This paper will examine the benefits that arise from the adoption of level four autonomous cars, and will effectively argue for the legalization of this technology in the United States. A critical analysis of the safety benefits of this technology finds the combination of cooperative abilities through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications systems, machine learning technologies, and advanced driver-assistance systems will reduce vehicular accidents (Bertoncello, M. & Wee, D., 2015). The analysis of the economic implications describes the various cost benefits that are associated with the shift into driverless cars. Transferring into road-use efficiencies, autonomous cars are able to optimize road usage by minimizing congestion and greatly reducing traffic causing accidents. Furthermore, this paper will analysis the various ways in which driverless vehicles are able to dramatically cut greenhouse gas emissions and overall improve the environmental impact of vehicle transportation. Finally, to conclude the discussions, opposing points will be stated to understand the challenges and issues that come with the legalization of this technology. This analysis of level four autonomous vehicles, which includes implementation strategies, will act as a policy guide for the United States in the legalization of this technology.
To understand the effects of autonomous vehicles, we must first observe the current automotive landscape and the overall trend towards autonomous transportation. When it comes to the technology of driverless cars in the automotive industry, we see several examples. Debatably the most infamous name in this segment is Tesla, who’s cars have been making headlines since the debut of their autopilot technology in late 2014. The first installments of this technology presented a semi-autonomous autopilot which included several basic hands off features such as automatic braking, lane switching, and blind spot warning (Thompson, 2016). With the purchase of the upgraded autopilot package, the most recent Tesla system update has the ability for full self-driving capabilities, according to Tesla (“Autopilot”). The success of Tesla has caught the attention of companies like Google, Volvo, and Mercedes-Benz, who are all investing millions of dollars into driverless development. Since the laws on driverless technology in the United States are obscure and unclear in most states, this presents a challenging issue for many of the automotive companies when deciding to pursue this technology. Due to this complexity, this paper presents arguments in favor of a universal legislation of level four autonomous vehicles across the United States. For the purpose of this paper, the five autonomous level rankings will be used to define level four autonomous cars. The United States Department of Transportation adopted the Society of Automotive Engineers (SAE) definition for level four autonomous which is defined as, “high automation: the driving mode-specific performance by an Automated Driving System of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene” (SAE International, 2016). Since driver error is responsible for approximately 90 percent of vehicle accidents in the United States (National Highway Traffic Safety Administration, 2008) this paper argues that the removal of humans from the responsibility of making driving decisions will not only save money, reduce congestion, and cut greenhouse gas emission but it will also save lives.
According to data from the National Highway Traffic Safety Administration, in 2012, there were 32,367 fatal crashes in the U.S. The breakdown of these accidents conclude, alcohol was involved in 31 percent of the time, speeding in 30 percent and distracted drivers in 21 percent of the crashes. What is consistent though, even when we review historical (2008) data, we find that driver error is believed to be the main reason behind over 90 percent of all crashes. According to the research group Eno, “Even when the critical reason behind a crash is attributed to the vehicle, roadway or environment, additional human factors such as inattention, distraction, or speeding are regularly found to have contributed to the crash occurrence and/or injury severity” (Eno Center for Transportation, 2013). Over 30 thousand people die each year in the U.S. in automobile collisions (National Highway Traffic Safety Administration, 2012), with 2.2 million crashes resulting in injury (Traffic Safety Facts, 2013). Traffic crashes remain the primary reason for the death of Americans between 15 and 24 years of age (Kegler, S. R., Beck, L. F. & Sauber-Schatz, E. K. 2012).
