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Long before the autonomous vehicles even existed as we think of them today, Leonardo da Vinci conceptualized, designed and possibly even made the first autonomous vehicle in 1478. Outlined in a single page of drawings is the design of a cart which would have been powered by large coiled clockwork springs, able to propel itself 130 feet along a predetermined path as defined by the user. However, despite being extremely interesting, because it was a cart and not intended for the transport of humans, and that the drawing remained unknown to the public until recently, it cannot be considered a precursor to the autonomous vehicles discussed below.

The first recorded concept of autonomous road vehicles can be found in ‘The Living Machine’, a short story by David H. Keller written in 1935. The author even discusses the potential of increased levels of safety far before the technologies emerged which will make them a possibility. The first visualizations produced for the concept of an autonomous road system were at the Futurama exhibit by Norman Bel Geddes at the 1939 World’s Fair in New York where the automobile maker talked of “‘abundant sunshine, fresh air and fine green parkways’ upon which cars would drive themselves”. As this was long before the days of computing the vehicles were limited to pre-determined paths because the technology was to be embedded into the roads.


General Motors (GM) began to take interest in the area in the early 1950s and in 1953 a collaboration between GM and Radio Corporation of America (RCA) lead to the development of the first full-size autonomous car. Using a scale model of a vehicle and section of road they experimented with how electronics could be used to steer vehicles and maintain a safe distance from the car in front, forming the basis for autonomous driving systems. They continued their contribution to the field by producing prototypes for models such as Firebird I, 2 and 3 which introduced many technologies and features that are considered innovative today, such as auto-piloting.

Little more happened until 1977 when, after spending years developing a dynamic route guidance system called Comprehensive Automobile Traffic Control System (CACS), Dr. Sadayuki Tsugawa and his colleagues at Tsukuba Mechanical Engineering Company in Japan produced a vision-based ‘intelligent vehicle’ which was the first truly road capable autonomous vehicle. Through the use of two cameras and an analog computer, the vehicle could achieve speeds of 18.6 mph and drive for 50 meters without interference, not so impressive by today’s standards but a breakthrough at the time.

In 1980 Ernst Dickmanns and his University of Bundeswehr team (located in Munich, Germany) re-engineered a Mercedes Benz van which they named ‘VaMoRs’. Through the use of computer processors and cameras, it could process in real-time sequences of images such as traffic signs and control the vehicle (acceleration, gears, and braking) accordingly. For safety reasons, the initial experiments in Bavaria took place on streets without traffic where the vehicle reached a new record autonomous driving speed of 31.1 mph, and by 1986 it was completely self-driving. Encouraged by Ernst Dickmann’s success, the PROMETHEUS (Program for European Traffic with Highest Efficiency and Unprecedented Safety) research program was initiated by the EUREKA organization in 1987. PROMETHEUS was an eight-year project run as a cooperative venture of several European motor manufacturers including Daimler-Benz AG along with electronics producers and suppliers, universities and institutes. The PROMETHEUS project set out to increase traffic safety, improve environmental compatibility, minimize energy consumption and enhance drivers’ level of comfort.

In 1987 the newly-equipped VaMoRs, outfitted with two cameras, eight 16-bit Intel microprocessors, a variety of other sensors and new software drove more than 55.9 mph for roughly 12.4 miles, setting new records for both. The project ended in 1994 with a final presentation in Paris of a re-engineered 500 SEL Mercedes named ‘VaMP’. With its two cameras processing 320 by 240 pixels per image at a range of 100 meters, the car drove 620 miles at up at 81 mph in simulated traffic, even capable of processing whether it was safe to change lanes.

The following year Dickmann’s team sent a Mercedes S-Class, named ‘VITA’, from Munich to Odense, Denmark, and back with 95% autonomy. This set new records with a trip of more than 994.2 miles at a maximum speed of 112 mph. Also in 1995, Carnegie Mellon University robotics department developed a vehicle they called ‘NavLab 5’, a modified 1990 Pontiac Trans Sport, which they sent from Pittsburgh to Los Angeles on a trip entitled ‘No Hands Across America’. The vehicle’s add-ons included a portable computing unit, a windshield-mounted camera, and a GPS receiver, the first autonomous vehicle to utilize the technology. The car set a new autonomous driving rate of 98.2%, needing only a little human input for obstacle avoidance.

The next landmarks in self-driving cars were established in trials set by the Defense Advanced Research Projects Agency (DARPA) in America. In 2004 DARPA set an open challenge with a prize fund of $1 million for an autonomous vehicle to be driven 150 miles through the Mojave Desert in California, an uneven terrain that would serve as a far greater challenge than the smooth roads autonomous vehicles had been tested on traditionally. In this first competition, there were fifteen entrants of which none completed the challenge, and the greatest distance traveled was just 7.3 miles which were set by Carnegie Mellon’s ‘Red Team Racing’ vehicle named ‘Sandstorm’, a re-engineered Humvee.

