Match Made in Heaven? Or Hell?: Megacities and Autonomous Systems
Jeremy D. McLain
This article is the latest addition to the U.S. Army TRADOC G2 Mad Scientist Initiative’s Future of Warfare 2030-2050 project at Small Wars Journal.
Military operations in urban environments present many challenges. Paramount is the need to avoid civilian casualties. The urban environment causes communications problems and line-of-sight is severely restricted limiting situational awareness. Adversaries may hide amongst the civilian population and obfuscate logistical support among a network of safe houses and subterranean tunnels. Room-to-room clearing of the urban battlefield is cumbersome and dangerous. To answer these challenges, autonomous systems in a complex city environment would present both opportunities and challenges for U.S. Army units operating in such environments. Over the next decades, technologies will also transform these operating environments.
The U.S. Army Strategic Studies Group came to the conclusion the U.S. Army is unprepared for operating in megacities1. Many fragile megacities occupy key strategic terrain2. Megacities are large cogs within the global economy3. Many cities have low resilience and would destabilize if wracked by a natural disaster. The SSG also states that “in most megacities, fragility and a lack of capacity are the norm.”4 Fragility worsens because governments cannot add infrastructure fast enough for rapid population booms5. Some doctrinal assumptions are flawed. Due to sheer scale, megacities would be impossible to isolate. It represents a new operating environment which requires innovative approaches6.
Lack of good intelligence capabilities in urban environments is a shortcoming7. Cities exhibit emergent non-linear behaviors. Changes cascade through the system with unintended consequences. As each city is different with its own characteristics, the way in which the Army can reach a strategic goal within that city would be different8. Winning the city the ‘wrong way’ may have dire strategic consequences. Adversaries operate in urban areas to negate US advantage. Defenders have many defendable positions from which to engage attacking troops. Cityscapes offer 360 degree battle with restricted movement and persistent risk of ambush9.
However, critical infrastructure nodes could be exploited by an attacker to shape the battlefield10.
Measures of Megacities
Intelligence, and data collection are increasingly critical. Some of these measures can have strategic, operational, or tactical applications. Widely used metrics are density of population, industrial assets, buildings, production, and infrastructure densities11. Dynamism is another measure utilized to measure changes over time of land use, population, and economic outputs12.
Urban planning is playing catch-up to facts on the ground. Absence of land use planning result in non-efficient infrastructure resulting in environmental and public health issues13. Upward of 70% of urbanization in the world is “uncontrolled.” Developing nations must implement urban planning to make their cities more sustainable14.
The socio-economic disparities between rich and poor, and resultant effects, in megacities can be an important strategic metric as it can be a variable to measure the resilience of a city. The poor are underserved and live in slums adding to instability15.
Many megacities are vulnerable to natural disasters which disproportionately affect the poor. Though only 11% of those exposed to disasters, nations with low human development index comprise 53% of deaths due to disasters16. Essential knowledge of the megacity can be used for intelligence purposes. Human and geo-spatial intelligence products and analysis tools will need to have greater capabilities.
Urban Logistics and Transportation Networks
Urban mobility is often cited as the most important infrastructure requirement. However, many cities, suffer unlivable traffic congestion. Innovation in “multi-modal” transportation capabilities is needed as well as innovative business, financial, and technology models17. One model taking root is use of shared services, particularly mobility services such as Uber or Lyft, in which riders hail drivers with smart phones. If self-driving cars were wide-spread within a megacity, congestion would be eliminated, and commute times would be shortened while reducing the quantity of cars. Safety would improve with fewer accidents. Cities could rethink the space now dedicated for roadways and parking while at the same time reducing costs of road infrastructure. If most cars were in shared fleets, travelers would save money by paying by the mile vs. owning the vehicle outright. Mobility for the blind, handicapped, and elderly would be improved18.
