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Abstract:
Current means of transportation for daily commuting are reaching their limits during peak travel times, which results in waste of fuel and loss of time and money. A recent study commissioned by the European Union considers a personal aerial transportation system (PATS) as a viable alternative for transportation to and from work. It also acknowledges that developing such a transportation system should not focus on designing a new flying vehicle for personal use, but instead on investigating issues surrounding the implementation of the transportation system itself. This is the aim of European project myCopter: to determine the social and technological aspects needed to set up a transportation system based on personal aerial vehicles (PAVs). The project focuses on three research areas: human-machine interfaces and training, automation technologies, and social acceptance.
Our extended abstract for inclusion in the conference proceedings and our presentation will focus on the achievements during the first 2.5 years of the 4-year project. These include the development of an augmented dynamic model of a PAV with excellent handling qualities that are suitable for training purposes. The training requirements for novice pilots are currently under development. Experimental evaluations on haptic guidance and human-in-the-loop control tasks have allowed us to start implementing a haptic Highway-in-the-Sky display to support novice pilots and to investigate metrics for objectively determining workload using psychophysiological measurements.
Within the project, developments for automation technologies have focused on vision-based algorithms. We have integrated such algorithms in the control and navigation architecture of unmanned aerial vehicles (UAVs). Detecting suitable landing spots from monocular camera images recorded in flight has proven to reliably work off-line, but further work is required to be able to use this approach in real time. Furthermore, we have built multiple low-cost UAVs and equipped them with radar sensors to test collision avoidance strategies in real flight. Such algorithms are currently under development and will take inspiration from crowd simulations.
Finally, using technology assessment methodologies, we have assessed potential markets for PAVs and challenges for its integration into the current transportation system. This will lead to structured discussions on expectations and requirements of potential PAV users.