Not dissuaded by the relative unsuccess of the first competition, a second was held in 2005 with a greater prize of $2 million that lured thirty-two entrants of which included “three tunnels, more than 100 turns and navigating a steep pass with sharp drop-offs”. Stanford University won the first place prize, completing the course in 6 hours and 54 minutes with a re-engineered Volkswagen Touareg called ‘Stanley’.

In 2007 DARPA further increased the difficulty by staging a 60-mile race in an urban area, which only eleven of the 89 entrants managed to finish. Carnegie Mellon’s ‘Tartan Racing’ team took the first place prize with a time of 4 hours and 10 minutes using a converted Chevrolet Tahoe named ‘Boss’. Arguably the greatest trip by an autonomous vehicle to date was performed in 2010 when the Artificial Vision and Intelligent Systems Laboratory (VISLAB) at the University of Parma, Italy, sent a vehicle from Parma in Italy to Shanghai in China, traveling 9,900 miles through nine countries in 100 days.

Also in 2010 Google began their work in the field, investing not only financially but also their knowledge of route mapping and programming skills they developed in creating ‘Google Maps’. Since then they have set themselves and accomplished numerous trials, such as traveling 100,000 miles on public roads, and that figure is now well over 500,000 miles tracked. Since 2010 many automotive companies and research groups have been quietly working in the field, with numerous press releases on new features and milestones and autonomous features being slowly integrated into new car models. An example of which is the autopilot mode found on the new ‘Tesla D’ model that can take control on highways, park itself in your garage and even intervene when it thinks it can do a better job of avoiding an accident than the driver

The technologies for autonomous vehicles

There are a wide variety of technologies that have enabled vehicles to attain the level of autonomy that we are currently capable of utilizing, as well as others that have been superseded by newer technologies. Outlined and explained in this section are all of the relevant technologies currently being utilized and how they contribute to the system as a whole. First and foremost, the ability for the vehicle to ‘see’ other cars, road signs, obstacles, animals and people is mandatory at this stage of autonomous vehicle development, while there will still be manually driven vehicles on the road. The ‘seeing’ of the car is made capable of a range of sensors, one of the most important of which is a camera or pair of cameras. Depending on the manufacturer; either a single front-facing camera, a front, and rear-facing camera or two front-facing cameras. Due to the rise of smartphones, the clarity of images produced by digital cameras has increased exponentially in recent years and the price per unit has dropped dramatically. The aspects of the image which are relevant in assisting the car from the cameras are the objects and their direction of movement which are used to make decisions for the movement of the car.

Another important technology is ‘LIDAR’, a name created as a portmanteau of ‘light’ and ‘radar’, which is a combination of laser-focused imaging and radar’s ability to determine distances by measuring the time it takes for the signal to return. Lidar has a wide field of vision of around 120 degrees and a single roof-mounted rotating unit can be used to sense objects 360 degrees around the vehicle. In combination with the ability to determine what an object is and in which direction it is traveling from the camera data, LIDAR enables the object’s distance and time of impact to be added to the data to be used to influence decisions for the vehicle. Radar, an older technology that was developed in the 1930s, is used to augment the camera and LIDAR data by emitting and receiving data about objects, primarily other vehicles, at further distances from the vehicle than cameras and LIDAR can.


Indifference to being able to influence rapid decisions like LIDAR and cameras can, radar is used more for tracking the distance of the vehicles in front of, behind and parallel to (such as at a crossing) the vehicle in order to influence the speed of the vehicle or braking if a car was to pull out in front. In combination with cameras and LIDAR, the data from radar technology enables the vehicle to be aware of and able to react to objects and situations both close in range to the vehicle and also further in range, both of which are necessary in order to provide the safest drive. The final sensor is a position estimator located on one of the vehicles’ wheels which contributes to the collection of sensory data by giving a more accurate understanding of where the vehicle is in relation to objects. It does this by being able to determine distances traveled based upon the number of rotations (or part rotations) of the wheels.