The penetration of autonomous vehicles and other advanced driver-assistance systems could ultimately cause vehicle crashes in the United States to fall from second to ninth place in terms of ranking among accident types and how lethal they are (Bertoncello, M. & Wee, D., 2015). We recognize that in order to make the best safety decisions, autonomous vehicles must be able to recognize common road objects (e.g. pedestrians, cyclists, road signs, animals, etc.) and environmental conditions (e.g. fog, snow, rain, etc.). This is a challenge for AV sensors. However, there seems to be consensus among most analysts that autonomous vehicles will overcome many of the obstacles that inhibit them from accurately responding in complex environments. We could see motor-vehicle fatality rates (per person-mile traveled) eventually approach those seen in aviation and rail, currently about 1 percent of current rates (Hayes, 2011). However, with level four autonomous vehicles, there is the possibility that drivers will take their vehicles out of self-driving mode and take control. An investigation was conducted by the National Transport Safety Board into a fatal accident involving Tesla’s Autopilot technology. The report concluded Tesla was not at fault, and revealed that the Tesla vehicle crash rates dropped by 40 percent after Autopilot was installed. Google’s only reported autonomous vehicle crash occurred when a human driver was operating the vehicle. The rate at which human control is needed will be a substantial factor in the safety of autonomous vehicles (Fagnant, D. J. & Kockelman, K., 2015).
Through the economic analysis of level four autonomous cars, this paper conceptualizes many of the cost benefits that are realized by the legalization of this technology. A large amount of the cost savings that arise from driverless technology is in the social and private costs that are cut due to a decrease in vehicle accidents (Anderson, 2014). Associated with these accidents are billions of dollars worth of costs that can be avoided with autonomous cars. The National Highway Traffic Safety Administration of the United States, calculated the economic cost of accidents in 2010 to be over $240 billion dollars (Blincoe, et al, 2015). These costs include property damage, medical costs, the cost of emergency services, legal and court costs, and more. Since around 90 percent of these accidents were caused by human error (Smith, 2013), it can be assumed that a large majority of these external accident costs will be able to be avoided by the use of level four driverless cars. Even at an adoption rate of 50 percent for these driverless vehicles, assuming they eliminate human error accidents, they have the capabilities of reducing economic costs associated with vehicle accidents by over $100 billion. A portion of these benefits will be obtained to the purchaser of the vehicle, while the other cost benefits are in the form of positive externality for other vehicles, cyclists, and pedestrians. Another untapped cost perspective is in the increased fuel efficiency of driverless technology. Forbes magazine predicted that by 2050, with the ability of autonomous cars to communicate with each other, fuel consumption will be reduced up to 44 percent (McMahon, 2017). With the average American household spending nearly $2,000 per year on gasoline (Doggett & Tarver, 2014), the car owners have the ability to save close to $1,000 a year on fuel, simply due to driving efficiencies. Finally, the attractiveness of car sharing programs with the addition of driverless technology creates unforeseen cost benefits. Technology think tank, RethinkX, believes that car ownership will be drastically changed in the ten years following the legalization of driverless cars for widespread public use and predicts that 95 percent of vehicle miles traveled in the U.S. will be by on-demand autonomous vehicles by 2030 (“Headlines”). This is because the legalization of autonomous vehicles allows the cost of car sharing programs to be significantly cheaper and more convenient than individual car ownership. The study conducted by RethinkX concluded that the cost for car sharing programs, around the timeframe of 2030, will approximate to a consumer cost of $3,400 per year. Compared to $9,000 per year cost of individual ownership (Brown, 2017), these cost savings will largely incentivize consumers to switch to these ride-hailing services.
Currently, the economic downside to level four autonomous vehicles is the cost of certain technologies that enables the driverless functions. Typical driverless vehicles have a LIDAR laser radar that creates a 360-degree visual map of the car’s surroundings. Velodyne, the leading company in cutting LIDAR costs, has created a small version of this technology that retails for around $8,000 (Amadeo, 2017). Although this cost is significantly cheaper than the $75,000 price tag on the most expensive Velodyne LIDAR model (Amadeo, 2017), this creates a major cost barrier in consumer adoption of driverless cars. However, Tesla is using cameras and sensors to obtain driverless ability (Bradley, 2017) and they are able to manufacturer this technology at a significantly lower cost. With the Tesla Model 3 being released at $35,000 this almost entirely removes this cost barrier.
