to the daily tasks of employees).The tool is scalable to the size and complexity of the organisation, which also makes it useful for small and medium-sized enterprises (SMEs). The AVAS-SCP tool also measures three areas in the organisation’s safety culture prerequisites to foster a positive safety culture:• Organisational plans (whether the company has designed/documented each of the safety cultureprerequisites).• Implementation (the extent to which the prerequisites are realised by the managers/supervisors acrossvarious organisational levels).• Perception (the degree to which frontline employees perceive the effects of managers’ actions relatedto safety culture).We field-tested these tools, demonstrating that they have adequate sensitivity to capture gaps between Work-as-Imagined (WaI) and Work-as-Done (WaD) across organisations. Both tools are therefore useful to organisations that want to self-assess their SMS and safety culture prerequisite levels and proceed to comparisons among various functions and levels and/or over time. Our field testing and observations during the turn-around processes of a regional airline confirm that significant differences exist between WaI and WaD. Although these differences may not automatically be detrimental to safety, gaining insight into them is clearly necessary to manage safety. We conceptually developed safety metrics based on the effectiveness of risk controls. However, these could not be fully field-tested within the scope of this research project. We recommend a continuation of research in this direction. We also explored safety metrics based on the scarcity of resources and system complexity. Again, more research is required here to determine whether these provide viable solutions.
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.
Every year the police are confronted with an ever increasing number of complex cases involving missing persons. About 100 people are reported missing every year in the Netherlands, of which, an unknown number become victims of crime, and presumed buried in clandestine graves. Similarly, according to NWVA, several dead animals are also often buried illegally in clandestine graves in farm lands, which may result in the spread of diseases that have significant consequences to other animals and humans in general. Forensic investigators from both the national police (NP) and NWVA are often confronted with a dilemma: speed versus carefulness and precision. However, the current forensic investigation process of identifying and localizing clandestine graves are often labor intensive, time consuming and employ classical techniques, such as walking sticks and dogs (Police), which are not effective. Therefore, there is an urgent request from the forensic investigators to develop a new method to detect and localize clandestine graves quickly, efficiently and effectively. In this project, together with practitioners, knowledge institutes, SMEs and Field labs, practical research will be carried out to devise a new forensic investigation process to identify clandestine graves using an autonomous Crime Scene Investigative (CSI) drone. The new work process will exploit the newly adopted EU-wide drone regulation that relaxes a number of previously imposed flight restrictions. Moreover, it will effectively optimize the available drone and perception technologies in order to achieve the desired functionality, performance and operational safety in detecting/localizing clandestine graves autonomously. The proposed method will be demonstrated and validated in practical operational environments. This project will also make a demonstrable contribution to the renewal of higher professional education. The police and NVWA will be equipped with operating procedures, legislative knowledge, skills and technological expertise needed to effectively and efficiently performed their forensic investigations.
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.
