Law enforcement agencies need to prepare for autonomous vehicles to become commonplace on public roadways and embrace the technology in order to better serve their communities. Although a fair amount of self-driving prototypes were tested in the 1980s, the first real test of autonomous vehicles (AVs) or self-driving vehicles took place with the DARPA Grand Challenge in 2004.¹ During the first challenge, none of the participating vehicles successfully finished the race. Less than a year later, several vehicles were able to complete it. Since that time, automobile manufacturers have been in a technological race to develop and perfect AV technology. The progress of AV technology has moved faster than expected and should continue to accelerate as in the coming years.² Is law enforcement prepared to handle self-driving cars on public roadways? Are police agencies prepared to leverage and employ self-driving vehicle technology to better serve their communities?

Autonomous Vehicle Technology

The National Highway Traffic Safety Administration (NHTSA) is responsible for developing and enforcing the Federal Motor Vehicle Safety Standards (FMVSS). Recognizing the need to distinguish the various types of autonomous vehicles, NHTSA established five levels of vehicle automation in 2013. As can be seen in Figure 1, the levels range from Level 0, which is no automation, to Level 5, which is defined as full self-driving automation.³ NHTSA is committed to ensuring the safety of autonomous vehicles with the release of its A Vision of Safety 2.0 report.⁴

In California, regulations for self-driving vehicles were implemented in 2014 and updated in 2017.⁵ Many vehicles currently on the road operate at Level 2 automation (semi-autonomous). This means they can operate for extended periods of time with little human involvement.⁶ Tesla and Mercedes-Benz plan to have vehicles on the road that can operate with little human interaction (Level 4), and many say fully autonomous vehicles could be on public roadways by 2025, even with the setbacks seen in recent years.⁷

The development of self-driving vehicles was on track to exceed the expected timelines of analysts and industry insiders until a series of incidents in the first quarter of 2018. On March 18, 2018, an Uber self-driving car in Tempe, Arizona, struck and killed a pedestrian. The Uber vehicle had an employee as a passenger when a pedestrian crossed the street in front of the vehicle and was struck. Although the investigation is ongoing, Uber suspended all testing of its autonomous vehicles the next day, halting work in Pittsburgh, Pennsylvania; San Francisco, California; Toronto, Ontario; and the Phoenix, Arizona, area.⁸ Two other incidents involving Tesla vehicles crashing, caused one fatality and one injury.⁹ As a result, the momentum this technology was experiencing has now slowed to a crawl, as companies assess the fallout from these collisions.¹⁰ Although the testing has slowed for many of the big companies, momentum will return once these concerns are addressed. The long-term safety benefits make AV technology difficult to ignore.

Implications for Public Safety

AV technology promises to address safety concerns for the motoring public by reducing traffic collisions related to distracted driving, human error, and impaired driving. This is not an opinion; in fact, the U.S. federal government is relying on AV technology to save millions of lives over the next 30 years.

Distracted driving continues to be the cause of a significant number of deaths each year. According to NHTSA, in 2016, 3,450 people were killed in vehicle collisions in the United States involving distracted driving.¹¹ The California Department of Motor Vehicles reported more than 249,000 handheld cellphone and texting convictions in the same year. Anecdotally, the same experts believe drivers are using their cellphones more than ever while driving, which is fast becoming a significant safety hazard to the public.¹²

In addition to reducing the instances of distracted driving, AV technology can reduce human error as the cause for many collisions.

In addition to reducing the instances of distracted driving, AV technology can reduce human error as the cause for many collisions. A 2015 article by Science Alert reported that removing human errors and emotions from driving could lower traffic related deaths by 90 percent. This enhancement alone could save almost 300,000 lives each decade in the United States, with a potential cost savings of $190 billion in health care–related costs resulting from traffic collisions.¹³ It also means those using cellphones, talking with passengers, or changing the songs on their playlist would no longer be the cause of collisions.

