Autonomous Automobiles Tetrad Analysis
By: Aaron Herbst, Rachel Knutson, Joy Turner, Greta Erdahl, Elizabeth Dailey
History:
The concepts of autonomous automobiles have been in the imaginations of individuals for decades upon decades, as can be seen through numerous example of popular culture, such as Back to the Future II (1989), Batman (1966), Total Recall (1990), I, Robot (2004), and many more. Within this realm of imagination, the coming technology in the last decade or so has the potential to create these dreams into a reality. The history and process of the creation of autonomous automobiles can be seen within three phases: foundational research, “Grand Challenges,” and commercial development (Anderson, 57, 2016).
The foundational research of AA demonstrates the early workings of self-driving automobiles, and tactics that were taken in order to advance this technology. Much of the early ideas of self-driving cars occurred between the 1980s and the early 2000s, but the idea of autonomous automobiles proved difficult due to the complexity of driving within inches of other objects, and humans themselves. Two technology sources occurred from this research, with those being “the development of automated highway systems . . . [and] both semi-autonomous and autonomous vehicles that depended little, if it all, on highway infrastructure” (Anderson, 56, 2016). In 1991, after numerous years of experimentation, the United States Congress passed the ISTEA Transportation Authorization bill, which allowed for the construction of the 1997 National Automated Highway System Consortium in San Diego, California (Brimbraw, 193, 2015). The DEMO 97 program showed the movement of 8 vehicles that were guided by magnets that were placed in the highway and the vehicle itself and were controlled by vehicle-to-vehicle communication systems (Anderson, 56, 2016). The second form of technology developed through the foundation research shows a large step in the process of autonomous automobiles, with Ernst Dickmann’s S-class Mercedes Benz taking a 1,590 km journey, using computer vision and microprocessors, included with memory systems designed for processing to react and interact in real time (Brimbaw, 193, 2015).
The three “Grand Challenges” of autonomous automobiles were created by the U.S Defense Advanced Research Projects Agency (DARPA) in order to further advance the creation of AA, and to reignite the public’s interest of the idea (Anderson, 56, 2014). These Challenges were held from 2003 to 2007, and the first challenges held no companies able to create an autonomous vehicle able to complete a 150-mile trip, until the second challenge (Anderson, 57, 2014). However, by the third challenge, dubbed the “Urban Challenge,” companies were encouraged to build an autonomous vehicle that could maneuver through an urban course, complete with traffic laws and other human-driven automobiles, with 3 teams finishing the course within 4.5 hours (Anderson, 57, 2014). The Grand Challenge was revolutionary in the history of self-driving cars, in the way that it encouraged the process of new algorithms, navigating roads, and abiding traffic laws.
The third phase of the history of autonomous automobiles, is the stage of commercial development, which has been seen within the last decade. Anderson writes that due to the “Grand Challenges,” there was the creation of relationships between the education sector, and automobile manufacturers (57, 2016). These programs include “the Autonomous Driving Collaborative Research Lab, a partnership between GM and Carnegie Mellon University and a partnership between Volkswagen and Stanford University” (Anderson, 57, 2016). Through these collaborations, driverless cars have begun to be sprung into production and retail. In addition, Google’s Driverless Car initiative is a program that also has encouraged the production of autonomous automobiles, through the testing of fleets of cars and different campaigns. The year 2013 also saw Toyota and Audi’s versions and visions of autonomous automobiles at the International Consumer Electronics Show (Anderson, 57, 2016).
Core Components:
When looking at how the technology of autonomous automobiles work, it is important to glimpse the outer body of the vehicles, as well as the inner structure of the physical object. Specifically, the system of the THUNDER-1 autonomous automobile includes core modules which include: “the implementation of Hector SLAM based on Teleoperation, Autonomous Hector SLAM, the realization of Autonomous Navigation System, Intelligent Obstacle Avoidance System, Command Processing Center, Data Recording System as well as the Hardware System” (Zhou, 2018). However, just as importantly, is the use of software and hardware within the technological design of autonomous automobiles. Huang writes that “hardware splits broadly into sensors, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technology, and actuators. Software splits broadly into processes for perception, planning, and control” (2018). Figure 1 demonstrates the functional architecture written by Huang, as well as the processing between software and hardware systems in AA.
