Advantages of commercial UAS-based services come with the disadvantage of posing third party risk (TPR) to overflown population on the ground. Especially challenging is that the imposed level of ground TPR tends to increase linearly with the density of potential customers of UAS services. This challenge asks for the development of complementary directions in reducing ground TPR. The first direction is to reduce the rate of a UAS crash to the ground. The second direction is to reduce overflying in more densely populated areas by developing risk-aware UAS path planning strategies. The third direction is to develop UAS designs that reduce the product (Formula presented.) in case of a crashing UAS, where (Formula presented.) is the size of the crash impact area on the ground, and (Formula presented.) is the probability of fatality for a person in the crash impact area. Because small UAS accident and incident data are scarce, each of these three developments is in need of predictive models regarding their contribution to ground TPR. Such models have been well developed for UAS crash event rate and risk-aware UAS path planning. The objective of this article is to develop an improved model and assessment method for the product (Formula presented.) In literature, the model development and assessment of the latter two terms is accomplished along separate routes. The objective of this article is to develop an integrated approach. The first step is the development of an integrated model for the product (Formula presented.). The second step is to show that this integrated model can be assessed by conducting dynamical simulations of Finite Element (FE) or Multi-Body System (MBS) models of collision between a UAS and a human body. Application of this novel method is illustrated and compared to existing methods for a DJI Phantom III UAS crashing to the ground.

Technology developments has enabled Unmanned Aircraft System (UAS) to be adopted for various applications, including Urban Air Mobility (UAM) – an air transportation system for passengers and cargo in and around urban environments. The operations of UAS in urban environment inevitably raises concerns about the safety impact of UAS. The operational characteristic of UAS is largely different from the conventional commercial aviation. which brings novel safety issues for which the safety learning process has just started. To address these novel safety issues of UAS operations, it is essential to systematically study them within a formal setting of safety risk assessment. Safety risk assessment involves a process that comprises risk indicators, risk analysis and risk evaluation. In recent years, regulators and researcher have dedicated significant efforts to developing risk assessment for UAS operations. These approaches are largely adopted from safety risk assessment of commercial aviation. However, it is essential to recognize that UAS operations have large differences with commercial aviation. Therefore there remains shortcomings and improvements to be made to the risk assessment of UAS operations. This thesis addresses the further development of risk assessment methods for UAS operations for Urban Air Mobility (UAM). The main risk posed by UAM is third party risk (TPR) posed to people on the ground. Therefore, the focus of this thesis is on improving risk assessment methods for ground TPR. The first study focuses on the TPR indicators for UAS operations. Based on these TPR indicators of commercial aviation, novel TPR indicators and nine separate third party fatality terms are identified. Subsequently, current UAS regulations are evaluated regarding their coverage of these nine third party fatality terms. By doing so, the research provides a more comprehensive understanding of the overall third party risk posed by UAS operations. The second study aims to develop a safety risk assessment method for the novel ground TPR indicators proposed in the first study. To achieve this, a Monte Carlo simulation based risk assessment approach is proposed and applied to a hypothetical UAS urban parcel delivery case. The results show that the proposed annual ground TPR model and indicators provide an accumulated understanding of the risk posed to people on the ground. The non-negligible level of uncertainty in the models adopted highlights the need for further development of more accurate sub models for UAS ground TPR assessment. The third study aims to improve the accuracy of the common ground TPR model, where a key limitation lays in the assumption that the product of impact PoF and size of impact area are independent of each other. To address this, an improved characterization is developed and evaluated using dynamical simulation of MBS model of a UAS impacting a human body. The comparison of the novel approach to existing approaches shows significant advantages of the novel developed approach. The fourth study applies the novel approach developed in the third study to an urban parcel delivery UAS, weighting 15kg, equipped with airbag and parachute. A key motivation is that existing models do not address the risk mitigating effects of equipping a UAS with a combination of airbag and parachute. For the UAS equipped with an airbag Multi Body System (MBS) and Finite Element (FE) models are developed. Subsequently, these models are used to assess ground TPR for different cases with and without airbag and parachute. This analysis show that the method developed in the third study is able to quantify the risk reducing effects of the combination parachute and airbag. The four interrelated series of studies have developed novel insights and methods in Third Party Risk assessment of UAS operations. These novel insights and methods can provide enhanced safety feedback to a UAS design process, and can stimulate further development of UAS regulation.

UAS-based commercial services such as urban parcel delivery are expected to grow in the upcoming years and may lead to a large volume of UAS operations in urban areas. These flights may pose safety risks to persons and property on the ground, which are referred to as third-party risks. Path-planning methods have been developed to generate a nominal flight path for each UAS flight that poses relative low third-party risks by passing over less risky areas, e.g., areas with low-density unsheltered populations. However, it is not clear if risk minimization per flight works well in a commercial UAS operation that involves a large number of annual flights in an urban area. Recently, it has been shown that when using shortest flight path planning, a UAS-based parcel delivery service in an urban area can lead to society-critical third-party risk levels. The aim of this paper is to evaluate the mitigating effect of state-of-the-art risk-aware path planning on these society-critical third-party risk levels. To accomplish this, a third-party risk simulation using the shortest paths is extended with a state-of-the-art risk-aware path-planning method, and the societal effects on third-party risk levels have been assessed and compared to those obtained using shortest paths. The results show that state-of-the-art risk-aware path planning can reduce the total number of fatalities in an area, but at the cost of a critical increase in safety risks for persons living in areas that are favored by a state-of-the-art risk-aware path-planning method.