Impaired driving in the United States is also a significant problem. According to the Centers for Disease Control and Prevention (CDC), 10,497 people died in alcohol-impaired driving crashes in 2016, accounting for 28 percent of all traffic-related deaths in the United States in 2016, and more than 1 million drivers were arrested for driving under the influence of alcohol or narcotics that year.¹⁴ Every two minutes, someone is injured in a drunk driving crash.¹⁵ Medical and recreational marijuana laws have also caused an uptick in impaired driving incidents.¹⁶ Over time, though, autonomous vehicles would significantly reduce the number of injuries and deaths related to impaired driving to the point that impaired driving collisions, and the enforcement of related laws, would become moot.

Although it appears fully autonomous vehicles can have a positive impact on these issues, some experts say semi-autonomous vehicles are not as safe as some might believe. Level 3 autonomous capability can already drive itself unless there is an emergency, when the technology alerts the driver to take control. Some manufacturers believe that Level 3 autonomy creates more problems than it solves.

Engineers at Google found that Level 3 cars allowed their drivers to take their focus off of driving much of time, but when drivers’ attention was required, the reaction time for a human to retake control of the vehicle was poor, at best. The same engineers describe humans as poor replacements in an emergency. Essentially, once the need for human intervention is identified by the car’s autonomous systems, the time needed for a human to take corrective action to prevent a collision is too long. Because of this, some manufacturers have changed course in their AV development. A 2017 article in Wired noted that Volvo is skipping semi-autonomous vehicles and working to go straight to full autonomy to create a Level 5 vehicle to sell to the general public.¹⁷

AV technology will also have an impact on the auto insurance industry. If cars are safer and are crashing less, the natural thought would be that insurance costs would go down. Compare.com posed this question in a 2017 article. The short answer provided by them is that full coverage would still be required for new cars as part of their purchase.¹⁸ Insurance companies will continue to assess fault, insurance rates, and other pertinent issues related to the phasing in of AVs. There are patent applications in which companies are assessing algorithms to decide how to determine fault and insurance premiums.¹⁹ The challenging part to determine fault would involve a vehicle with a human still at the controls. When AVs become the majority of vehicles on the road, though, it may be as simple as a comparison of the onboard data to determine which vehicle is at fault.

Implications for Police Departments

Semi-autonomous and fully autonomous vehicles have significant implications for law enforcement. Some implications are from the community members “driving” these vehicles; others are the ways the police may employ AVs to serve their communities.

The reduction in the number of traffic citations is a natural byproduct of self-driving vehicles. Traffic divisions in most municipal law enforcement agencies exist for the investigation of traffic collisions and the enforcement of traffic violations. If autonomous vehicles no longer commit traffic infractions, fewer police officers will be needed for traffic enforcement. As fewer tickets are issued, each municipality will also see a reduction in funds generated from traffic fines. About 41 million people receive speeding tickets in the United States every year, paying a total of more than $6.2 billion in fines and forfeitures per year—the equivalent of an estimated $300,000 in annual speeding ticket revenue per U.S. police officer ²⁰ The loss of that revenue will impact jurisdictions to varying degrees and could significantly impact their ability to fund traffic safety programs.

If the studies are correct, and upwards of 90 percent of traffic collisions can be reduced by self-driving cars, then police officers assigned to traffic duties would no longer be needed to investigate traffic collisions.²¹ Agencies need to prepare now for the significant reduction in the size of their traffic divisions. If not carefully managed, there could be a decrease in the level of service and response times since there may be fewer officers in the field.

Proactive policing is a baseline function in municipal law enforcement, especially in high crime areas. AV technology will change the manner in which proactive policing takes place.²¹ The most common involuntary contact with police is as a driver in a traffic stop. In 2011, an estimated 42 percent of face-to-face involuntary contacts that U.S. residents had with police occurred for this reason.²² Traditional police work often involves pretext car stops, using a traffic violation to investigate other criminal activity. Police departments often address high-crime areas by increasing patrols in the affected areas for visible deterrence and investigative car stops, often resulting in arrests. For instance, a vehicle driving or “casing” a parking lot at 3:00 a.m. is not a crime, but many officers have solved crimes as a result of initiating an investigative stop using a minor traffic violation.²³ Vehicles will still continue to be used to commit crimes. For example, high-tech vehicles may also be hacked and used as weapons by terrorists. Officers will need to be trained to leverage technology to overcome certain policing obstacles. These include fewer opportunities to initiate investigative stops due to reduced vehicle code violations and fewer officers on the street.