Autonomous Vehicle Hardware looks at technology sources within the automobile, such as sensors, V2V tech, and actuators (Huang, 2018). Sensors are technology sources that allow for vehicles to take in information about the surrounding environments; they are able to gauge what is surrounding the vehicle, and enable the vehicle to understand its surroundings in a more concise manner. A number of sensors are implemented into autonomous automobiles in order to maximize function, such as GPS/Inertial Measurement Unit (IMUs), camera, LiDar, and radar, and many of these sensors are combined with each other through a process called sensor fusion (Huang, 2018). Many of these sensors use a process called light detection and ranging, or lidar, which emit beams of light and calculate the time-of-flight in which the resounding reflection is returned back to the sensor (Anderson, 61, 2016). Within the hardware of the THUNDER-1, Zhou writes that “the Logitech Webcam, Intel Realsense Camera, Neato xv11 laser liDAR, and 6 DoF IMU are adapted to collect the raw data which include the images, point cloud and pose value for the purpose of mapping, pose estimation, localization, and obstacle avoidance” (2018). In this respect, the sensors collect the messages, and are transmitted to 7 port USB hub and nVidia Jetson TX1, which is able to compute image processing (Zhou, 2018). V2X tech is also used within the hardware and allows vehicles to take in information from other machine objects in the environment, such as traffic lights or other autonomous vehicles nearby (Huang, 2018). Lastly, there are actuators, which act as a controlling system for the vehicle (Huang, 2018).
Autonomous automobiles rely on three sources for the intrinsic software, those being: perception, planning, and control. Perception refers to the automobiles ability to compute the information that it is receiving from the outer sensors and other hardware (Huang, 2018). Generally, it allows for the vehicle to be aware of the environmental surroundings in order to maximize safety for individuals inside and outside of the vehicle. For the planning aspect, Huang writes that “the planning system works by combining the processed information about the environment (i.e. from the sensors and V2X components) with established policies and knowledge about how to navigate in the environment . . . so that the car can determine what action to take” (2018). The system can make certain decisions in order to achieve a multitude of goals. Lastly, the control system refers to the process of the system obtaining information from the planning system, in which it carries out the desired outcomes through the actuators (Huang, 2018). Within the software system of THUNDER-1, Zhou gives a more concise and complex form of how it functions. There are forms of software, such as Raw Data Collection, Scene Detection and Understanding, Path Plan, Car Control, Data Recording, Recognition Model Retraining, Communication, and Security (Zhou, 2018). These aspects each have a set of necessities and uses, such as localization, command systems, recognition, etc. Figure 2 below gives a visual representation of the software data within the THUNDER-1. All in all, the software and hardware of autonomous automobiles work together in numerous ways in order to complete the goals set upon it. Figure 1:
Figure 2:
Diffusion:
The diffusion of Autonomous Automobiles as a practical technology utilized in society has been gradual, however it is predicted to increase in popularity in the future. There are many different factors that affect this process. It was previously assumed that “an innovation that was superior to previously established technologies would quickly spread and become widely used in society” (Quan-Haase). However in truth, the diffusion of technology is instead more heavily influenced by “social, cultural, political, and historical factors,” rather than by only technological superiority (Quan-Haase). While autonomous automobiles have a lot to offer society, there is some uncertainty regarding the expected outcomes of this product, there are cost factors to consider, social factors, and practicality/ease of use. The diffusion of technology is a process that is generally guided by five things: relative advantage, compatibility, complexity, trialability, and observability (Nieuwenhuijsen, 2015, p. 28)
In regards to the diffusion and adoption of this technology among society, we must consider that autonomous automobiles are not necessarily an isolated product (Bosankic, 2017, p. 1). Partially autonomous automobiles are already a successful part of society today, saturation the automobile market. They have already undergone the scrutiny of relative advantage compatibility, complexity, trialability, and observability, and are successfully being used in society today, Automobiles today are already incorporating features with some degrees of automation into existing cars, such as parking assist, adaptive cruise control and collision avoidance systems (Levine, 2018, p. 1). The reflection of present societies acceptance towards these features suggests there is potential for a positive adoption rate of fully autonomous automobiles in the future. There are already brands of developed and tested prototypes of the first fully autonomous vehicles, such as Google, Tesla, and Mercedes-Benz. However, as you may have noticed, these are mostly luxury car brands, which means they will cost more. This is where we must consider the practicality of cost, safety, societal factors, that will influence how this technology is accepted or rejected by society as a whole. Another thought to consider is that once more autonomous vehicles are produced there will be more affordable options, that could reduce the cost barrier to society’s ability to utilize this technology.
