Development of Driverless Cars in Future

The primary focus of autonomous driving research is to improve driving accuracy. While great progress has been made, state-of-the-art algorithms still fail at times. Such failures may have catastrophic consequences. This paper presents research Development of Driverless Cars in Future with their failures and remedies. Explore the development, challenges, and future of driverless cars in this research-based paper. Find out the evolution of autonomous vehicles and potential solutions to the problems faced. Discover the impact of autonomous driving on transportation and land use. Get insights into the technology, safety concerns, and policy implications.

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 1
Development of Driverless Cars in Future
By student name
Unit title
Lecture, professor
Institution affiliation
Department
September 6, 2019

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Abstract
The primary focus of autonomous driving research is to improve driving accuracy. While great
progress has been made, state-of-the-art algorithms still fail at times. Such failures may have
catastrophic consequences. It, therefore, is important that automated cars foresee problems ahead
as early as possible. This is also of paramount importance if the driver will be asked to take over.
We conjecture that failures do not occur randomly. For instance, driving models may fail more
likely at places with heavy traffic, at complex intersections, and/or under adverse
weather/illumination conditions. This paper presents research Development of Driverless Cars in
Future with their failures and remedies.
The field of autonomous automation is of interest to researchers, and much has been
accomplished in this area, of which this paper presents a detailed chronology. This paper can
help one understand the trends in autonomous vehicle technology for the past, present, and
future. We see a drastic change in autonomous vehicle technology since the 1920s when the first
radio-controlled vehicles were designed. In the subsequent decades, we see fairly autonomous
electric cars powered by embedded circuits in the roads. By 1960s, autonomous cars having
similar electronic guide systems came into the picture. The 1980s saw vision-guided autonomous
vehicles, which was a major milestone in technology and till date we use similar or modified
forms of vision and radio-guided technologies. below is an illustration of an autonomous car on
the road

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DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 4
Table of Contents
Abstract......................................................................................................................................................2
Introduction...............................................................................................................................................5
Research background............................................................................................................................7
Aims and objectives...............................................................................................................................8
Research methodology..........................................................................................................................9
Preliminary research development......................................................................................................9
Summery................................................................................................................................................9
Literature review.....................................................................................................................................11
Evolution of the autonomous cars......................................................................................................11
Background information.....................................................................................................................13
Driverless car throttle control.........................................................................................................13
Forbes report on why autonomous cars are potentially failing........................................................15
Existence of too many corners........................................................................................................15
The technology is not robust enough..............................................................................................15
The expensive cost...........................................................................................................................15
Incompatibility with the human drivers........................................................................................16
Regulatory and liability hurdles that are deemed to lengthen the technology............................16
Cybersecurity...................................................................................................................................16
Economic devastation......................................................................................................................16
Discussion.................................................................................................................................................18
Challenges facing the driverless cars which call for attention..........................................................18
Software issues.................................................................................................................................18
Bad weather.....................................................................................................................................19
Digital mapping...............................................................................................................................19
Better sensors...................................................................................................................................20
Ethical issues....................................................................................................................................20
Reckless drivers/ unpredictable humans........................................................................................21
Creation of a political as well as a legal minefield.........................................................................22
Safety challenge...............................................................................................................................22
Possible solutions to the challenges faced by autonomous cars........................................................23
RSS model........................................................................................................................................23

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Deployment of a cognitive system for control................................................................................24
Solving the cybersecurity issues......................................................................................................25
Mapping...........................................................................................................................................26
Addressing the challenge of bad weather.......................................................................................29
Addressing the software issues.......................................................................................................30
Addressing the ethical concerns.....................................................................................................30
Addressing the reckless drivers......................................................................................................31
The future of autonomous cars...........................................................................................................31
Conclusion................................................................................................................................................31
Bibliography............................................................................................................................................33