Positive Impacts for Police Officers to Patrol in Autonomous Vehicles

AVs used in conjunction with predictive policing programs can be invaluable to prevent and solve crime.²⁴ Predictive policing technology, which gathers crime data and analyzes the data to improve police officer allocation, is currently being used throughout the United States and has proven successful. AV technology can take this to the next level. Based on the capabilities of self-driving cars, police agencies will be able to upload predictive policing data into each officer’s patrol car at the beginning of their shifts. The patrol car would know when and where to drive in an effort to provide a visible presence to deter crime. Currently, police officers need to look up this information, write it out, or try to memorize it. The police car of the future would have the data freshly downloaded each shift. This could reduce crime and provide a better environment for all stakeholders.

Modern-day police officers deal with multitasking more than ever. A self-driving vehicle will allow the officer to multitask while still driving safely.

Police officers, by the nature of their jobs, are arguably some of the most distracted drivers. Modern-day police officers deal with multitasking more than ever. A self-driving vehicle will allow the officer to multitask while still driving safely. In addition, police officers will be able to safely focus their attention outside the car in an effort to seek out criminal activity and, ultimately, reduce crime. The reduction in the number of officers injured or killed in traffic collisions is another benefit of AV technology. Annually, law enforcement loses several officers due to automobile related accidents.²⁵

Table 1: Automobile-Related Line-of-Duty Deaths

[LEOKA 2018]

With the safety features of the autonomous vehicles combined with GPS-enabled mapping to identify traffic congestion and the current technology of traffic red light preemption devices, response times will improve while ensuring the officers still arrive safely. AV will also allow for deconfliction at intersections since the police cars of the future will know when other police cars are nearing the same intersection while driving with lights and sirens. In addition, police pursuits can become safer by preventing officers from over driving.

Finally, lessening the need to investigate traffic collisions will create a fiscal advantage. Many vehicles on the roads are already semi-autonomous and rely less on human input to prevent collisions. In California, there have been more than 30crashes since 2014 involving self-driving vehicles.²⁶ In the majority of the cases, human error has been a factor. Over time, the number of fully autonomous vehicles will outnumber semi-autonomous vehicles, which will result in a reduction of personnel and time required to investigate collisions and, ultimately, save tax dollars that can be used to enhance community-based crime prevention, efforts to investigate other crimes, or other priorities in the community.

Recommendations

Law enforcement associations need to work with legislatures in ensuring laws are contemporary and address some of the issues already brought forward, such as defining DUI-related laws, assigning responsibility of citations when they are issued, and determining fault in traffic collisions. The same groups need to work with NHTSA in establishing standards for how AV vehicles are programmed to respond in situations that would require priority-of-life issues. The International Association of Chiefs of Police (IACP) is at the forefront of AV technology trends. Through the Highway Safety Committee, IACP has worked with the American Association of Motor Vehicle Administrators (AAMVA). As a result of this ongoing collaboration, AAMVA published [ital.]Jurisdictional Guidance for the Safe Testing and Deployment of Highly Automated Vehicles[end] in May 2018.²⁷ This publication provides recommendations in several areas that impact law enforcement. Municipal law enforcement agencies lack an ability to impact how fast the technology will be refined and socially accepted; however, they can maintain vigilance and engage automakers in incorporating self-driving technology into modern police cars. In addition, agencies need to monitor AV trends so they are not surprised by the consequences of the public “driving” AVs. Many issues will need to be confronted, but law enforcement cannot be caught flat-footed.

Conclusion

Self-driving cars are coming, and law enforcement needs to be prepared. How fast the technology will be perfected and then accepted by the general public is unknown. Its development has been moving at a rapid clip in recent months despite several minor traffic collisions. While high-profile fatal collisions temporarily halted massive testing on public roadways, the dust is settling, and the race to perfect the technology will continue.