The diffusion rate of this technology will be influenced by society’s willingness to adopt this technology, which is a decision they will make by weighing the pros and cons of using this product in comparison to already existing automobiles. Relative advantages of this technology include its ability to increase mobility for people that can’t drive themselves due to a disability or due to their age. Furthermore, “automated vehicles are considered safer than conventional cars, so lighter materials can be used, which also saves fuel,” making them more environmentally friendly (Nieuwenhuijsen, 2015, p. 8). Another common attraction for automated vehicles is that they offer the convenience of not having to find parking. The most commonly discussed benefits include the ability to multitask while en route and the potential for increased safety on the roads (Nieuwenhuijsen, 2015, p. 31). On the contrary, people also worry that the increase in road safety with the use of autonomous automobiles will be worse or the same as they are now, so they don’t see a purpose in utilizing this technology. The risk of virus attack is considered one of the most important barriers to adoption (Levine, 2018, p. 5). Many individuals also report their dislike in surrendering their control over the vehicle. A survey found that this feeling of losing control was more important to people considering the use of self-driving vehicles than safety concerns (Levine, 2018, p. 5). Many of the current barriers to the use of autonomous vehicles may also be due to the low maturity of the technology. For example, the high costs in the early stage, the readiness of the infrastructure, liability issues, personal preferences of the user are all barriers that will be reduced or eliminated over time if autonomous vehicles became an active technology in society (Nieuwenhuijsen, 2015, p. 11). Factors of compatibility for autonomous vehicles are a real concern, as the infrastructure of roads and parking availability would likely be altered. The complexity of autonomous automobiles on the other hand, should not be a concern. These vehicles are being created majorly for convenience purposes, and the fact that the individual does not have to be capable of driving the car makes it easy to use.
Trialability and observability seem to be the stage we are currently reflecting upon in regards to the use of self-driving vehicles. Many of us have heard about this luxury technology, but we have not seen or experienced it. This innovation is still in the testing process, as innovators continue to gather knowledge on how to perfect this technology. For example Google states to have already driven more than one million miles of test-drive in which they gained a lot of information about the technology and the human factor (Nieuwenhuijsen, 2015, p. 28).
Statistics indicate that self-driving vehicles are a product we can expect to hit the roads by 2020 (Bosankic, 2017, p. 2). However, I wouldn’t expect the population of individuals in ownership of these autonomous automobiles to be extremely large. The diffusion of technology into society is generally an S-shaped curve in which few people adopt it, then there is exponential growth in the products sales, and finally sales decrease again after many have obtained ownership of the product. This process is reflected in the graph below. This graph demonstrates the positive sale projections of highly and fully autonomous automobiles into our near future. From this graph we can observe that the societal acceptance of this technology now, would indicate a saturated market of self-driving cars by the year 2050, with exponential growth in autonomous vehicle sales occurring as early as 2035. This curve shows that the market will be saturated in 2059 when approximately 87 million autonomous vehicles would have been sold (Lavasani, Jin, and Du, 2015, p. 13).
Societal Effects:
The tetrad is a theoretical model that can be used to analyze and predict a particular technology’s effects on society. Marshall McLuhan and Bruce Power’s tetrad model incorporates four main elements that include enhancement, obsolescence, retrieval, and reversal. Enhancement analyzes what a particular technology does to solve a problem society previously had, and/or how the technology benefits society. Obsolescence focuses on what is being replaced when a new technology comes into play. Retrieval seeks to understand what values the technology brings back that was previously lost. Finally, reversal analyzes what new problem can come from a particular technology being introduced into society. In this section, the elements of the tetrad model will be applied to autonomous automobiles in order to understand what effect it could have on society. Additionally, the theory of relative advantage will be applied to this artifact and the areas of business, local community and liability will be discussed in terms of how autonomous automobiles will impact these specific areas of society.
Enhancement
The use of autonomous automobiles in the future could have significant benefits such as improving safety, allowing greater efficiency for consumers, and reducing harm to the environment. Every year, about 1.3 million people worldwide die in car accidents, which results in an average of 3,287 deaths per day (Beltz, 2018). Safety on the road is one of the biggest concerns in our world today as people suffer from the results of drunk or distracted driving. The use of fully self-driving cars could reduce the risks of driving, and allow for a decrease in driving-related accidents. Autonomous automobiles can achieve ultimate safety by removing human errors and perceptual limitations by using a vehicle operation control group (Jurgen, 2013). As Jurgen reports, driving a vehicle consists of three main functions that include perception, planning, and control. The use of planning allows autonomous vehicles to decide the behavior of the vehicle completely on its own. The result of many accidents today involves flaws in human perception and decision-making; however, the use of autonomous vehicles could eliminate these human errors. This has already been tested, as a car which used the features of planning algorithms and other software design won the 2010 Autonomous Vehicle Competition organized by the Hyundai Motor Group in Korea. The safety of consumers could drastically increase as fully autonomous vehicles are developed and integrated into our society. In addition to this benefit, consumers could also increase their productivity with the use of self-driving cars. Instead of having to spend time focusing on a commute, consumers can do their work or other activities while cars drive them to their destination, leading to greater efficiency. Another enhancement to the use of autonomous automobiles includes benefits to the environment. Self-driving cars will rely on electric engines, rechargeable batteries, and/or solar panel energy instead of fossil fuels. “BP has said that self-driving vehicles and electric engines will deplete demand for fossil fuels by 2040 in its 2018 Energy Outlook” (Loughran, 2018). Without the use of fossil fuels, there are significant benefits added to the environment. Currently in the U.S., about 29% of global warming emissions come from fossil fuels such as coal and natural gas (“Benefits of renewable energy”, 2017). With the use of self-driving cars that rely on other sources of energy, and the elimination of fossil fuels, the damage to the environment can be reduced.
