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White Paper

Autonomous Cars for Law Enforcement

By

Dr. Robert Finkelstein

President, Robotic Technology Inc.

Office: 301-983-4194

BobF@RoboticTechnologyInc.com

Mr. Rob Davis

Chief Social Scientist, Police Foundation

Office: 202-833-1460

RDavis@PoliceFoundation.org

Purpose

The purpose of this White Paper is to describe the advent of commercially available autonomous

vehicles (e.g., driverless cars, SUVs, vans, and trucks) by 2020 or so, and the potential impact on

law enforcement. Federal, state, and local law enforcement agencies, but especially local police

departments, must examine how best to employ this transformative technology for their

customary operations while developing new policies and procedures. They must take advantage

of the benefits of the technology with their fleets of autonomous police cruisers and other

vehicles.

We provide a scenario example – Walk n’ Roll – of how law enforcement practices will gain

benefits from this emerging technology. We define a higher level of vehicle autonomy (Level 6)

for this type of law enforcement application. While law enforcement will gain enormously in

effectiveness and efficiency from autonomous vehicle technology, so will its adversaries, such as

common criminals and terrorists.

The non-profit Police Foundation is teamed with Robotic Technology Inc. to examine and

address the law enforcement opportunities and issues presented by this technology. A Workshop

is planned for spring 2017 to begin an information exchange with the law enforcement

community. The Police Foundation performed, and subsequently published, a study for the US

Department of Justice examining Unmanned Air Vehicles (UAVs) and law enforcement, so an

autonomous ground vehicle law enforcement project will complement the UAV study. The

Workshop will consist of invited participants, about two-thirds from law enforcement and one-

third from autonomous vehicle developers. Law enforcement will be represented by: ranks from

chiefs to patrol officers; jurisdictions from cities to suburban to rural; and departments from local

to state to federal.

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Introduction: Why Autonomous Cars, Trucks, and Buses?

This is an introduction for those not familiar with the rationale for, and the expected benefits

from, the development of autonomous vehicles.

There are a number of reasons why autonomous (or driverless, or self-driving) cars, trucks,

buses, and other vehicles (let’s just call them autonomous cars) are frantically being developed

by many different companies around the globe, including some that are not traditionally in the

automotive industry, such as Google, Amazon, Uber, and others. After years in which

autonomous technology was mostly favored by the military and ignored by the automotive

industry, the race is on to be the first out with a commercially viable, fully autonomous car.

Technology Imperative: Historically, the technology imperative means that any technology that

is feasible, useful, and profitable will emerge like a weed in a sidewalk crack, no matter the

serious concerns with, or objections to, the technology. Concerns aside (and almost any new

technology has flaws compared with the otherwise inferior technology it is replacing),

autonomous cars promise to be the “next big thing,” the new technology that will unleash

entrepreneurial opportunity and ensuing personal and national wealth. Whatever the perceived

risks, all major auto companies are working feverishly to produce autonomous vehicles; in the

U.S., E.U., and Asia (including China); and many are teamed with high-tech and other non-

automotive firms.

Autonomous cars are a disruptive technology, which will cause major changes in the automotive

industry, with some firms going out of business and new companies emerging. They are also a

transformative technology which will stimulate major changes in society, culture, the

infrastructure, and relationships among individuals. They are also a foundational technology,

leading to ubiquitous autonomous civil and military robots, and manifold applications, over the

ensuing decades.

In addition to the technology imperative, autonomous cars will provide many benefits to

individuals and society at large.