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Introduction
The future is ultimately unknowable, but planning requires predictions of impending conditions
and needs (Shaheen, Totte and Stocker 2018). Many decision-makers and practitioners (planners,
engineers, and analysts) wonder how autonomous (also called self-driving or robotic) vehicles
will affect travel and land use development patterns; a road, parking, and public transit demands;
traffic problems; and whether public policies should encourage or restrict their use (Althoff,
2010). There is considerable uncertainty about these issues. 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 (Johnston and Walker 2017; Keeney
2017; Kok, et al. 2017).
However, there are good reasons to be skeptical of such claims.Most optimistic predictions are
based on experience with electronic innovations such as digital cameras, smartphones, and the
Internet. Their analysis 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 – including extreme weather, unpaved
roads and during wireless service disruptions – 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 camera, telephone or Internet failure can be frustrating but is seldom fatal; motor vehicles
system failures 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,

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autonomous vehicles will probably take longer to develop and provide smaller net benefits than
optimists predict (Brodsky, 2016).
These factors have significant transport policy and planning implications (Papa and Ferreira
2018; Speck ). Vehicles rely on public infrastructure and impose external costs, and so require
more public planning and investment than most other technologies. For example, autonomous
vehicles can be programmed based on user preferences (maximizing traffic speeds and occupant
safety) or community goals (limiting speeds and protecting other road users), and many predicted
autonomous vehicle benefits, including congestion and pollution reductions, require dedicated
lanes to allow platooning (numerous vehicles driving close together at relatively high speeds).
Policymakers must decide how to regulate and price autonomous driving, and when potential
benefits justify dedicating traffic lanes to their exclusive use.
Self-driving vehicles combine sensors such as radar, lidar, sonar, GPS and odometry
measurements with inertial units to perceive the environment. Advanced control systems perform
the sensing of data to define suitable routes and barriers and signage. The auto controls in the
vehicle are supported by various technologies. These include the car navigation, positioning
systems, electronic maps, mapping compatibility, worldwide trajectory planning, environmental
perception, laser vision, visual perception, control of the vehicle, the perception of the vehicle
velocity and direction, the process of control of the vehicle, etc., which needs enhancement at
present (Brown, 2017). The figure two below illustrates various levels of automation

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Figure 1 interface of a driverless car ("Driverless cars will make you sick – but there's a fix",
2019)
Research background
The automobile elicits a wide range of feelings: the pleasure of driving may include the
experience of power, freedom, autonomy, independence, speed—and virility.1 In daily road
congestion, however, the pursuit of individual mobility often turns into collective immobility.

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The___14 problem of tramcars, accidents, and the environmental costs of individualized mass
mobility have become a major hindrance to the promise of automobility.
Over the past twenty years, advanced driver assistance systems have been developed that renew
the promise of the automobile. Most of them have become standard features in contemporary car
models. Nowadays, however, researchers at high-tech companies, in the automotive industry and
academia, are pursuing an even more ambitious goal: fully autonomous driving. Existing
concepts of the driverless car that may or may not hit the road in a few years' time di erff
considerably. Something they all have in common, however, is that the promise of safer and
more efficient self-driving cars—a promise made by the manufacturers and echoed in journalistic
and popular culture discourse—rekindles the old familiar logic of a “technological fix”:
technology is understood mainly as a tool to shape the society in a one-directional way rather
than as the embodiment of social relations and the common product of human and nonhuman
practices and actors.
Accordingly, the dominant discourse seeks to solve the problems of contemporary road
transportation systems in a top-down and instrumental way, leaving unaddressed key social and
cultural issues of post-Fordist mobility (Chakraborty & Datta, 2018).
Aims and objectives
The primary aim of the paper is to develop a research-based on driverless cars. In order to
understand the development of research in autonomous driving in the last years, it
is important to conduct to understand the different fields of application
through which autonomous driving has evolved as well as to identify research gaps.
Therefore the main aim in the research process, methodology, and findings of the
literature review are presented.