Obsolescence
There are many enhancements when it comes to the use of autonomous automobiles, but our society must question with these future changes, what is being taken away? With electric engines and alternative sources of energy becoming a staple for self-driving cars, the use of fossil fuel would become unnecessary. The use of human drivers and services such as Uber and Lyft would also become obsolete. Less than a year ago, Uber Chief executive expressed these fears when he described self-driving cars as “an existential threat” to his company (Mims, 2017). Self-driving cars would be a lot cheaper to operate than cars requiring human drivers. This is a benefit to consumers, but not so much to the businesses this impacts. Companies such as Uber and Lyft would have to insert themselves into the development and use of autonomous automobiles to stay in business. As Sam Abuelsamid, a senior analyst with Navigant research puts it, “Uber, Lyft, and their imitators will eventually cease to exist as stand-alone companies, either going out of business or being acquired by car makers” (Mims, 2017). These companies aren’t the only ones impacted by the future use of autonomous automobiles. With alternative sources of energy for autonomous vehicles, fossil fuel would no longer be needed, putting gas stations/convenience stores out of business. Our society’s businesses could, therefore, be highly impacted by the use of autonomous automobiles in a negative way. Completely autonomous automobiles eliminate the use for many “staples” in today’s society, that has grown and gathered significant amounts of profit. The market of autonomous vehicles replaces businesses that thrive today, resulting in unemployment for many businesses.
Retrieval
The retrieval component of the Tetrad model refers to the recovery of values and insight that was once lost or eroded. If autonomous automobiles were implemented, it would retrieve a sense of unlimited and unrestricted quest. There would no longer be any inhibitions on travel. It would retrieve newfound independence despite age. It would bring back the freedom and safety that children used to have when they could travel by themselves before the invention of cars and the necessity of having parents or guardians with them when they travel. These cars would return society to an era where children can travel similar to the way they used to freely on their bikes or foot without the risk of danger or extremely long distances. This would also revitalize a form of revolution in which machines are in control and more powerful than humans. “The disruptive technological advancements associated with the advent of autonomous vehicles may be overshadowed by the enormous social changes that will accompany a transition to a world in which humans relinquish control of their vehicles to artificial intelligence” (Pettigrew 2017). It could also bring back a younger working age since kids would be able to attend jobs since they would not need their parents to drive them to and from their shifts. Adolescents could reclaim a sense of independence without the reliance on adults. It would be a new and improved sense of separation from their parents because of the unlimited information they can access through the internet.
Some aspects of society which would be affected by autonomous automobiles are family dynamics and the power that children have in their local communities. AA would change the parent-child relationship because it would decrease the amount of dependence that the child has on their parents. “While auto-piloted autos will surely make life more convenient for many adults, they will be nothing short of revolutionary for adolescents (and their parents)” (Petrilli 2014). Advancements in technology are always trying to make life easier for people and continually push people to the next step. “Most adolescents are ready for independent mobility well before they are qualified to operate a car” (Petrilli 2014). This can be a difficult concern because the brains of adolescents develop at different paces and it is difficult to measure whether or not someone is ready to operate a vehicle. “Many parents let their 12-year-olds ride a train or city bus or a bike to school or a friend’s house; some even let their 10-year-olds do so. But of course, these kids can’t drive the family car. But soon they will. Well, not “drive.” But sit in the back as a robot takes them to school, or soccer practice, or karate class” (Petrilli 2014). This would be revolutionary for parents who no longer want to chauffeur their kids around every day.
Reversal
Autonomous automobiles have the potential to bring forth numerous enhancements that could greatly benefit the world. Unfortunately, a device bringing positive effects also includes the possibility of negative outcomes. Another component of the Tetrad model is reversal. This demonstrates the idea that the enhancements produced by the device have the capability of being reversed; resulting in unexpected dissatisfactions. When pushed to its limits, the artifact flips on its user; creating a new problem. Some of the problems resulting from AA would include liability issues, drinking age laws, mass transportation dangers in education facilities, and danger in local communities.