Safety: Safety is a major benefit. Globally there are about 1 million deaths and 50 million

injuries per year due to automotive crashes. In the U.S., six million crashes each year cause

about 35,000 deaths and 3 million injuries costing the economy $250 billion per year, almost all

caused by driver failure, such as errors, distraction, or impairment. Errors include misjudging

distance, speed, and the intention of other drivers. Distraction, which is growing worse, includes

multi-tasking, texting, phoning, grooming, listening to music, watching videos or computer

screens, eating and drinking, and fiddling with controls. Driver impairment includes alcohol,

drugs, sleep-deprivation, vision-impairment, mindless meandering, being lost, and road rage

Affordability: Transport of people and goods will become more affordable because: (1)

autonomous technology, like most new technology, will become less expensive over time with

economies of scale and improvements in the technology; and (2) there will be no human drivers

to pay. Many or most autonomous vehicles may be owned efficiently in fleets by companies or

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municipalities to provide inexpensive ride and transport services: cars, taxis, vans, jitneys, buses,

and trucks. Door-to-door service will provide convenience with low cost.

Freedom: There will be increased freedom and independence for the old, young, infirm, urban-

dwellers, and those who choose not to drive. Parents and caregivers will gain freedom as well,

with no need to constantly drive to schools, play dates, sports activities, or doctor’s

appointments. With inexpensive ride services, the poor will have more freedom of travel and

greater choice where to work and live.

Productivity: Because the transport of goods and people will become much more efficient and

less expensive, individual and national productivity will increase, driving up the GDP and

national wealth. Commuters or longer distance travelers will gain the time during transport for

work, education, entertainment, exercise, or rest. The location of factories or business and

government facilities will be less dependent on conventional transportation convenience.

Infrastructure: The crumbling national transportation infrastructure will improve without major

new investment. The greater efficiency in the movement of autonomous cars means that more

road-lane equivalents will be “created” without the need for more land, asphalt, or construction

costs. There will be greater throughput on narrower lanes due to the increased safety at greater

speeds. There will be fewer, less expensive parking facilities in outlying areas (not prime

locations) with more fleet vehicles constantly, and efficiently, in use. Fewer or no signs and

signals will be needed, even at intersections, with more and safer space for pedestrians and

bicycles. There will be major changes in design and functionality of cities and suburbs.

Entrepreneurship: The advent of autonomous cars will also engender entrepreneurship and new

enterprises related to the unique services provided by the vehicles and the advanced technology

embedded in them. There will be a need for software to provide greater intelligence and more

sophisticated control of the vehicles, and software to enhance the productivity and comfort of its

passengers. Exterior and interior design firms will customize vehicles for specific functionality,

such as serving as a mobile office, entertainment center, or sleeping car. There will be new

forms of vehicle ownership and services provided by vehicle fleet companies, as well as services

provided to households by autonomous vehicles. Major changes in urban and suburban

infrastructure will encourage new start-ups in real estate construction and services. New

enterprise will accompany the emergence of other forms of autonomous robots providing

services in medicine, law, fast food, barbershops, and other otherwise human occupations.

National and Global Economy: The national and global economy will see an increase in

wealth, with savings from previously lost productivity and costs, and an increase in GDP from

new enterprises centered on autonomous vehicle software, hardware, components. There will be

manifold new enterprises, the purpose or function of which cannot be discerned now.

Ur-Technology for Autonomous Robots: The software to provide autonomous intelligence to

vehicles, and the social acceptance of autonomous vehicles, will establish this technology as a

foundational technology for autonomous robots of all kinds for the coming decades.

Autonomous intelligent vehicles have a limited but sufficient domain of knowledge and ability,

e.g., they know how to drive but do not know how to make an omelet or play chess. Their

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success will serve as the basis for developing and evolving autonomous robots into many kinds

for manifold applications, including biomimetic robots, including: humanoid and legged

(chimera and multi-legged); and zoomorphic robots (snakes, lizards, fish, octopuses, primates,

birds, insects, etc.). I predict that humanoid and chimera robots will become sufficiently

physically adept and cognitively capable for many applications by 2030, and that they will be

able to replace humans for most jobs by 2035.

The Long Road to Autonomous Cars

The U.S. military had motivation and a vision to develop and deploy autonomous vehicles on the

battlefield in the early 1980s, and there were a number of projects to demonstrate such systems

with the technology available at the time. In 1990, forward-thinking researchers in the

Department of Defense (DOD) predicted the advent of fully autonomous vehicles by 2020, a

prediction that seems to be on track to be fulfilled.

