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.

Airline reserve fleet capacity is a wide spread phenomenon and is used to limit the impact of delays on the planned flight schedule. This paper focuses on reserve fleet capacity in the form of standby unscheduled air craft. By means of a Monte Carlo simulation on an existing flight schedule using a rule-based delay mitigation model the effectiveness of reserve fleet capacity is analysed. A method of finding a break even point between fleet size and saved delay costs is proposed and the impact of delay duration on the effectiveness of reserve fleet capacity is analysed. Finally, a com parison is made between grouping reserve fleet capacity into a standby aircraft and spreading the reserve fleet capacity over the flight schedule.

Operations by Unmanned Aircraft Systems (UAS) or ‘drones’ pose third party risks to persons on the ground. The key question is: are these third party risks acceptably low? This thesis evaluates the level of risk posed by a concept UAS surveillance-based operation in the port of Rotterdam, by means of modeling and simulation. In a preceding MSc thesis, a modeling and simulation approach to estimate third party risk posed by drone-based parcel delivery service is researched. This modeling and simulation approach has been extended in quite a number of directions. Firstly, the details of the intended drone-based surveillance operation have been defined in collaboration with the Port of Rotterdam Authority. Secondly, the dynamic model of a quadcopter has been replaced by a dynamic model of a fixed-wing UAS. Thirdly, the influence of wind turbulence on the stochastic deviations of the drone flight have been modeled. Fourthly, for the seaport area a method has been developed for estimating local population densities, rather than using census-based data. These models have been integrated in a Monte Carlo (MC) simulation of the intended surveillance operation in the port of Rotterdam. The outcome of the MC simulations shows that the estimated third party risk level posed per drone flight hour to persons on the ground is about a factor 4 higher than a maximal allowable threshold proposed by the Joint Authorities for Rulemaking of Unmanned Systems (JARUS). The simulation results also show that the shallow glide angle of the fixed-wing UAS proposed for the surveillance operation causes a relatively large crash impact area on the ground, which leads to a relatively large expected number of persons to be hit by a ground crash. As expected, the main contributions to third party risk stem from parts of a surveillance flight that are near the city, not from parts towards the sea. Another interesting finding is that the estimated third party risk level remains the same if wind turbulence induced flight deviations are ignored. The modeling and simulation results developed in this thesis provide useful feedback to the further development of drone-based operations in the port of Rotterdam.

Like any other flying system, Kitepower poses risks to third-parties on the ground. Therefore, in this thesis a safety risk assessment is performed for the system of Kitepower. The research question of this thesis is: Which third-party risks are posed by Kitepower operations and how high are these? Kitepower uses a kite attached to a fixed ground station via a tether to harvest energy. This tether is reeled out by performing crosswind manoeuvres with the kite. The tether is retracted in a situation where the kite is in a gliding configuration with different aerodynamic settings. Therefore, there is a net energy gain between these two modes.

Firstly, a pure hazard brainstorm is performed to identify the hazards of the Kitepower operations. With these hazards four safety-relevant scenarios are constructed. The identified safety-relevant scenarios are: the kite, KCU, and tether fly away; the kite and KCU fly away; the kite flies away; and the complete system slides over the ground. Only the first scenario is modelled in this thesis because the first scenario is the most likely scenario.

The first scenario is modelled by using a model framework that is developed to estimate the third- party risk posed by a drone-based parcel delivery service. This model is adapted to the situation in which the kite, KCU, and tether fly away. A flight path model is used from a preceding MSc thesis. The non-nominal descend model is developed by simulating the forces on the kite. These models have been integrated in a Monte Carlo simulation that simulates the tether failure and subsequent landing of the kite multiple times at the proposed test location in Rutten, the Netherlands.

In the results it is found that the individual risk is the most critical in terms of regulation limits. The operational zone should be enlarged to a radius of 500m in the dominant wind direction at location Rutten to comply with the individual risk limits. The system operations comply with the regulations in terms of collective ground risk. However, it is also observed that the population density and wind conditions have a large impact on the individual risk and collective ground risk. Therefore, these parameters should be adapted if the risk is assessed for new locations. Furthermore, the tether failure rate should be based on operational data and not on the Kitepower expert his assumptions. Lastly, the scenarios that are not analysed yet should be analysed in further research.

Unmanned aircraft system (UAS) is an emerging technology that is now gaining traction around the world. UAS operations are expected to be integrated into very-low-level rural and urban airspace via the enabling of the novel concept of unmanned traffic system (UTM). For such operations to become a reality, one of the major challenges that needs to be overcome is the assessment and, subsequently, mitigation of safety risk posed to third parties on the ground.
Third parties on the ground refer to people or pedestrians that resides within the area of operation but are not involved with the operation. To assess this risk, an approach called third-party risk (TPR) assessment has been developed in many research. Prediction of TPR of UAS operations will allow operators, authorities and stakeholders make well-informed decision on the deployment of UAS operations. If the TPR risk level of the designed operational concept exceeds the acceptable risk level, then risk mitigation can then be applied.
In a typical TPR model, one of the important sub-models is the collision consequence model used to predict probability of fatality (PoF) of human subjected to UAS collision. This sub-component requires a good understanding of human fatality due to inflicted injury by UAS collision which is, at this time of writing, still under-studied.
This thesis addresses the key component of the TPR framework that is the quantification of UAS collision consequence on human on the ground. The central aim of this thesis is to develop a quantitative, model-based collision consequence model of UAS collision on human. To achieve this main aim, a series of interrelated research studies was performed in a systematic way.