Additional aspects of society which would be affected by autonomous automobiles are education, mass transportation, legal issues, liability, and health insurance related to car accidents. There are many ethical issues related to AA because when accidents do occur, it is difficult to know who is at fault when self-driving cars are involved. Car crashes involving at least one AA would bring forth many liability issues. It goes beyond suing a person to sewing an entire company who manufactured the car that drives itself. “The human element of driving, however, is not without a solution. Worldwide, Google and other car manufacturers argue that autonomous vehicles will reduce the number of car accident fatalities and injuries resulting from human error because the computer controlling the autonomous vehicle does not get tired, intoxicated or distracted as does the human driver” (Thomas, 2016). Although this could be true, it is impossible to guarantee and could bring forth the possibility of malfunction, corruption, or override. “The law regarding autonomous vehicle liability, however, is unclear. As noted by one legal commentator, “while autonomous vehicles are likely to be much safer than their human counterparts, they will inevitably be involved in accidents” (Thomas, 2016). This may present controversies in legality and the need to implement laws and systems for dealing with repercussions from accidents involving AA.
Approaching the era of AA brings the likelihood of human injuries that could be caused by artificial intelligence. In an attempt to ease the minds of people and their concerns about health insurance, some companies have attempted to make promises ahead of time. “Volvo’s announcement that it will accept full responsibility for any accident caused by its driverless cars had brought several intriguing questions to light” (Autonomous 2015). Although Volvo makes this claim in advance, it is difficult to predetermine whether this is actually possible in real cases. “While Volvo’s commitment simplifies the process of establishing blame in the case of a crash, it doesn’t solve all the liability problems. It remains to be seen how Volvo will react in the event of an actual accident” (Autonomous 2015). Ultimately, predictions and promises do not mean anything until one follows through with them when it matters.
As the concept of being carried by self-driven cars is more seriously considered, it brings forth a number of questions and concerns. These include a possible change in the age of legal drinking, age restrictions for passengers riding in AA, driverless busses affecting the education system, and local communities being affected by a combination of manual-driven and AA on the roads. It is difficult to know how to set appropriate restrictions that differentiate between a riding age, driving age, and manual driving age. “How old must children be in order to be driven by a Google-bot? If they are old enough to walk to school (say, eight), is that old enough?” (Petrilli 2014). It seems like these decisions would vary between families, and some parents would have stronger opinions than others. “Would said children have any control over where the car goes, or would parents set the route in advance? (How might that work for 15-year-olds? What’s to keep the cleverer and more dexterous among them from hacking the instructions?) Can each family make these decisions? Or should states set the rules?” (Petrilli 2014) This is a challenging issue to set legal restrictions on because certain families may strongly disagree with the laws that the states decide to implement for AA.
Another question which could be raised is related to the drinking age. If teenagers were not technically driving their own cars, would the state laws lower the drinking age? (Teenagers have famously bad judgment, weak self-control, and proclivities toward recklessness.) But once Google becomes a designated driver, that rationale goes away” (Petrilli 2014). As of now, Uber and Lyft offer more freedom to people who want to drink and change locations. These services still require money and a sense of dependence. The vehicles need to be in range of them, have active drivers on duty at that time, and the person’s credit card needs to be connected to their account. If teenagers could summon their car to come get them, this could drastically impact views about an acceptable drinking age. “Furthermore, if a robot can drive teens around town more safely than teens themselves, might states push back the “manual-driving” age to 21 or later to wait until young people’s brains are really up to the task? Such a policy is politically infeasible now because of the interest in allowing those 16 and up to get themselves to their jobs. But with a computerized chauffeur, that’s no longer a problem” (Petrilli 2014). This offers another ethical debate which could cause dissonance between personal views and legal restrictions. The usage of AA generates a relevant concern affecting schools and education. As soon as driverless cars become normal, driverless busses will follow suit. “Already the National Highway Traffic Safety Administration is preparing to require “connected vehicle” technology on school buses (gadgets that allow vehicles to talk to one another in order to avoid crashes). Eventually, driverless buses will surely be seen as the safer alternative” (Petrilli 2014). This is concerning because it involves the lives of many children. Who is responsible for the death of young, valuable lives if the bus were to crash? Mass amounts of children could be arriving at school in cars without any adults in them and busses without any human driver. This leaves room for many things to go wrong. AA could also cause an uprising in local communities because there will there be a combination of autonomous cars on the streets with manual-driven cars. Even though autonomous cars may be proven to be safer when looked at on paper, are the risks for crashes still lower if half of the drivers on the road are real humans? Would it be safer to implement a strategy that goes all or nothing in regards to whether the drivers are robotic or human? Or can AA still be successful if they are integrated slowly into the roads? Since AA are a completely new invention that the world has never seen a glimpse of before artificial intelligence, it is a foreign and unfamiliar land. The full reversal of enhancements and unexpected dissatisfactions cannot be completely understood until they actually occur.