As early as 1957, some in the automotive industry were contemplating cars that could be

driverless by detecting and following a wire embedded under the road. This concept, which is a

limited form of autonomy, was actually demonstrated in the late 1990s as the Automated

Highway System (AHS). Indeed, specially-equipped cars could follow the wires without being

manually driven. But this was an impractical system, where cars and trucks would be

autonomous only for certain lanes on some roads, requiring ingress and egress with the driver

transitioning from one mode to the other, and the wires would be costly to install and difficult to

maintain.

Between 2003 and 2010 the U.S. DOD sponsored the Intelligent Vehicle Technology Transfer

(IVTT) program, which we initiated and managed, to encourage the automotive industry to

develop and commercialize autonomous vehicles. The advantage to the DOD from

commercially available autonomous vehicles from the automotive industry, instead of the

aerospace industry, would be relatively inexpensive vehicles and technology that could be

modified for military applications.

The Defense Advanced Research Projects Agency (DARPA) then sponsored the Grand

Challenge (2004-2005) and Urban Grand Challenge (2007) to encourage development of

autonomous vehicles. The competitions were successful in demonstrating the ability of

autonomous cars, which were modified stock cars, for cross-country and urban environments.

DARPA then sponsored the autonomous humanoid robot challenge (2015), which demonstrated

a rudimentary ability of humanoid robots to serve as first responders in search and rescue

operations.

Technology Forecasting

The playwright Eugene Ionesco said “You can only predict things after they’ve happened.” He

was largely correct. Technology forecasting can be reasonably accurate in the near-term, but the

crystal ball becomes cloudy for the far-term. In general, first order impacts of a technology

usually involve linear extrapolation: for example, the new technology may be faster, better, and

cheaper than the old. But the main caveat is that a new technology is often not universally better

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than the one it replaces, lacking in certain benefits or introducing new disadvantages, such as

higher cost or lower reliability. The second and third order impacts of a new technology are

usually non-linear, take place further in the future, and more difficult to forecast.

For example, consider the automobile in the early 1900s. The horseless carriage was faster than

the horse, or the horse and buggy, did not require food or generate manure to be shoveled, and

did not need a blacksmith or veterinarian. But in the early stages of the technology there were

many disadvantages. The horse could autonomously take a drunken rider home, or

autonomously avoid running into a tree. The horseless carriage was unreliable, difficult to start,

had insufficient infrastructure (e.g., suitable roads, sources of gasoline and spare parts) and was

relatively expensive. But the technology gradually improved and became less expensive.

Subsequent second order changes included the rise of new industries for the production of the

automobile and its components, such as tires; the oil and gas industry; and road and bridge

construction. Social changes included the need for new clothing designs for better

accommodation with the cars; the rise of the suburbs, suburban shopping and lifestyle,

engendered by the ability to commute; new family dynamics, with the rise of the teen culture

centered on the car and the increased freedom and ease of sex in cars; increased family wealth;

and new mobility for wives and daughters.

Decades later, third order geopolitical changes emerged, including oil cartels and foreign policy

centered on the need for oil and gas; religious and tribal conflict and wars ensuing from oil

wealth in otherwise third-world nations; and environmental degradation and climate change due

in large measure from pollution from the internal combustion engine.

Who in 1917 for example, could forecast these second and third order effects?

Prognostication: In the Next Six Years

My near-term prognostication for the law enforcement impact of autonomous cars, vans, and

trucks is that within the next six years they will be available for purchase, lease, service – or theft

and hacking. Criminals and terrorists will love and use commercially available autonomous

vehicles. Criminals will quickly develop creative tactics for using autonomous vehicles to

commit crimes. Terrorists, without being suicidal, could use autonomous vehicles to carry

weapon of mass destruction (WMD) payloads for autonomous deployment; or the autonomous

vehicle itself (especially a truck) could be deployed as a WMD to run over and kill dozens of

pedestrians.