In this report we demonstrate the outcomes of the research performed in the Air Transport Safety Institute of the Royal Netherlands Aerospace Centre (NLR). This research project constitutes the MSc Thesis of the writer, towards the graduation of the MSc Aerospace Engineering at Delft University of Technology (Air Transport & Operations). The subject of this project lies in the area of aviation safety and quantitative risk assessment. In specific, the study deals with the safety issue of fuel planning and fuel management in airlines’ operations (Commercial Air Transport). As the air traffic growths rapidly, it is a challenge to keep the current safety levels and further improve them, achieving the EU’s vision safety target, which is less than one accident per ten million flights by 2050. Amongst the various accidents and incidents categories, this project researches the accidents and incidents related to fuel. In specific, we investigate two fuel-related events; the probability that a flight lands with less than the minimum regulated fuel amount (called FRF - Final Reserve Fuel) and the probability of fuel exhaustion. So as to analyse and assess the safety risks, we followed the steps of the TOPAZ methodology. Based on previous research on the subject, an extensive hazards list was created, as well as an agent-based risk model was developed and implemented as a Stochastic Dynamically Coloured Petri Nets (SDCPN) model. The risk model was algorithmically implemented in JAVA programming language, in the direction of conducting Monte Carlo simulations. The first event's (FRF) probabilities were estimated through regular (straightforward) Monte Carlo simulation, whilst for the second (fuel exhaustion) regular Monte Carlo proved to be insufficient. Indeed, fuel exhaustion is a rare event and, consequently, an acceleration method was needed to be implemented. The acceleration method chosen is the Interacting Particle System (IPS). Finally, through the simulations, we estimate the probabilities of these rare events for several operational scenarios. The fuel-related risks were assessed for their acceptability, eventually proving that for all scenarios the risks are either tolerable or acceptable, while also the most prominent safety bottlenecks are identified and analysed.

Remote tower allows the provision of air traffic control to one or more aerodromes from a location that is different than the local tower. As such, the air traffic controller or flight information officer is not required to be in the physical aerodrome tower anymore. There are three types of remote tower operations. First, single remote tower is providing remote tower service to one aerodrome. Second, contingency remote tower is providing only continency air traffic control. Third, multiple remote tower is providing remote tower service to two or more aerodromes. Single remote tower and contingency remote tower have been validated and are currently operational. Multiple remote tower is not operational, therefore a topic of research regarding its feasibility.
Currently, there is no available model looking into multiple remote tower operations. Developing an agent-based model can provide additional insight into the feasibility of this new concept of air traffic operations. It can be also be utilised in safety cases to assess the safety level of multiple remote tower operations. The focus of the MSc. Thesis is to develop an agent-based model for the evaluation of multiple remote tower.

TCAS (Traffic Collision Avoidance System) forms one of the crucial safety pillars in air traffic management. It has been designed to detect near mid-air collisions, provide advisories to the pilot and, ultimately, reduce the incidence of mid-air collisions between aircraft. Increasing traffic demands and the forthcoming use of drones in non-segregated air space poses novel evaluation challenges to TCAS. Important limitations of existing TCAS models are: that their model is specified through their computer code only, that uncertainties are not or only partially captured, and the difficulty in incorporating model changes in interactions with novel airspace users. These findings motivated the development of an agent-based modelling and simulation approach that takes various uncertainties well into account.

The core development consists of a mathematical model of TCAS II specifications according to the internationally accepted operational performance standards of TCAS II and airborne collision avoidance system (ACAS). This model has been completed with other agents and their interactions, has been implemented in MATLAB, and has been validated against EUROCONTROL’s deterministic TCAS simulation model InCAS.

The novel TCAS model considers the following uncertainties: errors in relative position measurements, errors in own rate of climb/descent estimates; variation in pilot response time; probability of reception of an interrogation response; variation in TCAS computation cycle. To assess the effect of these uncertainties on TCAS operations, several air traffic encounter scenarios are considered. For each scenario, rare event Monte Carlo simulations have been conducted. The results of the simulations show that the considered uncertainties may have a significant impact on the safety improvement by TCAS that often deviates from prior expectations. For example, the simulation results show that uncertainties may induce mid-air collisions in scenarios where continuation of the original aircraft flights would not have resulted in a mid-air collision. An overview of the results obtained will be given for current TCAS. In addition it will be explained what this means for future collision avoidance developments.