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The specific objectives in the project will help in achieving the research goals. These objectives
areas listed below.
a. Established the evolution of driverless cars
b. Identify problems and challenges faced in driverless car technology
c. Provide solution for the problems in an above
d. Established the future and possible future technology for autonomous cars
Research methodology
Therefore, taking into consideration only the literature publications relevant to roads, traffic,
crossroads and studies related to commuting, transportation or production, and including all
relevant publications found related to the automotive industry, as well as also considering
papers in other topics that acknowledge that the application could be relevant for self-driving
cars.
Preliminary research development
In order to understand the development of research in autonomous driving in the last years, it
is important to conduct a literature review to understand the different fields of application
through which autonomous driving has evolved as well as to identify research gaps.Therefore in
the next sections the research process, methodology, and findings of the
literature review are presented.
Summery
The primary focus of autonomous driving research is to improve driving accuracy. While great
progress has been made, state-of-the-art algorithms still fail at times. Such failures may have
catastrophic consequences. The primary aim of the paper is to develop a research-based on
driverless cars. In order to understand the development of research in autonomous driving in the

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last years, it is important to conduct to understand the different fields of application
through which autonomous driving has evolved as well as to identify research gaps.Therefore the
main aim in the research process, methodology, and findings of the
literature review is presented.

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Literature review
Evolution of the autonomous cars
The history of self-driving cars is related to various individuals who made significant
contributions from simple structures to the present idea of autonomous vehicles. The evolution of
the autonomous cars is dated back in c. 1500 where it all began by da Vinci who built a self-
propelled cart (Dreves & Gerdts, 2018). The car operated on high tensioned springs whose
steering was pre-set, such that the cart would move in a certain designated path. To some extent,
it became to be regarded as the first world robot. Later, in the times of the world wars, whitehead
torpedo constructed a torpedo weapon which could automatically propel itself underwater over
long distances, via a pressurized methodology. This technology contributed greatly to a variety
of autonomous devices.
An aircraft with autopilot was then developed in 1933 by mike, which was used for longer-range
aircraft. It depended on the gyroscopes to track its path, and the latter is still of significance till
date (Colonna, 2012). In the year 1945, Teeter developed a cruised control system for smooth
steering using a mechanical throttle. 1961 saw the development of the first autonomous vehicle
when the idea to design a lunar rover which would navigate independently on the moon was
proposed by a Stanford engineering graduate. The car was built on a number of sensors and
cameras to detect various changes and signals.
In 1977, based on an improved version of the autonomous car, Japan-based tsukubai developed
an autonomous car which had the ability to recognize the street markings while moving at a
speed of 20 miles every hour by the help of two mounted cameras. The idea was further
improved by Ernest Dickmass who enhanced the car further with a variety of sensors which
could detect various potential hazards as well as their locations. In 2015, tesla developed a

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hands-free control autonomous car for freeway and highway driving. The latest evolution
towards the autonomous cars is propelled by the University of Michigan city, which is 2015;
launched a test facility for the self-driving cars, partnering with various stakeholders such as the
government, google, ford, among others as shown below
Key stakeholders (Elbanhawi, 2016)
To have a clear view of the development, issues and how the issues can be addressed in the
autonomy’s cars, it is essential to conduct a literature review; so that the various developmental
stages in which the autonomous cars are brought into the light. This section will generally
present the overview of the autonomous cars

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Background information
A number of automotive consumers have the perspective that autonomous cars have been in
existence for just a short time. Nonetheless, the engineers began to develop systems which could
support the driverless cars back in the 1980s. To make the dream a reality, the car manufactures,
and designers needed to first lay a clear foundation (Elbanhawi, Simic & Jazar, 2015). They were
required to single out every system in the vehicle which called for the interaction of human
action, such as the use of foot or hand, and then develop an automated system for these
functions. It implied that the end result would be a complete redesigning of the devices so that
the electronic devices would function autonomously. Some of these systems would therefore
include
Driverless car throttle control
This is one of the first manually operated automotive cables which became extinct. In the first
100 years of designing the trucks and cars, pushing off the gas pedal would operate a cable
which would move the throttle. Thereafter, letting off the gas pedal would return a heavy spring
instantly which would close the throttle plates (Färber, 2016). This system alone became extinct
with the introduction of the driverless cars. In the mid-80s, drive by wire system installation
started to see the light of the day. Some of the primary full production of the drive by wire
throttle systems were realized in the German cars such as the Audi automobiles, as well as the
BMW series. Surprisingly, the introduction of these drive by wire throttle systems led to the
acceleration of syndrome complains from most of the car owners (Gerla, Lee, Pau, & Lee,
2014).
The reports released in connection to it majorly from the drivers was that they were fully aware
of the difference between the gas pedal and the brake pedal. In 2007, Toyota company released a