On the other hand, a few law enforcement agencies will start deploying autonomous vehicles as

relatively inexpensive but very effective tools to supplement officers on foot, horses, or bicycles,

or in patrol cars. Consequently, new law enforcement policies and procedures, strategies and

tactics, will be needed to optimize these operations, achieve public acceptance, and avoid

adverse consequences, along with new countermeasures to prevent and counter crime and

terrorism involving autonomous vehicles.

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Autonomous Vehicles Characteristics Beneficial for Law Enforcement

Autonomous vehicles for law enforcement can be designed to accommodate passengers (e.g.,

officers or arrested suspects) or to serve solely as robotic vehicles. In the latter case, there is no

need to encase and protect humans, so the vehicles can be smaller, lighter, more maneuverable,

faster, and expendable as needed. Conventional sized autonomous patrol cars could carry

officers who need not concentrate on driving and so would be better and more safely able to

focus on the neighborhood – or, as needed, patrol themselves without an officer onboard.

Without the cost of human officers, autonomous vehicles, as mobile sensor platforms, can patrol

or provide surveillance without needing to eat, rest, or sleep. Low operating costs mean that

large numbers of autonomous vehicles can be deployed to patrol high-crime areas or prevent

terrorist attacks. They can be supervised from a control center or manned patrol cars, with one

operator supervising many vehicles. They can be equipped so that the human supervisor can

communicate as needed directly with citizens via microphones and speakers affixed to the

vehicle. The vehicles might also autonomously communicate, with natural language and human-

like dialogue, with officers or the public who are outside of the vehicle. As trust is earned,

eventually the autonomous law enforcement vehicles could be equipped with non-lethal or lethal

weapons without unduly risking innocent casualties. As first responders, they could operate

safely in the presence of WMD: chemical, biological, radiological, or nuclear (CBRN) threats.

Smaller autonomous robotic vehicles (similar to EOD robots) could be deployed from larger

vehicles (mother-ships) to patrol on sidewalks, enter buildings, climb stairs, or summon elevators

(with humanoid robots available by 2035). The fleet of autonomous law enforcement vehicles

could be designed to share sensory perception and decision-making among themselves, with

human monitoring.

Example Scenario: Criminals

Autonomous vehicles will make possible new kinds of crimes and criminals, like the Internet

did. For example, criminals could use autonomous vehicles to perpetrate conventional crimes

(e.g., jewelry store robbery) more efficiently and effectively, or create new classes of crime. For

a jewelry store robbery, no get-away driver would be needed. The autonomous vehicle could

position itself as instructed, or arrive at a specified location at a specified time or, with software

modification, itself serve as a look-out. The vehicle could select the fastest or most evasive route

for the get-away and drive at maximum speed while avoiding crashes. Other autonomous

vehicles could be deployed before or during the robbery to block law enforcement access to the

area by causing traffic jams or physically blocking streets. An autonomous vehicle could be

used as a mule to carry the stolen goods surreptitiously to a rendezvous destination while the

thieves go elsewhere in different vehicle. Transformative technology engenders transformative

crime.

Example Scenario: Terrorists

My preferred definition of terrorism is: violence or the threat of violence intended to influence an

audience. The terrorist can be a lone true believer, a member of a group, or a mentally ill mass

murderer making a deranged statement or seeking fame from the act. Autonomous vehicles will

enable terrorists to be more efficient and effective without being suicidal.

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The autonomous vehicle itself can be a Weapon of Mass Destruction (WMD). During the

celebration of Bastille Day on 14 July 16, in Nice, France, a Tunisian resident of France drove

large truck into a celebrating crowd killing 86 people and injuring 434; the carnage finally

stopped when the driver was shot to death by police. What if there were no driver to be shot?