Location as a Utility
Geographic Information Systems and fidelity mapping of cities can lead to better decisions about infrastructure and increase efficiency of space use. GIS and satellite imagery track the growth of megacities and their support systems in the country-side19. Better mapping of megaslum areas will make them more livable. For instance, crowdsourcing is being used to map Kibera, in Nairobi and one of Africa’s largest slum areas. Landmarks, facilities, and paths are marked by users on mobile phones. Data is then used to locate new infrastructure like schools or police stations down to street lamps20.
Robots have been in the popular imagination for several centuries. Interest in robots has waxed and waned over the last century as hopes of a bright automated future have been portrayed in science fiction. Robots have revolutionized parts of society, but not the ones expected. Rather than being in the mainstream in homes and public areas, robots have been relegated to the factory floor to increase productivity. Enabled by other technological trends, autonomous systems will become mainstreamed in homes and in the public sphere performing a variety of tasks21. Autonomous systems will impact large swaths of the economy and society. These changes will be for the better, and some will be, as some will argue, for the worse22.
Robots in the Future
There are several enabling trends which will make development of robotics accelerate.
Miniaturization and Sensors
The trend in microchips and other electronics is that components are getting smaller but more capable every year, thus increasing onboard system capabilities23. Much of the progress has been driven by the cell phone industry. Each year, cell phones are lighter and yet packed with more components.
Sensors are getting smaller and more numerous. As sensors get smaller, cheaper, and more numerous, more data will be made available to measure and analyze the world.
Figure 1. Source: Yole Développement via http://www.siliconsemiconductor.net/article/77647-Yole-MEMS-sensor-market-set-to-sky-rocket.php
Artificial Intelligence, Big Data, and Cloud, Broadband, Internet of Things
Due to growing amounts of data and access to cheaper computational power, research in artificial intelligence has grown substantially24, 25. Access to wired and wireless broadband is well established in advanced countries but also getting faster26. The speed of these pipes are essential for advanced autonomous systems. In South Korea, which has the fastest broadband in the world, is planning for 10Gbs speed internet in homes27. Korea and several other nations lead the US in internet speeds28.
In wireless, driven largely from data hungry smartphones, 4G wireless networks have been rolled out with development of 5G networks underway with deployment in 202029. 4G speed is maxed out at 1Gbs while 5G networks will have up to 10Gbs speeds30. With development of devices on the internet-of-things, more data will flow through networks. The internet-of-things is “the internetworking of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.”31 It is connecting everyday objects to the internet to make them “smart.” Examples would be internet-enabled appliances like toasters or light bulbs which the user controls through his smartphone. IoT devices collect data to optimize manufacturing or process systems. Cisco predicts that IoT will increase value for companies by $14.4T in 202232. Big data processing on remote servers (i.e. the Cloud) and increasing bandwidth, combined with internet-of-things creates an ecosystem that enables the “Internet-of-Robots.”33 In fact, Bruce Schneier, a leading computer security expert argues that we are building a giant world-spanning robot.34
Dexterity and Locomotion
Wired journalist, Clive Thompson, makes the point that AI was able to beat the best players in Go, a difficult to master game but has had marginal gains in the hand coordination needed to pick up stones used as pieces. He quotes Siddhartha Srinivasa a robotics researcher at Carnegie Mellon, “Maybe the hardest part is not playing the game but moving the pieces.”35 The National Institute of Standards and Technology or NIST36 has been investing to improve robotics dexterity and manipulation37. Ishikawa Komuro Laboratory has demonstrated robotic hands capable of tying knots, dribbling a ball, and even catching a thrown cell phone in mid-air38. In 2015, DARPA had a competition of robots to complete simple tasks. The tasks proved how difficult it is for robots to interact with the real world39. But it points researchers into research areas to make robots more capable.