There are more benefits then negatives to this technology. The reduction in traffic collisions, including reductions in DUI-related collisions and distracted driving collisions, benefit the community and police departments. The same safety features can increase officer safety when used in patrol cars. Response times will improve, officers’ lives will be saved, and police pursuits will be safer. Municipal law enforcement will ultimately benefit as long as they take steps now to embrace this technology and ensure a better future.

Notes:

 ¹ Eric Adams, “Wait, Who Even Asked for Self-Driving Cars in the First Place?” The Drive, April 25, 2018.

² Auto Express Team, “Driverless Cars: Everything You Need to Know about Autonomous Car Revolution,” Auto Express, September 13, 2019.

³Kevin Davis, “Preparing for a Future with Autonomous Vehicles,” Police Chief Online (July 2016).

⁴ National Highway Traffic Safety Administration (NHTSA), A Vision for Safety 2.0. (Washington, DC: NHTSA, 2017); NHTSA, “SAE Levels of Automation,” 2018.

⁵ Autonomous Vehicles, CA Veh Code § 38750 (2018).

⁶ Stephanie Pratt and Kwame Boafo, “Semi-Autonomous Motor Vehicles: What Are the Implications for Work-related Road Safety?” NIOSH Science Blog, April 22, 2014.

⁷ Auto Express, “Driverless Cars.”

⁸ Bloomberg, “Uber Self-Driving Vehicle Kills a Pedestrian in Arizona; All Autonomous Tests Halted,” Orange County Register, March 19, 2018.

⁹ James Gilboy, “Tesla Sees Autopilot Usage Decrease after High Profile Crashes,” The Drive, May 4, 2018.

¹⁰ Will Knight, “What Uber’s Fatal Accident Could Mean for the Autonomous-Car Industry,” MIT Technology Review, March 19, 2018.

¹¹ National Center for Statistics and Analysis, “Distracted Driving 2016,” Traffic Safety Facts Research Note (Washington, DC: National Highway Traffic Safety Administration, April 2018).

¹² Gary Richards, “Cellphone Traffic Tickets Are Way Down across California, but Why?” Mercury News, updated August 12, 2016.

¹³ BEC CREW, “Driverless Cars Could Reduce Traffic Fatalities by Up to 90%, Says Report,” October 1, 2015.

¹⁴ Center for Disease Control and Prevention, “Impaired Driving: Get the Facts.”

¹⁵ Mothers Against Drunk Driving, “The Problem.”

¹⁶ “Pot Fuels Surge in Drugged Driving Deaths,” NBC News, February 15, 2014.

¹⁷ Alex Davies, “The Very Human Problem Blocking the Path to Self-Driving Cars,” Wired, January 1, 2017.

¹⁸ “Is New Car Insurance Getting Cheaper?” Compare.com, May 18, 2017.

¹⁹ Steven J. Fernandes, Paul Brendan Olson, and Pankaj Prakash, Systems and method for autonomous vehicle data processing. U.S. Patent US Patent #20150187019. assignee Hartford Fire Insurance Co. (2015).

²⁰ Colin Neagle, “Driverless Cars Could Cripple Law Enforcement Budgets,” Network World, May 20, 2014

²² Dennis J. Stevens, An Introduction to American Policing, 2nd ed. (Burlington, MA: Jones & Bartlett Learning, 2018), 247; Michele Bertoncello and Dominik Wee, “Ten Ways Autonomous Driving Could Redefine the Automotive World,” McKinsey & Company, June 2015;  ²³ Bureau of Justice Statistics, “Traffic Stops; Orin Kerr, “How Self-Driving Cars Could Determine the Future of Policing,” Washington Post, June 16, 2017.

 ²⁴ PREDPOL, The Predictive Policing Company, 2018.

²⁵  FBI, Law Enforcement Officers Killed and Assaulted, 2015, table 64, Law Enforcement Officers Accidentally Killed (Washington DC: U.S. Department of Justice, 2016).

²⁶ Dom Galeon, “Who Is Responsible When a Self-Driving Car Has an Accident?” Futurism, January 29, 2018.

²⁷ American Association of Motor Vehicle Administrators (AAMVA), Jurisdictional Guidance for the Safe Testing and Deployment of Highly Automated Vehicles (Arlington, VA: AAMVA, 2018).