My preferred definition of WMD: a weapon of mass destruction is a chemical, biological,

radiological, nuclear (CBRN), or other weapon that can kill and bring significant harm to a large

number of humans or cause great damage to human-made structures (e.g. buildings, bridges, or

entire cities), natural structures (e.g. reservoirs or mountains), or the biosphere (e.g., farms or

forests). WMD are defined in US law (18 USC §2332a) as:

(1) Any explosive, incendiary, or poison gas, including the following: a bomb; grenade; rocket

having an explosive or incendiary charge of more than four ounces; missile having an explosive

or incendiary charge of more than one-quarter ounce; mine; or device similar to any of the

previously described devices;

(2) Any weapons that is designed or intend to cause death or serious bodily injury through the

release, dissemination, or impact of toxic or poisonous chemicals, or their precursors;

(3) Any weapon involving a disease organism;

(4) Any weapon that is designed to release radiation or radioactivity at a level dangerous to

human life

Autonomous vehicles (cars, vans, trucks, buses, or new types of vehicles) are ideal for the

dissemination of CBRN or other weapons (e.g., munitions, electromagnetic pulses (EMP), etc.)

which can cause mass casualties or infrastructure damage, especially in cities. How can they be

detected and stopped?

Potential Countermeasures

The threat is just a few years away. It must be analyzed now, along with prospective

countermeasures, some of which may take years to devise, verify, validate, test, and implement.

I believe that countermeasures to (commercial) autonomous vehicle threats can be configured

like concentric barriers. The first defense could be vetted sales. Prospective autonomous vehicle

customers already undergo credit checks, while weapons buyers and airplane passengers endure

background checks. Autonomous vehicle buyers and users (which will mean, eventually, all

automotive buyers and users) could also be subjected to security vetting, with a no-buy or no-use

list like a no-fly list. This could filter out some of the threat.

The second defense barrier could be vehicle tracking. Many vehicles, such as those with “May-

Day” safety or theft recovery systems (GPS linked to a tracking center) are already being tracked

24/7 with the permission of the user (who typically pays a fee for the service). All autonomous

vehicle could be tracked, with their positions always known at a control center. The vehicles

could be designed so that any interference with the tracking system would cause the vehicle to

become inoperable.

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A third defensive barrier would require a periodic or continuous “handshake” between the

vehicle and a control center. This would ensure maintaining required connectivity with the

control center for updates about threats and the ability of the control center to disable the vehicle

if required. The system must be as hacker-proof as possible, and respond to tampering with a

default or intentional shut-off.

The final barrier would be the use of nonlethal weapons, such as electromagnetic pulses or nets,

or lethal weapons, such as conventional munitions or high-energy lasers, to stop threat –

assuming the location of the threat was known.

There is also a threat from autonomous vehicles that are home-made (not commercially

manufactured and purchased from a dealer), or those manufactured or imported illegally, without

integrated safeguards. If an autonomous vehicle were observed driving about, and it was not

emitting the appropriate “handshake” signal, for example, that would in itself indicate a threat.

As conventional vehicles are junked over a decade or two, there will be fewer opportunities for

home-made automotive autonomous conversions, but the problem will remain in the near-term.

Example Concept: Walk n’ Roll

The Walk n’ Roll concept is one of the many (but an important) prospective roles for

autonomous vehicles in law enforcement. Patrol, whether by foot, bicycle, horse, or car, is a

fundamental police function, especially for community oriented policing. Patrolling on foot is

generally considered the best approach for community policing, but it has inherent inefficiencies.

Autonomous patrol cars will greatly increase the efficiency and effectiveness of foot patrols with

which they are teamed, while enhancing the focus on the community.

Background

The word “beat” meaning “police patrol” originated in 18th century London when the first police

patrols were on the Thames River in row boats in order to protect the dockyards. A coxswain

called the “beat” for the rowing stroke at 1.5 knots (about 1.2 mph), which later was deemed a

suitable walking speed or “beat” when foot patrols where instituted so the patrol officer could

have an opportunity to interact with the residents..

Patrol is at the core of policing. Foot patrol provides the most interaction between the police and

the community, and between the people of the community and the criminal justice system.