However, the collection of data from these sensors alone can do nothing to influence a vehicle’s actions but a central processing unit (CPU) is required to process the data and make informed decisions. The computer with its CPU functions akin to the brain of a human which processes human senses and determines suitable reactions to the information. This is all made possible by ‘computer vision’ which is the method of processing, analyzing, and understanding objects and producing decisions based upon them. Computer vision has been made increasingly more accurate and reliable through the combination of developments in algorithm-based software programming and also the advancement of microprocessors that are enabling ever greater computing power in an ever-smaller package and at an ever-decreasing price. To put into context how far computing power has come we can compare the computing unit from the first computer-based autonomous vehicle ‘VAMOS’, one which took up half of the entire van’s interior, to the most recent computing unit – the ‘Nvidia Drive PX’ debuted at Computer Electronics Show (CES) 2015 which fits into the palm of the hand and costs orders of magnitude less. The Nvidia Drive PX with its 1 teraflop of processing power is also thousands of times more powerful than the processing capability of the computer in ‘VAMOS’.

That covers the how of the automation of the vehicles’ driving, but in addition to that Global Positioning System (GPS), a space satellite navigation system which provides a location within 3 meters distance and 100 nanoseconds of time anywhere on the Earth, is required to control where the vehicle travels. GPS enables autonomous vehicles to remain on what is considered suitable roads and to not stray onto pedestrian paths or unsuitable or dangerous ground. It also enables vehicles connected with a central database to avoid one another, and for real-time traffic situations and roadworks to be known to the vehicle so that traffic jams and blocked roads can be avoided.

Finally, high-speed and widely available wireless internet connections like 4G and its successors to come (such as 5G which is planned for the early 2020s), and other wireless internet technologies like WiFi Direct complete the package. These high-speed forms of data transfer will be used for the transfer of information between vehicles which will be necessary, for example, for a vehicle to know whether a parked vehicle ahead is about to pull out, or the distance to give a vehicle based on the vehicle type.

The benefits and dangers of autonomous vehicle adoption

An autonomous vehicle is going to profoundly change life on Earth in many more ways than the obvious, in so many ways that in order to make it easier to digest and also for easier referencing should only one area be of interest, the following section has been split into the following sub-sections.

The effect of an autonomous vehicle on human safety

How autonomous vehicles will reduce deaths, injuries and people made disabled from vehicle crashes by reducing the possibility of crashes to near zero and reducing the damage of unavoidable crashes. Undoubtedly the greatest impact that autonomous vehicles will have on humanity is increasingly reduced, as more and more vehicles become autonomous, the number of lives lost in road accidents. With road traffic accidents currently causing 1.24 million deaths a year worldwide and that figure expected to reach 1.9 million per year by 2020, as well as it is the most common cause of death for people between the ages of 15 and 29, it is clearly an area in which a reduction by any means will be world-changing.

Using statistics regarding the causal factor of car accidents in the US Eno Centre for Transportation claim that 93% of all motor vehicle crashes are due to human factors which could be eliminated by the use of autonomous vehicles. While it would be difficult to determine exact percentages due to the death of the driver, it can easily be deduced that causal factors such as driving under the influence (of alcohol or drugs), speeding, distraction, fatigue or sleepiness would be eliminated. These factors are negated by autonomous vehicles because the vehicles’ decisions are controlled by software algorithms based on data from a variety of sensors, none of which can be affected by the aforementioned factors and also because computer processors’ reaction time is increasing faster than human reaction time. As can be seen, due to the autonomy of the vehicles, the age of the driver is no longer a relevant factor. In an ideal scenario with Level 4 autonomy deaths will be reduced to near zero, however, in semi-autonomous phases, it may be possible that the number of deaths is in fact greater than or equal to manual drivers. Thus there is a strong argument for a push toward higher levels of autonomy rather than an intermediary period of semiautonomous vehicles. Further to the deaths caused by car accidents, there are 20-50 million more people who are injured every year, many of whom are disabled as a result of their injuries. These injuries and disabilities can also be eliminated by the adoption of autonomous vehicles. Therefore we can deduce that autonomous vehicles will reduce the number of deaths worldwide by millions, substantially reduce demand on hospitals, and drastically decrease the number of people made disabled in the world.

An autonomous vehicle can also potentially save lives, lead to decreased severity of injuries and people disabled as the result of injuries from other types of an accident through the use of autonomous ambulances. Due to being able to drive faster and for other vehicles to automatically (when all vehicles are autonomous) make way for them, the time until paramedic assistance is available is reduced. Furthermore, the number of specially trained members of staff can potentially be reduced due to not requiring a driver, and also the capacity of the ambulance’s interior be increased due to not requiring a front cab. The increased capacity can potentially enable the carrying of more medical equipment and other necessities for aiding the saving of lives.  However, these points aside, there are a number of issues that must be first addressed in order to ensure that the safety of autonomous vehicles is maximized.