Commercial companies are relying more on robots for logistics. They are using automatons for package storage, shipping, handling, and delivery. Amazon and other companies already use automated systems for warehouse management. Amazon acquired a top maker of warehouse robots Kiva Systems in 2012, redubbing it Amazon Robotics in 201540. Amazon is researching the use of drones for fast delivery of packages41. Domino’s Pizza is looking to use drones for pizza delivery.42 Militaries are investigating the use of UAVs/UGVs for battlefield logistics, especially for the dangerous last mile43.
Robots in Warfare
The use of robots in warfare does not come without risks. However, risks are in general, weighted against other risks, and thus no approach is risk-free. In autonomous systems, controllable risk may be taken if systems are utilized in relatively controlled and known environments with many known parameters. When complexity increases, understanding system behavior becomes difficult44. In real-time systems with little human oversight, predictive knowledge of the robot’s behavior under various conditions becomes critical45. The damage a system can do is considered for deployment of any weapon system46. This is also a consideration for autonomous weapons. Damage potential is dependent on the system’s magazine depth, geographic range, its engagement speed, and time it takes for corrective action47. Automated systems are limited by their “brittleness” or lack of adaptability to unanticipated conditions48. Future autonomous systems will be more adaptable but nonetheless have a non-zero susceptibility to programming bugs or failures49. Unintended engagements by lethal automated systems risk incidents of friendly-fire or civilian deaths50.
The DoD has been wrestling with the ethics of autonomous weapons in the last few years. In 2014 Hon. Frank Kendall, then Undersecretary of Defense for Acquisition, Technology and Logistics commissioned a Defense Science Board study exploring the challenges, including ethical, of use of autonomy in military systems51.
The automobile industry is struggling with ramifications of autonomous vehicles. As research funding is being poured into autonomous vehicles, ethical questions are being asked. A posited ethical quandary is the Trolley problem whereby a decision is made between doing nothing and letting an out of control Trolley run over and kill 5 people or taking action to throw a switch to divert it to kill one person52. The dilemma is whether to have engineers program the decision beforehand or let the machines learn to make the decisions themselves. With respect to autonomous vehicles, the vehicle may have to decide to kill either a pedestrian or the car occupants in an unavoidable accident53. Studies find that people want to save the greater amount of lives, but they would not buy for themselves a car which would sacrifice its owner54. Upwards of 90% of fatal accidents are due to human error, numbers of deaths could be decreased substantially if autonomous cars were widely deployed. Wide deployment of autonomous cars would be delayed as most people would not buy self-sacrificing varieties of cars55.
Within the DoD and other agencies, there is debate on how much automation is too much and what system functions, missions, and activities are “appropriate” for semi-automation or automation56.
Figure 2. Source: https://www.wired.com/2016/06/people-want-self-driving-cars-save-lives-especially/
Trends in the commercial information technology sectors will drive down costs for autonomous systems. A shift to in-field production and repair of spares or whole systems via 3D printing will enable the logistical tail of these systems57.
Changes in survivability concepts of unmanned systems would change strategy and tactics. With mass production and technology-sector driven cost/performance deflation, systems can be expendable and used in ways unforeseen with manned systems. Savings in training would be realized58. Unmanned systems would take risks not undertaken by manned missions, while alternative operational concepts may be envisioned trading survivability for swarms of systems59. Persistence is greater for automated systems than for manned, due to human limitations. Automated missions may be extended from hours to days (or weeks in some cases). This is evident for ISR missions, but applies to other mission-types60. Logistics automation would not only enable savings but also enable new logistical concepts. Automation would make personnel available for more challenging missions. Unmanned cargo storage, handling, and transportation of routine supplies (food, ammo, water, etc.) would be fully automated61. Support missions have been envisioned for autonomous systems which include “firefighting, decontamination, contingency base and base camp security, installation security, obstacle construction and breaching, vehicle and personnel search and inspection, mine clearance and neutralization, sophisticated explosive ordnance disposal, casualty extraction and evacuation, and maritime interdiction.”62
For the foreseeable future, the decisions of robots to make lethal engagements will remain in human hands63. However, a case may be made to give autonomy for non-lethal engagement. In fact, the use of autonomous systems makes possible new approaches for tactics and even strategic engagements. An example is a demonstration by NAVAIR in which UGVs and UAVs cooperate to disperse a crowd64.