Patrol officers can provide the majority of police services to the community. Patrol offers the

best opportunity to establish personal bonds in the neighborhood, strengthen relationships,

improve the quality of life in the neighborhood, and elicit cooperation between officers and

people in the community. The officers, no longer ensconced in their cars, know the local

troublemakers, and neighborhood residents are more willing to help them solve crimes. The

community feels safer. For example, New Haven, CT replaced many of its cruiser patrols with

foot patrols and serious crime (e.g., robberies, car thefts, and homicides) immediately fell by

30% (albeit the statistical correlation between foot patrols and reduced crime is not yet

established). An academic study of foot patrols in Philadelphia showed their ability to prevent

violent crime. Over time, foot patrol officers can establish strong relationships from daily

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friendly interactions with neighborhood residents who become valuable sources of information

and assist in preventing or solving violent crime.

Unfortunately, patrol is usually considered an undesirable assignment reserved for new and

lower ranking officers. Thus one of the most important police functions may in practice be

carried out by those with least experience or finding it professionally undesirable. An

experienced foot patrol officer who knows his or her beat and the folks in the neighborhood –

merchants, tenants, families, elderly, juveniles, and minor and major offenders – is a valuable

asset to the force. It is unlikely that departments will promote downwards, with higher-ranking

experienced officers doing the important duty of foot patrols. But autonomous vehicles, as we

will describe, may be able to enhance the performance of an inexperienced rookie officer.

Patrols distribute officers geographically over the city, making them more readily available when

needed. The visibility of patrol officers is also intended to deter crime and make the public feel

safer. Because car patrol is more efficient than foot patrol, covering greater area and responding

more quickly to incidents, more than 80% of patrols are in cars. This has resulted in a loss of

personal contact with the people in the community and a consequent loss of public respect and

trust. Also, foot patrols do not seem feasible or justified in spread-out rural and suburban

jurisdictions. It may be beneficial for suburban tracts or rural towns, which are not immune from

crime or distrust of the police, to have the hybrid walk n’ roll patrol system made possible by

autonomous cruisers.

A disadvantage of foot patrol, as noted by one foot patrol officer, is the reduced ability to

monitor driving infractions and catch dangerous drivers. This problem will be alleviated by the

autonomous patrol car. The autonomous cruiser can also augment an essential practice of good

patrol officers who create a journal of people in their neighborhood beat. They record and

update information, for example, on elderly residents with special needs, or shopkeepers subject

to petty theft, or those who have past criminal histories or active warrants, or those who tend to

loiter on the corner.

Thus there has been some return to policing with foot patrols as a result of rising tensions in

some communities, with improvement to the relationship between the police and residents. But

the area covered by an officer on foot is much less, leading to greater costs to maintain

comparable coverage. On the other hand, some efficiency is recovered by assigning one, rather

than two, officers to a patrol. There is generally only a slight increase in risk for a single officer

patrol and productivity (e.g., number of arrests and response time to calls) can be high.

Productivity, however, depends on how the officer patrols and is managed, e.g., whether the

officer is proactive or reactive, the expectations and management style of the patrol sergeant, and

the policing culture of the department. Efficiency and effectiveness also depend on technology

introduced in the past, present, and future, such as communications, video, and autonomous

patrol cars.

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Walk n’ Roll Description

The Walk n’ Roll police patrol concept is to team the foot patrol officer with an autonomous

patrol car “partner.” It combines the community policing benefits of foot patrol with the

efficiency advantages of cruiser patrol.

In operation, the foot patrol officer would be accompanied on the beat by his or her autonomous

cruiser. Ideally the vehicle could follow the officer through the neighborhood at walking speed,

if the streets and traffic patterns permit. Otherwise the vehicle would park at curbside on a block

being patrolled by the officer, then drive itself to the next block as the officer progresses along

on the beat. The officer can summon and enter the vehicle at any time to use the onboard

computer to access information, communicate privately, take a break, ride in the vehicle while

responding to a service call, transport a suspect, or commute between the beat and the precinct

house.