The first of these issues is that the mapping systems used (such as Google Maps and Apple Maps) must be perfected before allowing self-driving cars to follow them without the option of human interference. This is because a number of potentially life-threatening issues have arisen from people following mapping systems manually, yet they were able to avoid them because they were in control of the vehicle. If the vehicles in these scenarios were self-driving with no option to manually override, as autonomous vehicles will eventually be, then they could have easily resulted in death. Two examples of this are from Apple maps; one where drivers were directed to drive through an airport’s runway, and another where drivers were directed deep into the Australian outback to the wrong location of a similar name where if the driver was unaware of the wrong direction being given then they could have easily run out of petrol and died from dehydration in the outback. Without a manual override, this is what would happen with an autonomous vehicle that was auto-piloting and ran out of power when the vehicle was far into the outback. Other concerns regard the use of GPS for the directing of vehicles. The first being that the use of GPS scrambling equipment which can be easily purchased for as cheap as $20, could easily be used to knock an autonomous vehicle off course, or even worse into other vehicles, people, or buildings. The second, more worrying issue, is that GPS can be hacked with fairly basic and affordable equipment. This is made possible by using the software on a computing device to send out spoof signals which can direct a vehicle wherever the controller wants it to go. This was demonstrated on a 210-foot yacht in the sea in 2013 and proves it would be just as easy to perform on-road vehicles.

Even if the issues regarding GPS jamming and hacking are solved completely, there are yet more and even more threatening related issues that need to be dealt with. That includes the potential for vehicle systems to be hacked, which can be done one of two ways, either through directly hacking the computer in the vehicle or by hacking the system which the vehicle is connected to. With access granted to a vehicle’s controls through hacking, problems such as increasing or decreasing acceleration to crash the vehicle, steering the vehicle into a crash, and driving the car to a location and locking the doors to trap people, to give a few examples, are made possible. There are no clear-cut solutions to these problems now except advancements in computer security and greater levels of encryption. Even then though it would still be theoretically possible to hack into a vehicle, only requiring a greater processing power at the end of the hacker or more time for the hacker’s computer to get into the targeted vehicle’s system.

Those issues aside, they will not be commonplace and if someone intends to kidnap and/or murder they will attempt to do so by any means possible so it should not really be an argument that delays the adoption of autonomous vehicles. There are a number of solutions to the matter of GPS and vehicle system hacking being discussed, with the most likely replacement being the ground-based “LORAN” system which was developed during World War II. Nevertheless, the greatest and most pressing issue with autonomous vehicles and human safety is the ‘Who?’ question. In complex situations where there is no way to avoid all damage to human safety, who will be decided as the receiver of the damage? What variables will the software use to make the decision be based upon? The number of people injured? The age of the people that will be injured? The level of contribution to society of the people who will be injured? These questions are yet to be considered by autonomous vehicle makers and will likely require massive external resources and time to be spent on the topic by governments.

It is likely that the Disability Adjusted Life Years (DALY) calculation will be used initially, but even that has a wide variety of issues to be addressed before it could be, and they cannot be easily answered. These include; that the data used in the calculations are now 25 years old and could have changed fairly dramatically since, that it places greater value on men lives over women’s’ due to “biological differences in survival potential”, and that older and younger peoples’ lives are less valuable than middle-aged peoples’, to give a few examples. The most worrying outcome for such a system is that, because the system will be defined by a governing body and not the individual vehicle owner, the vehicle could be programmed to kill the very driver itself [35]. Of course, none would want to buy a vehicle with the thought that it could be programmed to kill the owner so that could be an issue that affects adoption if it is ever even made clear to consumers. Even if such a system was agreed upon and implemented then it would still be open for the potential to be abused. For example, a person could hack their vehicle’s computer and set it to be seen by other vehicles as a school bus full of children, and then in the case of a crash with a family with two children it may define that the family is to take the brunt of the damage when in fact the other vehicle actually only contains an elderly man. So it is apparent that a lot of work would have to be done to prevent such possibilities also.

The final issue is that, especially during the period of adoption when both manual and self-driving cars will be on the roads, of who will be to blame if vehicles do crash and cause damage to humans? Again, there’s no clear answer here and in the early stages of evolution of the software controlling the vehicles it could be argued to be the programming, but then is the programmer to be held responsible? The driver clearly cannot ever be held responsible but this paper does not aim to address these complex questions, instead of making them aware for the reader to be aware of their complexity and lack of an objective solution to them.

The economic impacts of an autonomous vehicle.