Communications for unmanned systems are a challenge. Globally accessible high-bandwidth feeds for UXVs are lacking as demand for C4 capabilities grows due to sensor data growth. Interoperability of systems is a challenge because different systems use proprietary solutions. It is expected that adversaries will develop means to disrupt communications posing a problem for unmanned systems65. Solutions may come to alleviate these issues. The military is actively researching pseudo-satellites or “pseudolites.” High-flying UAVs or balloons would act as satellites for rerouting of data traffic if satellites are overburdened or disabled66. Commercial companies are developing internet by satellite. OneWeb is planning on a constellation of approximately 700 satellites to deliver global internet connectivity. The constellation will be operational in 201967. Similar systems are being researched by other companies68.
Advances in navigation are required to enable autonomous systems’ movement in complex environments, such as megacities. Sensors and onboard interpretation of data would be critical for systems to be aware enough to negotiate the environment69. Sense-and-avoid algorithms are important for navigation and research is being done in the automobile industry70.
In the battlefield of 2050, proliferated autonomous systems and other technologies will generate new ways of conducting warfare in all domains71. Erosion of US technical edge will happen as commercial technologies may be used by other state and non-state actors alike72.
In an age of limited defense budgets, future threats could come from US investment in “good enough” technologies to preserve current capabilities precisely when adversaries can take advantage of advances to modernize capabilities to exploit US weaknesses through cyber warfare73.
Autonomous capabilities will be used in ways unforeseen in current thinking. Instead of relegating these machines to niche applications, autonomous systems will feature prominently in future fights74. Future warfare may amount to continuously evolving swarms of autonomous machines of various sizes, missions, and capabilities fighting each other. Miniaturization of components and systems with attendant increase of production and lower per unit cost, will give rise to swarming capabilities75. Autonomous systems may see a decoupling of a nation’s population-size from its military power76. With increasing capabilities and availability of commercial technologies, chances increase of technological surprise77.
Adversary use of unmanned systems will require developments in counter-measure technologies, tactics, and training to defeat adversary systems78. A Defense Science Board report stated that demonstrations of “intelligent robots” are common in universities across the world and up to 50 countries have procured unmanned surveillance drones while the market will increase for the foreseeable future. Threats made from small UAVs are already possible79. In regard to what is called the “third offset,” Bob Work, its chief architect and deputy defense secretary, thinks that in contrast to the first two offsets, the 3rd will be easier to duplicate by near-peer competitors. US advantage would not last as long either80.
The DSB found that the DoD has not given much consideration to counter an adversary’s lethal autonomous systems which are not held to the same stringent Rules of Engagement that US systems would be bound to81. The dynamics that triggered the explosion of unmanned aerial capabilities are happening within ground and sea counterparts. At some “tipping point,” the capability increase with simultaneous performance/cost reduction would portend a similar market explosion within the UGV/USV/UUV markets. Adversaries will take advantage of these trends to outfit themselves with unmanned assets82. Far future implications of autonomous systems are outside the scope of this paper but are illustrative. If taken too far, an autonomous systems arms race could transpire83. In remarks made by Vice Chairman of the Joint Chiefs of Staff Gen. Paul Selva, if a major power goes forward with artificially intelligent weapons development, an arms race would inevitably follow. Autonomous weapons would become the “Kalashnikovs of tomorrow.”84
Bob Work is quoted as having said “China’s investing heavily in robotics and autonomy, and the Russian chief of General Staff, [Valeriy] Gerasimov, recently said….quote, ‘in the near future it is possible a fully robotized unit will be created capable of independently conducting military operations.’” The fear is if both sides get good at cyber and EW (Electronic Warfare) offense, there will be ‘mutually assured disruption’ in which swarms of autonomous weapons will be the only option left85. Bob Work is also quoted “ is the first operational and organizational construct of the Third Offset Strategy, People say, ‘what’s the about? And they say, ‘oh, it’s about AI [ ] and autonomy.’ We say no…. It’s about .”86 In 2014, the U.S. Navy demonstrated swarming capabilities with unmanned swarming boats to protect a larger ship. One sailor was able to manage 13 of the USVs at the same time87.