The use of autonomous automobiles can best be understood through the theory of relative advantage. Relative advantage “assesses the merits of innovation in relation to the idea, practice, or object it is to replace” (Quan-Haase, 2016). If consumers perceive that a particular technology will add value to their lives, it’s more likely to be adopted. When it comes to consumers and autonomous automobiles, there are many benefits in terms of consumers. For example, the use of fully autonomous vehicles will mean that transportation will be cheaper for those commuting. In addition, consumers will also have the opportunity to work on tasks or activities other than driving during their commute. This is particularly beneficial for individuals who have busy schedules, and are looking to boost efficiency. Also, the use of autonomous vehicles would give kids the chance to use this method of transportation, and get to places easier without relying on their parents. This would boost the independence in individuals under the age of 18, and allow them a method of transportation without having to have a license. Consumers will be focusing on these benefits and how it applies to their daily lives when considering using this technology in the future. Therefore, autonomous automobiles will become easily adopted into society as described by the theory of relative advantage.
Overall, enhancement, obsolescence, retrieval, and reversal are in a resonant, interchangeable relationship with one another because they are intertwined and complementary to one another. Each component depends on the others and draws from historical and social resources in order to develop predictive power in regards to the impact that the new technology will have on society. When analyzed using the tetrad model, it is evident that autonomous automobiles are likely to affect the future in a variety of ways. In the case of AA, the enhancement component demonstrates the ways in which they will solve problems and benefit society. Obsolescence depicts the erosion aspect of this new artifact on society and how AA will replace things of the past as it takes power. The element of retrieval explores the values, insights, and technology of the past that are being reincarnated because of the onset of AA. Finally, reversal addresses the possible negative outcomes and unexpected dissatisfactions that could result from the adoption of AA. This section also applied the theory of relative advantage and the idea of adding value to one’s life through the adoption of a new technology. The areas of business, local community, and liability were also discussed in terms of how autonomous automobiles will impact these specific areas of society in the future.
Forecasted Effects:
It’s difficult to predict how new technology will affect not only society but our everyday lives. Autonomous vehicles are a new technology that may impact Generation Z as well as Millenials much like the cell phone impacted their parents. It will be an entirely new way of transportation that will affect most everyone. There are certainly pros and cons that come with every new technology, and autonomous vehicles are no exception. And while it’s easy to pick apart the new technology, it’s more difficult to predict how it will impact our lives going forward.
Autonomous vehicles will impact every part of our life from our commute to work, to civilian safety, to public transportation and everywhere in between. When a technology has such a major impact on society and culture, there comes added problems pertaining to its adoption into the mainstream. Much like many groundbreaking technologies, it is very expensive in the beginning phases of adoption. According to Johnston and Walker, “ Optimists predict that by 2030, autonomous vehicles will be sufficiently reliable and affordable to replace most human driving, providing independent mobility to non-drivers, reducing driver stress and tedium, and be a panacea for congestion, accident and pollution problems” (2017). While optimists may say 2030 is a reasonable time frame for the adoption of self-driving cars, you may not want to hold your breath. Many “optimists” usually have some sort of stake or financial self-interests at hand with the given technology. Meaning 2040 or 2050 may be a more reliable time frame for full adoption into society. “[Optimists] often overlooks significant obstacles and costs. Although vehicles can now operate autonomously under certain conditions, many technical problems must be solved before they can operate autonomously in all conditions, and those vehicles must be tested, approved for general commercial sale, affordable to most travelers, and attractive to consumers. Motor vehicles last much longer and cost much more than personal computers,cameras or telephones, so new technologies generally require many years to penetrate vehicle fleets. A failure by a camera, telephone or the Internet can be frustrating but are seldom fatal;system failures by motor vehicles can be frustrating and deadly to occupants and other road users. Autonomous driving can induce additional vehicle travel which can increase traffic problems. As a result, autonomous vehicles likely take longer to saturate their markets and will provide smaller net benefits than optimists predict” (Litman, 2018). Below is a chart provided by Litman (2018) in his book Autonomous Vehicle Implementation Predictions: Implications for Transport Planning depicting a potential timeline.
There are already self-driving, and partially autonomous cars on the road today. Most notably, the Google self-driving car. There are both advantages and disadvantages that come with this new technology. One major advantage of having roads with only autonomous vehicles on them would be passenger safety. According to Fagnant and Kockelman, “because human error contributes to 90% of crashes, autonomous vehicles will reduce crash rates and insurance costs by 90%” (2013). Removing human error from the occasion would be a major advantage. Deaths due to drunk driving, distracted driving, or falling asleep at the wheel would be a thing of the past. However, just like with any computer, it can malfunction. What would happen if an autonomous vehicle malfunctioned, and injured or killed someone? Who would become liable? Who pays for the damages? These are all of the extra things that make the adoption of this technology more difficult than say communication technologies. Along these lines, another disadvantage presents itself. These cars run on computer chips, and just like any computer system, they can be hacked. A skilled hacker could take control of a car and commit murder, or carry out assassinations.