The autonomous police patrol vehicle will be equipped with additional hardware and software,

including sensors, processors, and communications links to a cloud containing law enforcement

databases and software, including machine intelligence software. While teamed with a foot

patrol officer, and accompany the officer on the beat, the autonomous vehicle will perform many

transformative functions to assist the officer and enhance effectiveness and efficiency, e.g.:

Provide immediate autonomous transport as needed for the officer, victims, or suspects.

Autonomously drive the officer while the officer is busy with the computer, surveillance,

or communications, thereby avoiding accidents caused by a distracted officer manually

driving (not an uncommon event).

Perform constant 360-degree surveillance for situational awareness while the officer is

otherwise engaged on the block during foot patrol, especially scanning across the street

and behind the officer. It will provide the officer with the proverbial eyes in the back of

the head. The vehicle will be able to perform facial and vehicle recognition, especially

for neighborhood residents. It will detect anomalies, such as a broken window or

someone lurking in a doorway at night. It will detect traffic violations, such as speeding

or weaving in traffic.

Communicate in natural language with the officer and headquarters, reporting suspicious

anomalies or violations as they are observed. In addition to providing situational

awareness of the immediate area, it will offer the officer database-derived information or

explanatory analyses on request. The vehicle could also assist an inexperienced officer in

a difficult situation with guidance from experienced patrol officers as encoded in an

artificial intelligence expert system.

Communicate directly with the public in natural language (whether English, Spanish, or

any other languages needed for the residents of the neighborhood). The communications

might consist of a friendly greeting, where the vehicle recognizes the neighborhood

resident and remembers previous conversations (e.g., “Hi Sam, how are you, and how is

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your wife Susan feeling? Is she over her cold?”). Or the vehicle might issue a friendly

warning (“Hey Phil, there’s a $50 fine for littering. Please pick up your trash now so I

don’t have to give you a summons). Or the resident might have something to say or

report to the vehicle. It might seem strange at first to engage in conversation with a

police car, but people have become accustomed to talking to Siri, once no less bizarre, all

the time. The car could ask the officer to speak with the resident, if necessary, with the

vehicle translating as needed.

Respond autonomously to a call for service elsewhere or to pursue a speeding or wanted

car, for example, while the officer remains on the beat, if appropriate.

Maintain detailed daily records for the officer of all beat interactions and anomalous

observations, analyze the records, and provide summary reports to the officer (who could

modify the reports as needed).

Allow for (intermittent) foot patrols in suburban areas and rural towns where it would

improve policing. For example, there are burglaries, vandalism, and more serious crimes

in suburban areas and neighborhoods where patrols could serve as a preventive measure.

The autonomous vehicle would follow the officer and be available at a moment’s notice

when needed. Or the patrols might be split, with an officer on foot and the autonomous

cruiser covering different sections of a housing development where there have been

burglaries or vandalism, for example. The cruiser could be summoned by the officer

almost instantly, if required.

Serve as a sort of roving neighborhood police station – allowing residents to interact with

the police department to report crimes or neighborhood concerns. It could be used to

conduct field interviews by the remotely located police staff or transport victims to the

nearest precinct or hospital.

Provide safety for officers in pursuits and when vehicles are used as weapons against

officers.

The Philadelphia, PA, police department published a list of nearly 50 strategies for foot patrol

officers. Many of them would benefit the officer being teamed with an autonomous car:

“Study the criminal histories of those living in your beats; know their names and faces”:

as previously discussed, the autonomous cruiser would maintain a detailed beat log, have

access to massive databases, and recognize individuals.

“Not everyone is your enemy”: The autonomous cruiser could interact with neighborhood

folks in a friendly manner without inherent or acquired biases or preconceived

expectations.

“Become an expert of city services so you can direct citizens to appropriate agencies”:

The autonomous cruiser would have instant access to, and expertise about, city services,

and be able to communicate the information to neighborhood residents directly or via the

patrol officer.

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“Make it appear you are everywhere by consistently walking and being seen:” the team of

foot patrol officer and autonomous cruiser would seem ubiquitous – and authoritative –

by residents.

“Keep beat integrity; only veer off if you feel it is absolutely necessary, and then, only a

block or two:” the autonomous cruiser would cover the beat for the officer as needed.