Megacities and Robotics
Cities will impact robotics technology development which will in turn impact design and working of megacities. Increasing numbers of conurbanizations within the next decades will drive change in the robotics technologies market. An obvious impact of megacities on robotics are the requirements for autonomous cars. The parameters that designers would need to account for would come from interactions of autonomous cars and the environment. The obstacle density and the signals density in megacities create challenges for self-driving cars. However, data created by vehicles on the road and sensors in a “smart city” will undoubtedly create opportunities for reimaging the possible. Navigation and dexterity within a crowded city environment will place stringent requirements on autonomous systems. Urban canyons and city bandwidth saturation will be challenging.
Robots will transform what is possible in the cityscape. They will be used for faster and better construction88. Infrastructure will depend on construction robots as less workers perform these dangerous jobs89. With use of autonomous systems in the staid construction industry90, construction and maintenance will become affordable for cash-strapped localities. Robots will enable sustainable cities via urban gardening and autonomous garbage streams. Farther-out, bee-like robots would collect energy from the environment and push it onto the grid.
Megacities and Subterranean Space
As cities grow in density, supporting subterranean spaces grow. Underground spaces support vital flows of people, materials, energy, and information supporting the city above. In dense sectors, it becomes more economical to build underground rather than horizontally. Estimates are that underground development costs from approximately a third to 5 to 10 times more than surface structures in cities91,92. However, these structures save costs on heating and cooling over their lifecycles. Economists are developing models to understand economics and pricing of underground “real estate.”92 Lack of understanding is hampering coherent policy on underground land. Because land is scarce in the city-sized Singapore, planners must think in 3-dimensions93. Another city that thinks underground is Helsinki which has developed an underground development “master plan” limiting sprawl and saving heat in cold winters94. Underground projects are vital for a megacity’s growth but not without risk. Many projects take decades to complete95.
Because need for subterranean spaces to support the infrastructure of megacities, robotics for underground sensing and effects are expected to increase. Increasing urban density by use of “smart” cities and autonomous logistics may mean underground arteries which move things automatically under and up and down buildings. City flows would be augmented by automation. An example of a “future city” is Song Do in Korea. It features a pipe network into which the residents’ trash is sucked. Thereafter, it is sorted to be recycled, landfilled, or burned. The number of workers needed is only seven96. “Addibot”, a 3D printing bot is being developed by Robert Flitsch to automatically repair street potholes. Some organizations are using “patrolbots” to provide security in lieu of human security guards97.
Humanitarian Assistance/Disaster Relief and Robotics
Research is investigating use of robots for HA/DR missions. Hard requirements have stemmed from disaster relief missions. Robots would have been handy in the Fukushima disaster. Because emergency automated valves depended on energy supplied by emergency generators (which were flooded by the tsunami), the plant was unable to stabilize the reactor cores. Reactor cores melted down and radioactive materials were released into the atmosphere98. Manual valves could have been turned by workers, but radiation levels were too high. Interest has grown for robots for hazardous situations. Inspired by the disaster, DARPA held robot challenges to spur research in more agile robots99.
Despite the amount of support, there’s a while to go before robots are agile enough for challenging disaster environments100.
Logistics and Robotics
More efficient supply chains offer up opportunities for autonomous systems. Supply chains will drive requirements for development of autonomous delivery systems. Sensors and end-effectors would send data to algorithms to eke out every last drop of efficiency. Exact whereabouts of shipments in supply chains would affect strategy and tactics of military units. An early demonstration platform for battlefield logistics is the “Joint Tactical Aerial Resupply Vehicle.”101 The JTARV is essentially a large quadcopter meant to shuttle supplies to troops.
