Smart Cities are Not Safe Cities for Drones, Air Taxis, Autonomous Vehicles etc-They Should and Can Be
“Smart City” efforts appear to be significantly behind where they can and should be to ensure safe urban environments for new air and ground services and technology. We seem to be missing end-state system of systems design and implementation due diligence. Whether that is from autonomous air and ground vehicles or those operated by a human. This includes use cases ranging from personal use to deliveries, inspections, ride sharing, air taxis, etc. The puzzling part of this is that unlike creating autonomous vehicles, where machine learning and deep learning are still major challenges, the technology and know-how exist to design and deploy most of what is needed now. Albeit it from a variety of industries. (Which is part of the problem.) The most concerning part is the apparent lack of end-state designs, top-down systems engineering and deployment plans. Including air and ground air traffic control or “AWACS” capabilities. (At least as far as what the community is sharing, especially NASA and the FAA.) This is particularly concerning given how long it will take to design and field solutions given there are already “driverless” vehicles and robots on our streets and in the air now. From ride sharing to delivery drones, air taxis, non-cooperative drones. It seems as if the industry is a bit Pollyanna and not giving nearly enough respect to Murphy. Choosing to follow IT/Silicon Valley “Agile” methods that are often void of systems engineering, exception handling or what if scenarios at a total system level. Complex safety-based systems are not the time or place to “move fast and break things”. (While waterfall users can try to know too much up front, many Agilists ignore too much up front.) One air tragedy or a significant accident on the ground involving a child or family and the whole thing comes to a grinding halt. With an air safety rating of 6.4 sigma a couple years ago, which resulted in no deaths from air travel in the US, to the recent Boeing disaster, seven people around the world killed needlessly by autonomous vehicles to date and trust in the FAA and autonomous systems low, one would think the current approach and posture would be the opposite of what it is. I would like to suggest a way forward to remedy this.
Way Forward — Integrated Air and Ground Domains
(To an air domain UML4 level for both ground and air. This is a complexity factor for thousands of simultaneous operations.)
Create a List of Complex Urban End-state Use Cases and Associated Challenges
· Expected or Desired Use Cases
· What if Scenarios or Exceptions — To include streets and air ways cluttered with a variety of entities both wanted and unwanted. Envision air and ground chaotic operation and chain reactions, especially regarding non-cooperatives. Include natural and man-made issues or disasters. (Include federal cooperation or take over.)
Match Technology to Use Cases — Identify and Resolve Technical Gaps — Examples
· C-V2X 30mhz bandwidth limitations for combined air and ground use (see article below). Many drones and remote operated ground vehicles require sensor data, including video, to operate. Where is this bandwidth coming from long term?
· Current public UAM (Urban Air Mobility) plans assume UTM (UAS Traffic Management) is adequate and do not include independent active object detection and avoidance, like passive and active radar. And assumes all air entities can deconflict on their own.
· There does not seem to be a plan for integrated air and ground situational awareness and command and control. No common operating picture or “AWACS”. (Which will be needed to help resolve C-V2X 30mhz bandwidth issue as well as entity deconfliction.)
Create Integrated Simulated and Real-world Modeling for Development, Testing and Public Awareness
· Digital Twin — Model exact locations and objects to include sensor and 5G/sensor material reflectivity characteristics. This would ensure there is no false confidence in location or operation of these systems, especially in edge cases, to include bad weather. There cannot be communication dead zones from blockages, multi-path or even moving objects like aircraft, buses etc. (The simulation and modeling technology and approaches used should be limited to gaming technology, which is extremely prevalent in the industry. Gaming technology has technical limitations that significantly limits active sensor modeling and real-time operation. (Technology from DoD/aerospace/FAA resolves this. See below.)
· Model dense and chaotic entity movement — Vehicles, people, animals, robots, bikes, birds, drones, aircraft, balloons etc
· Model all spectrum and associated messages with high volume — V2X (J2735), ADS-B telematics, UTM, sensor data etc
Create System of Systems Design and Progressive Implementation Plan — Tailor by Location
· Command, Control, Computers, Communications (C4)
· Infrastructure, Power, Cyber Security
· Use simulation with real-world integration and verification
· Factor in redundancy, outages, hacking etc
· Include right of way, zoning, regulatory, financial, and logistic processes, and timelines
· Include technology and approaches from other industries like DoD (JTDS. AWACS, Link-16, DDS etc)
· Integrate with all local, state, and federal agencies. Include what if scenarios
· Create near and long-term plans
· Fill short term gaps — even if the solution is temporary
· Communicate this to the public — Request public input
The V2X 30mhz Issue should be addressed now with DoD Technology and Approaches
My name is Michael DeKort — I have worked for Lockheed Martin, the US State Department, the US Navy and in IT. This includes Software Engineering Manager for NORAD, a Program Manager for the Aegis Weapon System, C4ISR Systems Engineer for DHS/US Coast Guard and the US State Department Counter-terrorism Team and the US Navy. As well as a Systems Engineer and Project Manager for FAA Level D Flight Simulation. I am currently involved in air and ground autonomous vehicle development and testing, smart city and V2X systems engineering and simulation.