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report, attributing the issue to the driver side floor mats which got out of position and then
displaced the gas pedal. They did refer to this condition as floor mat entrapment. The company
thereafter volunteered to secure floor mats so that they did not get displaced.
When the issue persisted, the company blamed a friction gadget in the pedal section which was
meant to offer a recommended feel by stabilizing the pedal as well as the addition of more
resistance (Gerla, Lee, Pau, & Lee, 2014). There was increased pressure thereafter, promoting
the Toyota company to make a recall in 2010, on a more aggressive approach, replacing the
original throttle control mechanism with an updated model. This updated model would then
integrate with the switching brake and thereafter return the throttle to the closed position on the
application of a brake pedal.

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Forbes report on why autonomous cars are potentially failing
Forbes produced a range of potential issues, which encompasses operational resiliency, technical
viability, as well as other fears which are related to the driverless cars. Among the potential
issues which the Forbes produced which might contribute to the failure of the driverless cars
includes
Existence of too many corners
Despite the autonomous cars being able to solve a number of issues in relation to the driving
scenarios, some of the issues remain unsolved. John Leonard, of masochists institute technology,
points out that adverse weather, points to left-hand turns, changes in road surfaces, hand and eye
gestures will have a long way (Gogoll & Müller, 2017).
The technology is not robust enough.
Despite having theoretical solutions to the problems faced with driverless cars, translating the
solutions to real-world becomes one of the hardest tussles. Robustness would relate to various
components such as mechanical, electronic as well as software with a minimal error tolerance
under adverse weather conditions, electrical as well as network outages.
The expensive cost
The driverless cars are generally characterized by autonomous systems such as radar, cameras,
sensors lidars, networking devices, in addition to high costs of maintenance, and development
(Hussain & Zeadally, 2018). By implication, the driverless cars will not be within the reach of
most of the consumers, and this is likely to contribute to the failure of the cars.

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Incompatibility with the human drivers
Despite the dispatched of driverless cars, compatibility with the cars with drivers might not be
possible and eventual. It thus means that there is likeliness of collisions which results in
accidents and eventual failure of the technology.
Regulatory and liability hurdles that are deemed to lengthen the technology
The regulatory frameworks, as well as the legal aspects which are instituted, are with regards to
the cars with drivers. It, therefore, encompasses on expectations on the person that is liable to a
certain action or the components which are required in the cars as well as other factors. Sorting
these issues out is deemed to take a long time and the approval of the process is likely to be
delayed. Further, product liability is deemed to be a showstopper (Le Vine, Zolfaghari & Polak,
2015).
Cybersecurity
So far, the cybersecurity of the driverless cars has not been clearly outlaid, and this makes the
cars susceptible to attack by hackers. Further, the thieves, terrorists, and hijackers are likely to
take advantage and thrive in terror activities. There is also the risk range from the privacy
invasion to the spectra of the driverless cars being utilized as bomb precision delivery vehicles.
1087940
Economic devastation
By way of approximation, 10% of all the jobs are related to driving. Deployment of the
driverless cars is likely to put millions of the citizens out of work, the inclusion of the truck, bus,
Uber and taxi drivers. Generally, the job of many citizens would be at risk. Some of the hardest
issues which the driverless cars may not easily find a solution to the dispatching of the

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autonomous cars are the issues which require societal views, such as public acceptance among
others (Lin, 2016).