In the civilian world, automated logistics enabled by driverless trucks will change assumptions. Use of driverless trucks will decrease shipping costs by up to 40%102. Currently, truck drivers are allowed to drive at most 11 hours before having to rest. Automated trucks could run 24/7 between maintenance stops. Driverless trucks could lead to rethinking of placement of warehouses which are currently close to population centers due to driver costs103. Warehouses could be placed at cheaper remote locations. Design and configuration of automated warehouses would lead to cost savings as space footprints are smaller104. Goods could be driven at nighttime while people sleep, lessening daytime traffic congestion. While the costs of goods would drop for consumers, the shift to driverless trucks could affect the livelihoods of over a million US truckers (and many more world-wide)105.
Concepts of moving materials through a megacity will be developed in order to minimize traffic effects. Real-time information flows will enable lean but intense supply-chain delivery systems to work in urban environments106.
To enable these flows, mapping them across differing modes of transport would be critical. The logistics capabilities taken for granted in the industrialized world do not exist in many developing world megacities107. he autonomous future will depend on precise location-aware technologies and Geographic Information Systems.
GIS, Location Awareness and Robotics
Autonomous systems that can interact with the world will depend on location-awareness enabling technologies. Autonomous systems will use sensors to create accurate real-time situational awareness of space to feedback for use by other autonomous systems. The Tesla S “remembers” where potholes are and adjusts suspension accordingly108. Such ubiquitous feedback can lead to “just-in-time mapping.” Just-in-Time mapping will make sense in dynamic situations where locations of things may change, such as in a natural disaster. A scenario developed in a National Academies paper illustrates the JIT mapping concept.
“A devastating earthquake, ‘the Big One,’ has hit downtown San Francisco. A huge complex of skyscrapers built on reclaimed land has caved in. It is feared that thousands of people are trapped in the rubble. Emergency personnel have little time in which to rescue them. Although cranes and heavy earthmoving equipment have been put in place with amazing speed, it is not clear how the excavation should proceed. With unstable interior spaces and broken gas and electric lines, it is not clear how to excavate in a way that is fast yet will not further injure survivors. Time is ticking away and with it, hopes for survival. With few options left, the disaster-relief director decides to use an experimental, robot-based, just-in-time three-dimensional (3D) mapping capability that was developed after the September 11, 2001, World Trade Center calamity. Thousands of small mobile robots (“mapants”) burrow into the rubble. Each robot is equipped with location-sensing ability as well as with visual, toxic gas, and other sensors. The key to the speed of the just-in-time mapping application is the enormous parallelism made possible by the huge number of mapants. To conserve energy and to enable communication through the rubble (which has large concentrations of steel), the robots use ad hoc wireless communication to share data with one another and with high-powered computers located outside the rubble. The computers perform planning tasks and assist the mapants with compute-intensive tasks such as image recognition and visualization of the map as it is constructed.” 109
Rubble crawling ‘mapant’ bots could be built like cockroaches having collapsible exoskeletons allowing them to fit in spaces a quarter their height110. Just-in-time mapping capabilities has implications for intelligence gathering robots.
Intelligence Gathering and Robotics
In the future, much intelligence will be gathered from ubiquitous sensors often as part of the internet-of-things but also from specially designed platforms designed for such missions. So called “micro” UAVs could be used to collect intelligence without being noticed111. These intelligence assets may be especially useful when dealing with megacity “no-go” zones.
Megacity Impact on TTPs
The megacity will undoubtedly change CONOPS (Concepts of Operations) and Tactics, Techniques and Procedures. The aforementioned technology trends and interactions will enable different thinking for military engagements. The psychological effects on “outnumbered” soldiers may be daunting. However, better use of unmanned assets and filtering/organizing salient information may overcome this feeling. Technologies will be used in unexpected ways, further amending TTPs112.