The biggest obstacle to having these cars on the road in the near future, however, is the cost of these vehicles, as well as legislation. Money always seems to be the limiting factor with the incorporation of new technologies. In a perfect Utopian society, all the old cars would be taken off the road, and new, autonomous ones given in their place. Obviously, this isn’t realistic and many argue that initially, having self-driving cars will be much more expensive. “For the foreseeable future (one to three decades) autonomous vehicle costs will probably average (total annual costs divided by annual mileage) $0.80-$1.20 per vehicle mile, which may eventually decline to $0.60-$1.00 per mile, which is somewhat more expensive than human-operated vehicles’ $0.40-$0.60 per mile average costs” (Stephens, 2016). That’s not to mention all the additional maintenance costs as well. “Autonomous vehicles will require additional equipment and services,” says Litman (2018). “Since failures could be deadly, autonomous driving systems will need robust, redundant and abuse-resistant components maintained by specialists, similar to aviation service standards, further increasing costs. To monitor passenger behavior, autonomous vehicles will also require in-vehicle security cameras and enforceable behavior rules, plus frequent interior cleaning and repairs” (Broussard, 2018).
For every negative, or potential headache this new technology presents with implementation, there are amazing implications that could make our lives so much simpler. Imagine not having to sit in traffic anymore. Autonomous vehicles on a macro-scale will allow them to communicate with one another in a fraction of a second to reduce traffic jams, thus allowing your commute to be quicker, more efficient, and theoretically gas-saving. Below is a chart from Litman (2018) on how Autonomous vehicles can help reduce emissions.
There are a lot of potential pitfalls this technology presents. Some may find it expensive, a hassle to implement, and even a threat to their livelihood. If autonomous vehicles do happen, then a lot of people are going to lose their jobs. There are millions of people from around the world that make a living on transportation including: truck drivers, taxi and Uber drivers, public transportation drivers just to name a few. Another major caution would be the safety of driving in inclement weather. There needs to be a great leap in the sensor technology to ensure that driving in snow or rain is safe. This is a major concern not just with autonomous vehicles, but all AI. Can a machine adapt to certain conditions that may not show up on their sensors? For example, in bad weather, human drivers all slow down so they don’t hydroplane, or hit an ice patch and lose control. How would an autonomous vehicle react to dangers that may not be able to be measured in their programing? Like I mentioned before, there are pros and cons with all technologies. Here is another chart of some more pros and cons given to us by Litman (2018).
After examining all the positives and potential negatives this technology offers, our recommendation is that we think autonomous vehicles will serve a useful purpose in the future, and the pros far outweigh the negatives. We came to this conclusion for four simple reasons. First, we think that having self-driving cars will be much safer in the future, and nothing is more important than saving lives in our assessment. According to the US National Highway Traffic Safety Administration, over 1.3 million people are killed annually on the roads around the world with several million seriously injured. Most of these accidents (over 90%) are caused by human error. Next, we concluded that the convenience of having self-driving cars which would reduce traffic jams, and cause your commute to be more efficient and use that time to work or get other tasks done. This is a major societal effect that we took into consideration during our assessment. People, and Americans especially, are always looking for more hours in the day. Having autonomous vehicles would aid in that. Third, having self-driving cars, as mentioned in exhibit 8 would substantially reduce the numbers of cars in use. To make self-driving vehicles a reality, the costs, in the beginning, would be far too great for the majority of people to buy. This would cause people to “subscribe” as one expert put it to a company with a fleet of these vehicles. You would then pay to use their services (have it pick you up, drop you off, etc.) and there would be no need for people to have their own car. This has many added benefits to it. Not only would it clear up garage space, but it would be more affordable too. Also, it would clear up the streets in residential neighborhoods making it safer for children to play outdoors. Cars today spend a majority of their time unused, autonomous vehicles would fix that. Lastly, with the reduction of total cars on the road, and the autonomous vehicles being electric, it would significantly reduce the pollution and harmful emissions that are released by gas-powered vehicles today. This would have a major impact on the preservation of the Earth’s ozone layer, as well as the health and safety of people around the globe — another major societal effect. In conclusion, we feel that if the technology is safe for autonomous vehicles to transport us they should be used and taken advantage of. Collectively, we think the positives outweigh the potential pitfalls autonomous vehicles present.
Sources:
Anderson, James M., et al. Autonomous Vehicle Technology: a Guide for Policymakers. Rand Corporation, 2016.