How self-driving cars will reduce money spent on insurance, reduce the cost of vehicles due to a lower crash survival specification, reduce fuel wastage in congestion and increase the GDP of countries by enabling people to work in transport. The adoption of autonomous vehicles is going to affect both national and international economies dramatically, through many avenues. The effects will mostly be beneficial but the potential net job loss in positions that have historically required human drivers to perform is very concerning. The exact figure of the total jobs which will be displaced is difficult to calculate accurately, but there were, for example, 297,000 registered taxi and private hire vehicle drivers in the UK in 2013 and 233,000 taxi drivers and chauffeurs in the US in 2012 which are all at risk of being displaced.

In a survey performed by the Open Roboethics Initiative, 75% of respondents believe that more jobs will be displaced than created, and surprisingly 19% believe that more jobs will be created than displaced. Ultimately, advancements in robotics are going to affect all job industries, and have already done so for the past 60 years with manufacturing and fabrication jobs being replaced by machines and robots and self-service checkouts replacing cashiers. We have coped thus far with this by evolving our focus on training and education to prepare people not for less skilled jobs but more service-based technical jobs. This is not a new phenomenon and therefore should not be a limiting factor in the adoption of autonomous vehicles.

Chunka Mui discusses this problem on Forbes’ technology blog by comparing it to his father’s laundry industry which was put out of business by the rise of domestic washing machines. He rhetorically asks; “Should we have banned washing machines, or taxed and regulated them heavily, to keep my father’s hand laundry viable? Should we stop driverless cars from closing off opportunities for those in numerous other job categories?”, in order to point out the ridiculousness of banning or somehow slowing the adoption of autonomous vehicles due to job losses. He finishes by stating; “What we cannot do, however, is to allow the deaths, injuries, and destruction to continue just to protect jobs.”, insisting that human lives and safety are more valuable than the resulting loss of jobs. The second industry which will most be affected is the insurance industry. To put into context the amount of money spent on remedying car accidents an estimate carried out in the USA in 2000 suggested that the economic cost of road traffic crashes was approximate $518,000,000,000 per year and national estimates place the cost between one and three percent of their gross national product. Due to the greatly reduced quantity and eventual near elimination of road accidents, combined with drivers no longer being responsible for such accidents, insurance will become a thing of the past. This will undoubtedly affect insurance companies and the economies of many countries, but more importantly eliminate the financial impact on families which “has been shown to result in increased financial borrowing and debt, and even a decline in food consumption”.

Self-driving cars, in part due to being electric fuelled rather than petrol-fuelled, will also be cheaper to produce than current vehicles. One reason being that they will no longer require complex engines which add to cost, but also because the base for autonomous vehicles (containing all motors, sensors, and batteries) will be able to be standardized and mass produced, reducing the price dramatically. Another factor in this will be a shift to manufacture in China and other countries cheaper to manufacture in and more competitors entering the market than the current automotive market. Autonomous vehicles will be more expensive than normal vehicles for early adopters, but these costs will be passed to the consumers eventually and result in cheaper vehicles than current fossil fuel vehicles. Due to this automotive manufacturers will see a boost in sales and profit in the period following the availability and adoption of autonomous vehicles, however, this will only be for a period of time before a decline. This is because vehicles that currently spend 96% of their time idle while sitting in the car park at work or overnight could eventually be 96% active and thus the world would require fewer vehicles. One reason is that homeowners will no longer require more than one car as a single vehicle could take one member of the family to work and then return to take the children to school, for example, and in the longer term, a single a vehicle could be shared by an entire extended family. Therefore if 20 times fewer cars are required then 20 times fewer cars need to be produced and this will profoundly affect automotive vehicle manufacturers’ financial income, and thus many countries’ economies are heavily supported by automotive manufacturing, such as the UK. This potential reduction in vehicles has been confirmed by a study by Massachusetts Institute of Technology which concluded that the number of vehicles used in Singapore currently could be reduced to just one-third of that figure through the use of connected autonomous vehicles. This trend will extend to regular bus services and taxis also as has been shown by a Columbia University study which concludes that New York’s fleet of 13,000 yellow cabs could be replaced with just 9,000 autonomous cabs, be more frequently available and cheaper for the consumer.

Furthermore, a trial conducted by Ecole Polytechnique Federale de Lausanne has shown that the use of autonomous vehicles in public transport can reduce costs by 40-60%. In their case study they showed that through the use of ‘Navia’, an autonomous shuttle bus by Induct Technology, there are “40 percent cost savings over its regular shuttle service with a driver”. The train industry will also see a large decline in commuters due to their inability to compete with autonomous vehicles on price, and also because of their comparative inconvenience. Randal O’Toole, a Senior Fellow at the Cato Institute in Washington, states that the idea of a “sweet spot” of traveling between 100 miles and 600 miles that trains currently full will be eliminated by the availability of autonomous vehicles that will enable the user to have the use of their vehicle at the end destination. This has caused people to show concern for the plans for new and extremely expensive train lines that are planned to be built within the next 15 years, including the HS2 line which will cost Britain £42.6 billion and the Brisbane to Melbourne line which will cost Australia $114 billion AUD [45]. Building these as planned while ignoring the impacts that the adoption of autonomous vehicles will bring could be a waste of taxpayers’ money, and extremely harmful to the economies of the countries in question.