The Federal Highway Administration estimates that 25% of congestion is attributable to traffic incidents, around half of which are crashes (Federal Highway Administration, 2005). Platooning is a component of the suite of features that autonomous vehicles may employ that allow vehicles with cooperative vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication capabilities to travel closer safely at high speeds. The ability to anticipate acceleration and braking decisions of the lead vehicle allows for the reduction of traffic waves. It is also expected that this cooperative capability will facilitate shorter headways between vehicles at traffic signals (and shorter start-up times). Autonomous vehicles could more effectively utilize green time at signals and considerably improve intersection capacities. Simulation studies show that cooperative V2V and V2I communications coupled with Adaptive Cruise Control (ACC) deployed at 10 percent, 50 percent, and 90 percent market-penetration levels will increase existing lanes capacities by around 1 percent, 21 percent and 80 percent respectively (Shladover et al., 2012).
We are cognizant that many of the benefits to be derived from the legalization of autonomous vehicles will not be realized until there is high market penetration. However, many studies show that the penetration of autonomous vehicles and other advanced driver-assistance systems would ultimately cause vehicle crashes in the United States to fall and reduce congestion. Autonomous vehicles are expected to use existing roadways and intersections more efficiently through shorter gaps between vehicles and coordinated platoons. However, many of the features of advanced driver-assistance systems (e.g. anti-lock braking, forward collision warning, adaptive cruise control, etc.), are already being integrated into vehicles and some of the benefits will be realized even before high autonomous vehicle penetration is achieved. At 10 percent, autonomous vehicle market penetration, freeway congestion delays are estimated to fall 15 percent (mostly due to smoothed flow and bottle- neck reductions). At 50 percent penetration, a 39 percent congestion improvement and 20 percent road capacity improvement is expected. Finally, at the 90 percent level, freeway congestion is assumed to fall by 60 percent, with the near doubling of roadway capacity and dramatic crash reductions (Shladover et al., 2012). However, at the arterial-roadway level, congestion is assumed to experience 5 percent, 10 percent and 15 percent at 10 percent, 50 percent, and 90 percent penetration rates respectively. The reason is that delays on arterial roadways emerge largely from conflicting turning movements, pedestrians, and other transportation features that autonomous vehicles cannot easily address without near-complete market penetration and automated intersection management (Dresner, K. & Stone, P., 2008).
To set the framework for the environmental benefits of level four autonomous cars, we must first observe the situation that we are facing without this technology. Currently, vehicle transportation makes up 26 percent of total greenhouse gas emission in the United States. It is clear that this represents a large issue when waging the war against global warming. Autonomous vehicles are able to alleviate the effects that cars have on greenhouse gas emission through various technologies and social incentives. The first way that autonomous vehicles can accomplish this is through driving efficiencies in acceleration and braking. The Business Insider speculated that these efficiencies, that result in greater fuel efficiency, can reduce carbon emissions by up to 300 million tons per year in the United States alone (Thompson, 2016). In addition to the environmental benefits that are attained from driving efficiencies, autonomous vehicle technology incentivizes consumers to adopt electric vehicles. Currently, driver experience and the cost of electric vehicles are the major barriers that consumers are hesitant to buying electric vehicles. However, when coupling the gradually declining cost of electric cars and the introduction of driverless technology consumers have virtually no reason to purchasing gas fueled car. We are already seeing such vehicles drive off the production line. In March 2016, Tesla announced the Model 3. At a base price of $35,000 USD, this fully electric mid-sized car has self-driving technology (Glon & Hard, 2017). With over 500,000 preorders, this car has the ability to the biggest disrupter to the American automotive industry since the 1908 Ford Model T. Due to the success of Tesla, other companies have been forced to consider both self-driving cars and fully electric cars (Hawkins 2017). If Tesla’s growth is able to successfully entice all major car brands to autonomous vehicles and to adopt these new electric technologies, the environmental benefits are undeniable. The National Resource Defense Council calculated that by 2050 with full market penetration of electric cars, greenhouse gas emissions can be reduced by over a billion metric tons per year, or 45 percent relative to 2015 levels (Tonachel, 2015). It is clear that these environmental improvements, which are enabled by the adoption of level four autonomous vehicles, can create a legitimate difference in the carbon emissions created by the United States.