“If there is heavy radio traffic, have patrol cars stop by to run persons/vehicles:” the

autonomous car would already be available for that and manifold other assignments.

Levels of Autonomy

An autonomous police cruiser will need autonomous capabilities beyond that of safely driving

itself a city. It will need a knowledgebase with information about many topics other than

driving, such as police procedures, officers in the department, innocent civilians in the

neighborhood, former criminals and arrestees, human behavior and emotions, facial and vehicle

recognition, and so on. It will need to employ machine intelligence tools and techniques for

achieving suitable perception and behaviors in conjunction with the knowledgebase.

Levels of autonomy have been defined to characterize autonomous vehicles, but there are a few

somewhat different sets of definitions. Here is one:

Level 0 is a vehicle with no autonomy. With Level 1, a few functions, such as automated cruise

control, are automated. In Level 2 the driver, while always monitoring the car, does not have to

steer or brake or accelerate under some driving conditions. There are many commercially

available vehicle models with Level 2 autonomy. With Level 3 autonomy the vehicle can drive

mostly autonomously, but the driver must always be alert to take over as needed. The vehicle

may check the driver’s alertness regularly; and if found lacking, the vehicle may stop on its own.

A few Level 3 vehicles will commercially available within the year. With Level 4 autonomy, the

vehicle can operate fully autonomously at least in some environments, e.g., on an interstate road,

without the driver having to be alert while in that environment. Or the vehicle may operate in all

environments without the driver being always alert to take over. But there must always be a

driver in the vehicle. With Level 5, the vehicle can operate without any human or driver in the

vehicle. There are fully autonomous, no occupant vehicles operating now in very limited

environments, such as shuttle buses or vans.

We define a new level, Level 6, where the autonomous vehicle, such as a police cruiser, can

drive itself with self-contained hardware and software (perhaps supplemented by the

developmental Connected Vehicle System, where vehicles communicate with each other and the

infrastructure for greater safety and efficiency), but make use of the Cloud to access and use

supplementary knowledge bases and artificial intelligence software. For example, it might

access IBM’s Watson to use for natural language interaction with neighborhood civilians, or to

discuss reporting requirements with its partner police officer. Using data and software in the

Cloud, the vehicle will be able to recognize license plates, vehicles, and faces. Access to the

cloud for non-driving cognition will save on the need to integrate hardware and software in each

vehicle.

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In summary, the foot patrol officer teamed with an autonomous patrol car and combining the best

attributes of humans and machines, could provide superior community-centered policing.

Artist’s Concept of an Autonomous Police Cruiser

The Police Foundation

Since 1993 the Police Foundation has provided community policing education, training, and

technical assistance to more than 1,000 law enforcement agencies and communities. The

Foundation works closely with police officers and police agencies across the country, bringing

researchers and technology into a constructive partnership with law enforcement, engendering

new models of law enforcement and creative approaches to policing. In 2016 the Foundation

published the results of a study concerning law enforcement and unmanned air systems (UAS),

sponsored by the Office of Community Oriented Policing Services of the U.S. Department of

Justice.

Mr. Rob Davis is Chief Social Scientist for the Police Foundation. He has more than 30 years of

experience in criminal justice research and evaluation, directing more than 35 projects on

policing, crime prevention, terrorism, victimization, courts, prosecution, courts, and

immigration, for federal and state governments and private foundations. He has led projects

with the nation’s leading law enforcement agencies. He authored two books on crime

prevention, is the editor of six books on crime prevention and victimization (including the highly

popular “Victims of Crime,” which is in its fourth edition), and is the author of more than 100

journal articles and book chapters.

Dr. Robert Finkelstein is President of Robotic Technology Inc. and is an adjunct Professor

teaching graduate courses in Technology Management, Systems Engineering, and Autonomous

Vehicles. He has more than 30 years of experience with military and civil autonomous vehicle

research and development. RTI clients have included 15 government agencies, 6 universities, 8

non-profit organizations, and 43 corporations.