Commercial aviation distinguishes three indicators for third party risk (TPR): i) Expected number of ground fatalities per aircraft flight hour; ii) Individual risk; and iii) Societal risk. The latter two indicators stem from TPR posed to population by operation of hazardous installations. Literature on TPR of Unmanned Aircraft System (UAS) operations have focused on the development of the first TPR indicator. However the expected increase of commercial UAS operations requires an improved understanding of third party risk (TPR). To support such improvement, this paper extends the existing TPR model for UAS operations with societal and individual risk indicators. The extension is developed both at modelling level and at assessment level. Subsequently the extended approach is applied to a hypothetical UAS based parcel delivery service in the city of Delft. The results obtained for the novel UAS TPR indicators show that this aligns commercial UAS operations with land use policies and standing TPR regulation for airports and hazardous facilities.

The unique capabilities of an Unmanned Aircraft System (UAS) creates opportunities for commercial services. The key question is what is an acceptable level of risk posed to third parties on the ground that have no direct benefit from commercial UAS flights. In literature the common view is that an acceptable level of Third Party Risk (TPR) posed by UAS operations follows from an Equivalent Level Of Safety (ELOS) criterion, which means that per flight hour a UAS should not pose more safety risk to persons on the ground than a commercial aircraft does. However in commercial aviation there are also TPR indicators in use that are directed to accident risk posed by all annual commercial flights to the population around an airport. These population directed indicators find their origin in TPR posed by hazardous installations to its environment. The aim of this paper is to improve the understanding of risk posed to the population by annual UAS-based services through learning from TPR knowledge and regulation for airports and hazardous installations. As main result this paper develops an analytical approach to evaluate the annual risk posed by a commercial UAS-based parcel delivery service in urban and metropolitan areas. The obtained results show that the TPR indicators that stem from hazardous installations and airports provide novel insight regarding TPR of commercial UAS-based service.

Evaluating safety risk posed to third parties on the ground due to UAS impact requires a model of probability of fatality (PoF) for human. For quadrotor UAS, the existing impact models predict remarkably different PoFs. The most pessimistic is the impact model adopted by Range Commanders Council (RCC) while the Blunt Criterion model is far more optimistic. The ASSURE study has assessed the third set of PoF values through conducting controlled drop tests of a DJI Phantom III on a crash dummy; these results differ again. To investigate these discrepancies, this paper employs a numerical impact analysis of UAS collisions on humans. The current paper is the third in a series of studies. The first study developed a MultiBody System (MBS) simulation model of a DJI Phantom III impacting the head of a crash dummy; this MBS model has been validated against the experimental drop test results of ASSURE. The second study conducted simulations with the validated MBS model to systematically show the differences in head and neck injuries if the human dummy is replaced by a validated MBS model of a human body. The aim of the current paper is threefold: i) to extend the latter MBS model to assess injury levels for DJI Phantom III impact on thorax and abdomen; ii) to transform the assessed injury levels for head, thorax and abdomen to PoFs; and iii) to compare the MBS obtained PoFs to those from RCC and Blunt Criteria models. The MBS based results show that variations in the scenario of DJI Phantom III impact on the head significantly affect PoF. These variations are not captured by the RCC or BC model, and neither in the ASSURE measurements. Both for head, thorax and abdomen, in case of comparable impact scenarios, the RCC model tends to over-predicts PoF compared to the MBS model, while the BC model tends to under-predict PoF.

Use of Unmanned Aircraft Systems (UAS) is growing rapidly around the world. Very different types of UAS are used for applications such as aerial photography, inspection, emergency and Urban Air Mobility (UAM), operating in low altitude and urban environment, as well as in high altitude airspace integrated with the conventional air transportation system. As a new airspace user, UAS brings novel safety challenges to the current aviation system. For current aviation the main safety issues concern first and second parties, i.e. lives and property of crew and passengers. In contrast, the main safety concern of UAS operations is third party risk (TPR), i.e. the risk posed to people and properties that have no responsibility for the UAS operation and neither benefit in some way from the UAS operation. In order to ensure the safe operation of UAS, there is a need for an evaluation of safety regulation developments for UAS operations against relevant TPR indicators. The aim of this paper is to identify relevant TPR indicators for UAS operations and to evaluate safety regulations against these TPR indicators. The main finding is that current UAS safety regulations do not consider the accumulation of TPR contributions from many UAS flights per annum over rural or urban populations.