Risk and Mitigation Factors
Opponents of the resolution argue that to remove of humans from the decision-making process where life and death choices have to be made is immoral. The ethical dilemma that arises when an autonomous vehicle has to make a choice in a crash scenario, where there exist multiple courses of action in which all options may cause harm to a human being, is a valid concern. There is no solution to the ‘Trolley problem’ and the reasons for this are outside of the scope of this paper. However, this scenario is not something that occupies much research time among the manufacturers of automated vehicles. Rather, the industry is focused on technologies that keep the vehicles out of such scenarios in the first place. According to Christian von Hugo, Manager Driver Assistance Systems, Active Safety & Ratings, Daimler Mercedes-Benz, “This moral question of whom to save: 99 percent of our engineering work is to prevent these situations from happening at all. We are working so our cars don’t drive into situations where that could happen and [will] drive away from potential situations where those decisions have to be made” (Taylor, M. 2016). Some manufacturers, including Audi and Volvo, are already getting around the scenario by assuming full legal responsibility for any crashes or fatalities that occur with their technology. In addition, we may see auto insurers shift their core business model from the protection of private customers from risks associated with human error in accidents to focusing mainly on insuring car manufacturers from liabilities from technical failure of their autonomous vehicles (Bertoncello, M. & Wee, D., 2015).
By analyzing the benefits of level four autonomous cars in the United States, this paper urges for the legalization of this technology in order to obtain these benefits. Beginning with safety benefits, the increased vehicle safety due to driverless technology can make transportation significantly safer. Considering that around 90 percent of accidents occur due to human error, an adoption rate of only 50 percent for driverless cars has the potential of reducing vehicle accidents, injuries and deaths by approximately 2.5 million per year, 1 million per year, and 14,500 per year respectively (National Highway Traffic Safety Administration, 2012). These safety benefits also translate into significant economic benefits due to the savings obtained by the reduction of these accidents. It can be calculated that with 50 percent driverless cars, America can save over $100 billion is accident associated costs (Blincoe, et al, 2015). Level four autonomous cars are also able to achieve various other benefits due to its driving efficiencies. It is estimated that at the 50 percent penetration rate of adoption, current lane congestion can be reduced by up to 39 percent (Shladover et al., 2012). Freeing up this lane space creates time and cost benefits for the driver, and it also creates environmental values. The Business Insider speculates that these values will add up to a reduction in nearly 300 million tons of carbon emission (Thompson, 2016). Therefore, it is clear that these benefits cause a large positive impact on, not only drivers, but society as a whole. However, this paper explored possible concerns for the legalization of this technology, and it is crucial the legalization of level four autonomous vehicles considers certain regulations. Although some of the benefits may not be achieved with regulatory system, it is imperative to mitigate several of the risks associated with driverless technology to ensure a high societal adoption. It is important to note that the analysis of the various social effects demonstrates the benefits that are obtained, and only obtained, by the legalization of level four autonomous cars. Therefore, in the best interest of society, it is greatly beneficial to legalize such technology.