Fuel savings as a result of the adoption of autonomous vehicles from congestion avoidance in the US, as calculated by Morgan Stanley Research. The money will also be saved for consumers because autonomous vehicles will be able to drive faster, use less fuel by taking the most efficient route, by avoiding congestion, and also because electricity is increasingly cheaper than fossil fuels like petrol due to advancements in and the adoption of renewable energies such as solar and wind power. Due to no longer requiring to pay the salaries of delivery drivers, cheaper fuel prices and also because autonomous vehicles are able to drive 24 hours a day, the delivery of products should be cheaper which will result in cheaper products for consumers. For example, in the US there are currently 1.7 million people employed as delivery drivers on a median salary of $38,200 a year and this could all be negated.

Due to driving no longer requiring focus, and because people can sleep and relax in autonomous vehicles, we should also see reverse urbanization from major cities. This will affect the world economically by a better distribution of spending in urban and rural areas, and by decreasing the gap between the city center, suburban and countryside property prices. Finally, the adoption of autonomous vehicles could potentially increase the GDP of countries dramatically by enabling employees in the white-collar industry to work on the way to and from work by reading and responding to emails, receiving and making phone calls and doing other computer-based work. The value that this ability to work in-car has been calculated to be worth $422 billion a year in the US by Morgan Stanley Research.

The effects of autonomous vehicle on quality of life.

Autonomous vehicles will increase the quality of life by enabling people to have more free time to partake in leisure activities and relax, and also increase human health by removing stress from driving. The third area which will greatly be affected by the adoption of autonomous vehicles is that of human health and quality of life. The most prominent of these is the increased diversity of people who will be able to travel independently, this is for both people who have been prevented from driving by law and people prevented from getting around due to physical disability. Some examples of people who will be able to get around independently by the adoption of autonomous vehicles include:
-those too young to drive under current laws, and those considered too old
-people considered too disabled to drive (e.g. those with visual impairment and the blind, those who suffer from epilepsy or strokes)
-people who could not afford to learn to drive, because autonomous vehicles will eliminate driving lessons and tests which are currently expensive
-people who could not afford to drive because of the vehicle and/or insurance costs
-those banned from driving for reasons related to manual vehicles, such as driving under the influence of drugs or alcohol, speeding, reckless driving, etc.
-those who have simply never had the time or ability to work towards and obtain a driving license

To put into context some of these demographics, consider that there are 39 million blind and 246 million severely visually impaired people in the world and 50 million epilepsy sufferers, and that 25.79% of the world’s population is under the age of 15 so the amount of people that will be enabled on the road alone is potentially billions. The second most prominent factor regarding human health and quality of life is the increased free time which will be provided to people, both through the faster transport speeds enabled by autonomous vehicles and also from the ability to do other things while in transport.

This free time can be spent partaking in leisure activities and relaxing and the removal of the need to focus on driving will also lead to greater physical and mental health because stress caused by driving has been proven to attribute to cancer among other problems. Other disorders and that will be reduced by autonomous vehicles are the negative health impacts that are a result of fossil fuel fumes which include cancer, asthma, diabetes, and cardiovascular disease. To put into context how much time of their lives people spend driving consider that, according to the BBC, in Britain “the average motorist now spends three full years of their life driving” and drivers “spend more time driving than socializing”. Allianz Insurance adds to this by making the claim that “97% of us spend up to 15 minutes extra on each journey just looking for somewhere to park our car. This equates to Brits wasting over 8,325 hours in a lifetime looking for a parking space”. However, this free time to do as one likes will also have negative effects on human health and quality of life, because it will not be illegal to drive under the influence of drugs or alcohol in an autonomous vehicle it is likely that their abuse will become more common.

The ability to reduce the number of vehicles on the road, as mentioned in the previous section, is an area that Michael E. Arth has also written extensively on. His calculations led him to state that the world could reduce the “800 million gasoline-powered vehicles with about 100 million private and shared-use driverless vehicles”. Due to vehicles being constantly in motion to meet the needs of the people, the need for car parks would become outdated and this now free land could be converted back to green space which is enjoyed by people in cities. This increased green space would lead to greater mental and physical health from the cleaner air produced by the increase of plants in cities. Furthermore, due to the reverse urbanization which will be enabled by autonomous vehicles, more people would be able to live out of the city in more peaceful, less stressful, and healthier areas like the countryside which will further add to the increased health and quality of life for people. Urbanization has been linked to “an increase in the risk of chronic diseases and some infectious diseases” decreased biodiversity, poor sanitation and increase infant mortality among many more problems. Thus, reversing urbanization should lead to greater health and quality of life for people.

