Security and Safety Concerns in Air Taxis: A Systematic Literature Review.

Different from traditional transport systems, such as cars or trains, which are limited by land transit space, flying cars (such as UAS, drones, and air taxis) do not occupy space with traffic. They have a degree of freedom in space and time, smaller displacement, and consequently, less stress for their users. Large companies and researchers around the world are working with different architectures, algorithms, and techniques to test air taxi transport to serve a significant proportion of people safely and autonomously. One of the main issues surrounding the diffusion of air taxis is safety and security, since a simple failure can lead to the loss of high-value assets, loss of the vehicle, and/or injuries to human lives, including fatalities. In this sense, despite significant efforts, the literature is still specific and limited regarding air taxi safety and security. Therefore, this study aimed to carry out an extensive systematic literature review of the main modern advances in techniques, architectures, and research carried out around the world focused on these types of vehicles. More than 210 articles from between 2015 and January 2022 were individually reviewed. In addition, this study also presents gaps that could serve as a direction for future research. As far as the authors are aware, no other study performs this type of review focused on air taxi safety.

Embedded Computation Architectures for Autonomy in Unmanned Aircraft Systems (UAS).

This paper addresses the challenge of embedded computing resources required by future autonomous Unmanned Aircraft Systems (UAS). Based on an analysis of the required onboard functions that will lead to higher levels of autonomy, we look at most common UAS tasks to first propose a classification of UAS tasks considering categories such as flight, navigation, safety, mission and executing entities such as human, offline machine, embedded system. We then analyse how a given combination of tasks can lead to higher levels of autonomy by defining an autonomy level. We link UAS applications, the tasks required by those applications, the autonomy level and the implications on computing resources to achieve that autonomy level. We provide insights on how to define a given autonomy level for a given application based on a number of tasks. Our study relies on the state-of-the-art hardware and software implementations of the most common tasks currently used by UAS, also expected tasks according to the nature of their future missions. We conclude that current computing architectures are unlikely to meet the autonomy requirements of future UAS. Our proposed approach is based on dynamically reconfigurable hardware that offers benefits in computational performance and energy usage. We believe that UAS designers must now consider the embedded system as a masterpiece of the system.

Context/Resource-Aware Mission Planning Based on BNs and Concurrent MDPs for Autonomous UAVs.

This paper presents a scalable approach to model uncertainties within a UAV (Unmanned Aerial Vehicle) embedded mission manager. It proposes a concurrent version of BFM models, which are Bayesian Networks built from FMEA (Failure Mode and Effects Analysis) and used by MDPs (Markov Decision Processes). The models can separately handle different applications during the mission; they consider the context of the mission including external constraints (luminosity, climate, etc.), the health of the UAV (Energy, Sensor) as well as the computing resource availability including CPU (Central Processing Unit) load, FPGA (Field Programmable Gate Array) use and timing performances. The proposed solution integrates the constraints into a mission specification by means of FMEA tables in order to facilitate their specifications by non-experts. Decision-making processes are elaborated following a "just enough" quality management by automatically providing adequate implementation of the embedded applications in order to achieve the mission goals, in the context given by the sensors and the on-board monitors. We illustrate the concurrent BFM approach with a case study of a typical tracking UAV mission. This case also considers a FPGA-SoC (FPGA-System on Chip) platform into consideration and demonstrates the benefits to tune the quality of the embedded applications according to the environmental context.