Amadeo, Ron. “Google’s Waymo invests in LIDAR technology, cuts costs by 90 percent.” Ars Technica, 9 Jan. 2017, www.arstechnica.com/cars/2017/01/googles-waymo-invests-in-lidar-technology-cuts-costs-by-90-percent/
Anderson, James M., et al. Autonomous Vehicle Technology: A Guide for Policymakers. RAND Corporation, 2014. JSTOR, www.jstor.org/stable/10.7249/j.ctt5hhwgz. “Autopilot.” Autopilot | Tesla Canada, www.tesla.com/en_CA/autopilot
Bertoncello, M. & Wee, D., (2015). Ten ways autonomous driving could redefine the automotive world. McKinsey & Company. Retrieved from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/ten-ways-autonomous-driving-could-redefine-the-automotive-world
Blincoe, L. J., et al. The economic and societal impact of motor vehicle crashes, 2010. Washington, DC: National Highway Traffic Safety Administration, May 2015, https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812013
Bradley, Ryan. “10 Breakthrough Technologies 2016: Tesla Autopilot.” MIT Technology Review, MIT Technology Review, 21 Feb. 2017, www.technologyreview.com/s/600772/10-breakthrough-technologies-2016-tesla-autopilot/
Brown, Mike. “The $5,600 Reason Car-Sharing Will Take Over the World.” Inverse, 4 May 2017, www.inverse.com/article/31125-rethinkx-report-self-driving-rideshare-end-car-ownership
Dresner, K. & Stone, P., (2008). A multiagent approach to autonomous intersection management. Journal of Artificial Intelligence Research, 31, 591–656
Doggett, Tom, & Russ Tarver. “U.S. Energy Information Administration – EIA – Independent Statistics and Analysis.” U.S. household gasoline expenditures in 2015 on track to be the lowest in 11 years – Today in Energy – U.S. Energy Information Administration (EIA), 16 Dec. 2014, www.eia.gov/todayinenergy/detail.php?id=19211
Eno Center for Transportation (2013). Preparing a Nation for Autonomous Vehicles. Opportunities, Barriers and Policy Recommendations. William P. Eno Paper
Fagnant, D. J. & Kockelman, K. (2015). Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Elsevier, Transportation Research Part A 77 (2015) 167–181
Glon, Ronan, and Andrew Hard. “Model 3 experiences delays as Tesla tries to claw out of production hell.” Digital Trends, 17 Nov. 2017, www.digitaltrends.com/cars/tesla-model-3-performance-specs-news-rumors/
Hawkins, Andrew J. “How Tesla changed the auto industry forever.” The Verge, The Verge, 28 July 2017, www.theverge.com/2017/7/28/16059954/tesla-model-3-2017-auto-industry-influence-elon-musk.
Hayes, B. (2011). Leave the driving to it. American Scientist. 99, 362–366. “Headlines” RethinkX, www.rethinkx.com/headlines/
Kegler, S. R., Beck, L. F. & Sauber-Schatz, E. K. (2012). Motor Vehicle Crash Deaths in Metropolitan Areas — United States, 2009. Centers for Disease Control and Prevention.
McMahon, Jeff. “Big Fuel Savings From Autonomous Vehicles.” Forbes, Forbes Magazine, 18 Apr. 2017, www.forbes.com/sites/jeffmcmahon/2017/04/17/big-fuel-savings-from-autonomous-vehicles/#76a07ed44390.
National Highway Traffic Safety Administration (2008). National Motor Vehicle Crash Causation Survey. U.S. Department of Transportation, Report DOT HS 811 059
National Highway Traffic Safety Administration (2015). Traffic Safety Facts. U.S. Department of Transportation, Report DOT HS 812 169
SAE International. (2016). U.S. Department of Transportation’s New Policy on Automated Vehicles Adopts SAE International’s Levels of Automation for Defining Driving Automation in On-Road Motor Vehicles [Press release]. Retrieved from https://www.sae.org/news/3544/
Shladover, S. E., Su D. & Lu X. (2012). Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow. Transportation Research Record: Journal of the Transportation Research Board, 2324, 63–70
Smith, Bryant W. “Human error as a cause of vehicle crashes.” Center for Internet and Society, Stanford University, 18 Dec. 2013, cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes.
Taylor, M. (2016). Self-Driving Mercedes-Benzes Will Prioritize Occupant Safety over Pedestrians. Car and Driver
Thompson, Cadie. “The 3 biggest ways self-Driving cars will improve our lives.” Business Insider, Business Insider, 10 June 2016, www.businessinsider.com/advantages-of-driverless-cars-2016-6/#roads-will-be-safer-1.
Thompson, Cadie. “7 incredible things Tesla’s cars can now do on Autopilot.” Business Insider, Business Insider, 11 Jan. 2016, www.businessinsider.com/7-incredible-tesla-autopilot-features-2016-1/#when-tesla-first-launched-in-october-cars-got-the-ability-to-autosteer-the-new-update-however-adds-new-restrictions-to-the-function-1
Tonachel, Luke. “Study: Electric Vehicles Can Dramatically Reduce Carbon Pollution fromTransportation, and Improve Air Quality.” NRDC, 17 Sept. 2015, www.nrdc.org/experts/luke-tonachel/study-electric-vehicles-can-dramatically-reduce-carbon-pollution.