One factor which is argued as a reason against the quality of life which will be affected by the adoption of autonomous vehicles is that people enjoy driving too much to give up manual driving. However, many polls on the matter have shown that people are ready and willing to adopt autonomous vehicles. Further to this I pose the following question; Do you really think that people, when they reach the age of 17 in the UK, when given the choice of spending months of training and thousands of pounds to pass a test which enables them to drive will really desire to expend the effort and money when they can simply use an autonomous vehicle instead? I propose that they would choose the autonomous vehicle, which leads to my next point – that the joy of driving will be lost because of this, and within two or three generations the point will be moot.

Environmental and sustainability effects of autonomous vehicles. 

Autonomous vehicles will benefit the survival of the planet by increasing fuel efficiency and reducing the number of vehicles required in the world. Another area that will be greatly affected by autonomous vehicle adoption is that of sustainability. Due to the combination of moving away from fossil fuels and the reduced number of vehicles on the road, we will immensely reduce ozone depletion, carbon dioxide emissions, aquatic acidification, fossil fuel depletion and other areas which will lead to a cleaner and more sustainable planet. As autonomous vehicles will not be prone to crashing and thus require far less structural strength, far less material can be used to produce the vehicles which in turn will increase the sustainability factor of the vehicles themselves. Further to these structurally weaker materials which are far lighter will be able to be used which will make the vehicles far more fuel-efficient compared to traditional vehicles.

Due to the removal of the front half of vehicles which traditionally hold the engine, and also due to no longer requiring different and more difficult to obtain licenses to drive larger vehicles, the internal capacity of vehicles will be able to be larger. With larger capacity vehicles becoming more commonplace many large families which may have required two vehicles to get everyone around previously could replace both with only one autonomous vehicle which would reduce environmental impact also. The same is true for smaller single-person vehicles because 85% of commuting trips and 83% of business trips by car are single person occupancy. These large four-person vehicles that people are traveling around in with only one person are extremely fuel-inefficient and single-person vehicles would alleviate this fuel wastage. As has been mentioned in the previous section, the area will be freed up that was traditionally used for car parks and reverse urbanization will reduce population density in cities. The area freed from these factors will be able to be changed into gardens or planted areas which will increase the rate of carbon dioxide reduction in these areas, thus further providing benefit to environmental factors.

Yet another way in which autonomous vehicles will enable dramatic fuel savings is that they will be able to drive faster than normal vehicles due to not being limited for fear of crashing and causing damage. This ability to retain faster speeds will enable autonomous vehicles to remain in the ideal speed range for maximum fuel efficiency. The elimination of congestion, like vehicles, will take the least busy routes and avoid traffic jams, combined with the reduced drag enabled by vehicles to be driven closer together will also massively reduce fuel consumption.

The effects of an autonomous vehicle on vehicle design.

The autonomous vehicle will change the perceived norm of vehicle design and the benefits which result from the changes. The final area is the effect autonomous vehicles will have on vehicle design. Vehicles are going to evolve rapidly due to both architectural changes from no longer requiring a large motorized engine, and also from possibilities which will be enabled from vehicles no longer requiring to be structurally engineered to survive crashes.

To highlight how important design is for people to adopt autonomous vehicles when Google showed off their prototype in 2014 the first criticisms came at its design rather than its flawless ability to perform as a fully autonomous vehicle. It was deemed too “childish” and “cute” and was compared aesthetically to the Cozy Coupe toy car. Engineers and designers must, therefore, be well prepared to add sophistication to autonomous vehicles despite their taking away from the ‘machine’ aspect of the vehicle. First and foremost autonomous vehicles have no reason to maintain the current perception of how a car looks, or “should” look. The benefits that different form factors that are enabled by autonomous vehicles will far outway the barriers to owning a vehicle that does not aesthetically conform to the norm. The most apparent effect of this will be the increased variety of vehicle sizes and types, including both vehicles that are far smaller than standard road vehicles today, such as the Ropits by Hitachi, which will consume far less energy and also vehicles which are far larger than vehicles are currently. The increased size will be beneficial for larger families and also for the increased level of comfort to perform leisure activities in the vehicle, even for sleeping if desired. This has been taken to the extreme in the design work by IDEO in 2014 where they envision an entire home office in a vehicle that can be used to work while traveling from location to location.