Autonomous car liability called into question. (2015). Professional Engineering, 28(11), 7. Retrieved from http://ezproxy.bethel.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=keh&AN=111191536&site=ehost-live&scope=site
Beltz, B. (2018, October 29). 100 Car Accident Statistics for 2019. Retrieved January 24, 2019, from https://safer-america.com/car-accident-statistics/
Benefits of Renewable Energy Use. (2017, December 20). Retrieved January 24, 2019, from https://www.ucsusa.org/clean-energy/renewable-energy/public-benefits-of-renewable-power#.XEoeAuHYqhc
Bimbraw, Keshav. (2015). “Autonomous Cars: Past, Present and Future — A Review of the Developments in the Last Century, the Present Scenario and the Expected Future of Autonomous Vehicle Technology.” ICINCO 2015–12th International Conference on Informatics in Control, Automation and Robotics, Proceedings. 1. 191–198.
Bosankic, L. (2017, July 17). How Consumers’ Perception of Autonomous Cars will Influence their Adoption. Retrieved January 24, 2019, fromhttps://medium.com/@leo_pold_bhow-consumers-perception-of-autonomous-cars-will-influence-their-adoption-ba99e3f64e9a-
Charlie Johnston and Jonathan Walker (2017), Peak Car Ownership: The Market Opportunity for Electric Automated Mobility Services, Rocky Mountain Institute (www.rmi.org); at http://bit.ly/2rhJRNi.
Daniel J. Fagnant and Kara M. Kockelman (2013), Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations, Eno Foundation (www.enotrans.org); at www.enotrans.org/wp-content/uploads/wpsc/downloadables/AV-paper.pdf.
Huang, Sam. “How the Autonomous Car Works: A Technology Overview.” Medium.com, Medium, 25 Apr. 2018, medium.com/how-the-autonomous-car-works-a-technology-overview-5c1ac468606f.
Jurgen, R. (2013). Autonomous Vehicles for Safer Driving. Warrendale: SAE International.
Lavasani, M., Jin, X., & Du, Y. (2015). Market Penetration Model for Autonomous Vehicles Based on Previous Technology Adoption Experiences. 1–40. Retrieved January 24, 2019, http://pdfs.semanticscholar.org/5a56/2bde7972c6cdda6c443ae87c4900bd1a41ad.pdf.
Levine, B. (2018, August 17). Research Predicts Adoption Rates of Connected Autonomous Vehicles. Retrieved January 24, 2019, from
Litman, T. (2018). Autonomous Vehicle Implementation Predictions
Implications for Transport Planning. Victoria Transport Policy Institute.
Loughran, J. (2018, February 21). Driverless vehicles to deplete demand for fossil fuels by 2040,
BP predicts. Retrieved January 24, 2019, from https://eandt.theiet.org/content/articles/2018/02/driverless-electric-vehicles-to-deplete-global-demand-for-fossil-fuels-by-2040-bp-predicts/
Mims, C. (2017, May 08). Keywords: How self-driving cars could wipe out uber. Wall Street Journal Retrieved from https://search-proquest-com.ezproxy.bethel.edu/docview/1895823238?accountid=8593
Nieuwenhuijsen, J. (2015). Diffusion of Automated Vehicles (Master’s thesis, Delft University of Technology, 2015) (pp. 1–120). Delft: Connekt.
Petrilli, M. J. (2014). Coming soon: “Car-key kids”: what autonomous automobiles will mean for adolescence. Education Next, 14(2), 87. Retrieved from http://link.galegroup.com.ezproxy.bethel.edu/apps/doc/A377574733/PROF?u=clic_bethel&sid=PROF&xid=916ad01a
Pettigrew, S. (2017), Why public health should embrace the autonomous car. Australian and New Zealand Journal of Public Health, 41: 5–7. doi:10.1111/1753–6405.12588
Quan-Haase, Anabel (2016). Technology and Society: Social Networks, Power, and Inequality.Ontario, Canada: Oxford University Press. ISBN: 978–0–19–901471–2
Stephens, T. (2016), Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles, Technical Report, National Renewable Energy Laboratory (www.nrel.gov); at www.nrel.gov/docs/fy17osti/67216.pdf.
Thomas, J (Summer, 2016). COMMENT: Putting Programmers in the Driver’s Seat: State Tort Systems Applied to Autonomous Automobiles. University of Detroit Mercy Law Review, 93, 553. Retrieved from https://advance-lexis-com.ezproxy.bethel.edu/api/document?collection=analytical-materials&id=urn:contentItem:5KYV-BHC0–00CV-81W7–00000–00&context=1516831.
Zhou, Chengmin, et al. “Architecture Design and Implementation of Image Based Autonomous Car: THUNDER-1.” ProQuest, 3 Mar. 2018, link-springer-com.ezproxy.bethel.edu/article/10.1007/s11042–018–5816–9#citeas.