CONOPS and TTPs will need to take into account strategy-frustrating unintended consequences. For instance, TTPs would take into account impacts of disrupting flows within the city. Damage or shutting off of water or electricity would have untoward effects on normal people. CONOPS would require subtler methods for engagement against opponent forces. Restraint in damaging vital infrastructure would mitigate resources being used for “break it, you buy it” occupation operations113.
Megacities and Humanitarian Assistance/Disaster Recovery
Megacity planning will emphasize resilience against natural or man-made disasters. Supporting a city struck by a catastrophe proves to be challenging. Strategically, the US and other industrialized nations would save resources in the longer run by encouraging megacities to invest in resiliency measures against disasters in the first place. Industrialized cities located in earthquake zones have been designed for these events. Tokyo, the largest cities in the world, lies on an earthquake zone. Over centuries of enduring earthquakes, Tokyo has adapted and become one of the most resilient areas114.
Cities in developing countries are not as well prepared as Tokyo. The U.S. Army is training for such scenarios. A series of technology demonstrations dubbed ‘Thunderstorm Spiral’ intend to demonstrate technologies meant to help in megacity and subterranean environments during disasters115. Recent disaster events such as hurricanes Katrina (2005) in New Orleans and Sandy in the New York City region have illustrated shortcomings in response capabilities. The Katrina response also illustrated the scale of the disaster logistics burden116. Slum areas are challenging for disaster relief. People already living on the edge are disproportionately impacted by natural disasters. For instance, much effort had to be invested in the aftermath of Haiti’s 2010 earthquake which killed more than 100,000 people117.
Megacities and GIS/local Information
Megacities will impact the possibilities of local data and information. In addition to Geographic Information Systems applications, sense from data from local sensors will be forged by artificial intelligence applications operating in the Cloud. Analysis of local generated social media of a local event will be done in real-time118. Sophisticated algorithms will parse and use the sea of data being captured from the urban area119.
Processing the data in real-time for real-time tactical advantage will be challenging. Precise and rich data will enable efficient, effective, and innovative transactions. Sensors will enable data to be recorded and fed into algorithms to make optimal decisions on land use. Localized data services enable participation of citizens. One application is the “adopt-a-hydrant” program started in Boston. Due to 3 feet of snow in January 2011, hydrants weren’t dug out and could not be located by firefighters. A Code-for-America volunteer created an app Adopt-A-Hydrant whereby local citizens could volunteer to clear hydrants after snowstorms. Many civic-minded apps are being developed to make use of local data120.
The growth of megacities and autonomous systems present opportunities and challenges which will not only shape local regions but will have far-reaching ramifications that shape the future of the world. The US Army will need to adapt to and work with these trends in to keep battlefield advantages against adversaries. Implications for changing the way the Army fights are expected to be profound. Autonomous systems and enabling sensor/data-flow networks will change the way cities organize themselves and solve problems. Smart cities will create opportunities for economies and for reimaging what can be possible. Cities in the developing world may leapfrog industrialized cities by taking advantage of these technological trends. Autonomous systems will enable totally new governmental and commercial services. Automated logistics is one of many possibilities that can impact the day-to-day bustle in a megacity. The U.S. Army needs new perspectives on how to conduct successful autonomous operations within megacities.
1. Harris, M., Dixon, R., Melin, N., Hendrex, D., Russo, R., & Bailey, M. (2014). Megacities and the United States Army: Preparing for a complex and uncertain future. CHIEF OF STAFF OF THE ARMY STRATEGIC STUDIES GROUP ARLINGTON VA. p21.
2. Ibid. p21.
3. Felix, K. M., & Wong, F. D. (2015). The case for megacities. Parameters, 45(1), 19. p24.
4. Harris, M., Dixon, R., Melin, N., Hendrex, D., Russo, R., & Bailey, M. (2014). Megacities and the United States Army: Preparing for a complex and uncertain future. CHIEF OF STAFF OF THE ARMY STRATEGIC STUDIES GROUP ARLINGTON VA. p5.