In terms of types of vehicles on the roads, it is likely we will see fewer and fewer motorbikes because any benefits they have historically given to consumers, such as their price advantage or the relative ease to get a license, will be defunct. Also because the benefits of autonomous vehicles such as increased leisure time, traveling comfort and potentially increased salary or decreased working hours will be very difficult for people to refuse. That said, a number of companies and organizations are working on the development of autonomous motorbikes, including Google, Honda, and BMW, but they will always be less safe than larger vehicles like cars. Due to vehicles no longer requiring to be designed to survive impacts, because autonomous vehicles will almost never crash, vehicles will start to lose the masses of unnecessary heavy metalwork in order to ease the increased speeds they will be able to drive at. This will enable a vehicle’s outer to be made from materials other than those currently used and newer materials like aluminum, glass, wood, fiberglass or carbon fiber could become common.

3-D printing can also potentially be utilized to print vehicles in plastics or metals such as titanium, the ability to use the minimum amount of material for maximum structural strength will make it a suitable manufacturing process because it will provide vehicles that are both lightweight and durable. Internally, autonomous vehicles will have no steering wheel, pedals or dashboard so the area will also be freed up for storage or more seating space. Seating arrangements will no longer need to conform to the four forward-facing seats we have become accustomed to either. A more common concept for autonomous vehicles is to have the front seats facing toward the back seats, a design feature that is shown by automotive manufacturers today as a new concept when in fact it was first shown in 1950. Finally, autonomous vehicles will no longer have a ‘front’ or ‘rear’ as they will be able to travel in either direction just as easily, and it will be beneficial for them to be able to do so for parking and other reasons. It may, therefore, be most comfortable for all passengers if they were seated perpendicular to the direction in which the vehicle is traveling.


Autonomous vehicles will profoundly change the world, and hence why the adoption of fully autonomous vehicles is going to positively affect the world in a number of ways. Firstly, that through the widespread adoption of autonomous vehicles we will be able to save millions of lives per year, avoid tens of millions of injuries which place a burden on hospitals, and reduce the number of people made disabled every year by vehicle accidents. Secondly, that autonomous vehicles will bring massive economic benefits to the world through reducing money spent on insurance and fixing the damage caused by vehicle crashes, through reduced fuel wastage from congestion and also from productivity gains from enabling people to work during transport. Thirdly that, due to the removal of fossil fuel fumes, negating driving stress and enabling people more time to relax and partake in leisure activities, human health, and quality of life will be increased. Fourthly, that there will be sustainability benefits in all phases of the life cycle of autonomous vehicles due to reduced materials and energy in manufacture, the change of fuel from fossil fuels to electric, greatly enhanced fuel efficiency and ultimately a reduced quantity of vehicles in the world. Finally, autonomous vehicles need to avoid the generally accepted look and style of existing vehicles in order to benefit from the different form factors that autonomous vehicles will enable such as single-person vehicles which will enable greater fuel efficiency, bidirectional vehicles which enable better maneuverability and manufacturing methods such as 3D printing which will enable more efficient material usage.

Different automotive manufacturers are now giving their estimates on when we can expect to be able to purchase autonomous vehicles, with autonomous features, such as automatic braking and autonomous cruising, being implemented into manual vehicles more and more already. Tests are showing that the “sensors work perfectly well in good weather and daylight,” but that the cameras aren’t as effective at night time, and radar systems “get frustrated” in snow. Vauxhall, BMW, Nissan, Toyota, and other automotive companies are also working hard in the area and have stated they will have models on the road by 2020. In terms of when we can expect to see autonomous vehicles become commonplace, it has been recently predicted by the Institute of Electrical and Electronics Engineers (IEEE) in New York that 75% of cars will be autonomous by 2040, with others predicting that will come even sooner. Other experts in the field predict that it will be much longer until we even have them at all, but they are over-concerned with the problems which will arise when someone dies as a result of an autonomous vehicle despite that they will significantly reduce overall deaths and injury.

The greatest barrier currently is the laws preventing them, but this is changing rapidly in the last two years where a number of states in America (Nevada, Florida, California, and Michigan) have passed laws to permit them, as well as laws permitting them on the roads in the United Kingdom and Singapore has allowed full access to testing on public roads also. The European Union was hesitant to allow autonomous vehicles but a document submitted to the U.N. in 2014 signed by the governments of Germany, Italy, France, Germany, Belgium, and Austria has the European Union to make a change on the use of autonomous vehicles and they are now road legal – as long as they have a manual override feature.