5. Felix, K. M., & Wong, F. D. (2015). The case for megacities. Parameters, 45(1), 19. p22.
6. Harris, M., Dixon, R., Melin, N., Hendrex, D., Russo, R., & Bailey, M. (2014). Megacities and the United States Army: Preparing for a complex and uncertain future. CHIEF OF STAFF OF THE ARMY STRATEGIC STUDIES GROUP ARLINGTON VA. p8.
7. Ibid. p9
8. Ibid. p10
9. Shunk, D. (2014). Mega cities, ungoverned areas, and the challenge of army urban combat operations in 2030-2040. Journal Article| January, 23(4), 09pm.
10. Felix, K. M., & Wong, F. D. (2015). The case for megacities. Parameters, 45(1), 19. p25.
11. Kötter, T., & Friesecke, F. (2009). Developing urban indicators for managing mega cities. Land Governance in Support of the MDGs: Responding to New Challenges (Washington DC, USA). p4.
12. Ibid. p5
13. Ibid. p5
14. Ibid. p11
15. Ibid. p6
16. Ibid. p6
17. Shannon Bouton, Stefan M. Knupfer, Ivan Mihov, and Steven Swartz - http://www.mckinsey.com/business-functions/sustainability-and-resource-productivity/our-insights/urban-mobility-at-a-tipping-point
19. The Age of MegaCities: A look at ten of the world’s largest cities, showing growth patterns over time.
20. Our Fragile Emerging Megacities: A Focus on Resilience
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46. Ibid. p10.
47. Ibid. p19.
48. Ibid. p12.
49. Ibid. p8.
50. Ibid. p18.
51. Frank Kendall, Undersecretary of Defense for Acquisition, Technology and Logistics, “Terms of Reference – Defense Science 2015 Summer Study on Autonomy,” Memorandum for Chairman, November 17, 2014, 1, www.acq.osd.mil/dsb/tors/TOR-2014-11-17-Summer_Study_2015_on_Autonomy.pdf.
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56. DoD, U. S. (2013). Unmanned systems integrated roadmap: FY2013-2038. Washington, DC, USA. p15-16.
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59. DoD, U. S. (2013). Unmanned systems integrated roadmap: FY2013-2038. Washington, DC, USA. p18
60. Ibid. p23.
61. Ibid. p24-25.
62. Ibid. p24
63. DEPT OF DEF., DIRECTIVE 3000.09, AUTONOMY IN WEAPON SYSTEMS 13–14 (Nov. 2, 2012)
64. Work, R. O., & Brimley, S. (2014). Preparing for war in the robotic age. Center for a New American Security, Washington, DC, Tech. Rep. p29.
65. DoD, U. S. (2013). Unmanned systems integrated roadmap: FY2013-2038. Washington, DC, USA. p40-41.
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69. DoD, U. S. (2013). Unmanned systems integrated roadmap: FY2013-2038. Washington, DC, USA. p87.
70. Ibid. p88.
71. Work, R. O., & Brimley, S. (2014). Preparing for war in the robotic age. Center for a New American Security, Washington, DC, Tech. Rep. p7.
72. Ibid. p17.
73. Ibid. p20.
74. Ibid. p22.
75. Ibid. p26.
76. Ibid. p33.
77. Ibid. p35.
78. DoD, U. S. (2013). Unmanned systems integrated roadmap: FY2013-2038. Washington, DC, USA. p10.
79. Murphy, R., & Shields, J. (2012). The role of autonomy in DoD systems. Defense Science Board Task Force Report. p13.
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82. Murphy, R., & Shields, J. (2012). The role of autonomy in DoD systems. Defense Science Board Task Force Report. p68.
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99. Robots compete in Fukushima-inspired U.S. challenge
100. The DARPA Robotics Challenge Was A Bust
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