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Discussion
Challenges facing the driverless cars which call for attention
In the recent past, Google released a couple of data which indicated that its autonomous cars
have been involved in eleven minor crashes in the past six years, which has led to the question of
when will the autonomous vehicles be fully ready. In the report, the major issues which were
referred to were the crash as a result of human driver error, which as well could not be prevented.
The reporter, Steven shaldover went further ahead to note that despite the completely
autonomous systems being in existence, much of innovation is still needed in regards to the
steering wheels and brakes. The problems further laid to the driverless cars which call for further
attentions would include
Software issues
Taking a driver in the united states is incredibly safe, with incidences of fatal crashes taking
place once every close to three million hours of driving. It thus implies that driverless cars would
be required to be safer than that. However, with the existing software, it becomes a little bit
difficult to do so. The major reason behind this is because a number of these software’s which
have been designed to operate in laptops or modern electronic gadgets cannot operate for longer
hours without crashing, freezing, or dropping a call. The goggle autonomous cars have thus tried
to manage this situation by having another person as a monitor as well as a backup driver. These
persons would then shut the system immediately after realizing a hitch. Nonetheless, designing
failsafe software for autonomous cars would call for a reimagining of how the design of the
software is.

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Bad weather
Usually, the changes in the weather patterns are metaphysical, such that they are beyond human
prevention. In most situations, the changes in the weather might result in causing fog, snow, rain,
or other types of weather which might make it difficult for the humans who are driving. The
driverless cars, however, utilize the digital sensors, lidars, and cameras which keep track of the
lines in the pavement. Nonetheless, there is little so far which the sensors can do about the
changes in weather such as the creation of fog or mist. They make it very much impossible for
autonomous cars to make decisions.
Further, in the past reports which have been published by the google company, one of the major
challenges to the success of the autonomous cars was recorded as bad weather during the road-
tests with the autonomous cars. The manufactures of the auto systems, however, are very
positive that they might come up with more robust systems which are weather prone and will be
able to perform their duties in whatever kind of weather (Litman, 2017).
Digital mapping
The googles autonomous cars have so far been successful on the streets, courtesy of the
company’s effort to generate a virtual map of how the town looks. This enables the cars to be
aware of how the street view is. However, the current autonomous cars, on a general perspective,
are not really equipped with the digital map of the globe. Further, very few numbers of roads
have been leveled or designed to that level of extent; an even if so, there are usually other
incidences of road repair or construction which are likely to alter the conditions of the road.
Moreover, most of the companies which are undertaking the manufacture of the automobiles are
trying to ensure that the roads are digitally mapped to allow the smooth operation of the

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autonomous cars. Some of the companies include Audi and Daimler unit of Volkswagen and the
BMW of the German automakers.
Better sensors
Most of the already designed autonomous cars lack the opportunity to distinguish between
threats and the situations which are harmless. This is likely to result into slamming of the brakes
irresponsibly, as well as failing to take measures while under some level of threat such as
potholes. Past incidences have been experienced by various passengers who experienced the
autonomous cars slow down in areas where there are no road threats and then speed up in
instances where it was supposed to slow down such as on the road potholes (Maurer, Gerdes,
Lenz, & Winner, 2016).
Ethical issues
Take an instance were the ball suddenly bounces in the road, and then two children appear in
pursuit of the ball. The autonomous cars will make a decision in such a case, either to hit the two
children and save the life of the children, or swerve off the road and hit the pedestrians, as well
risking the life of the passengers on board. Which could be the ethical decisions/stance/case in
such a situation? Or who should the computer give priority to? One might reason that the
autonomous car in such a case should hit the children so that the lives of the majority are saved.

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One can reason out that it is better to hit the children as they are only two and then save the lives
of the many passengers and pedestrians, a reasoning which is ethical right, and the other person
might as well reason that the children have nothing to do with the vehicles and it is the
passengers who by boarding the cars took a risk and should bear the risk; by the car swerving off
and possibly causing harm to them.
In a normal situation, though in rare cases do we experience a situation whereby the normal
driver would press the emergency brakes and end up saving the lives of all parties. The engineers
are faced with this ethical situation on their daily activities of design and have s0o far not come
up with an ethical solution to such a case. The problem with the algorithm lies in the decision to
make an instant or rather prompt response when faced with an emergency.
Reckless drivers/ unpredictable humans
This also presents itself as one of the major problems which are facing the success of driverless
cars. The driverless cars rely on algorithms, which when manipulated, can position the
autonomous cars to obey the traffic rules. For instance, slowing down on the traffic lights turning
yellow, or stopping when the light changes to red or green. However, the algorithms have no
effect on ordinary cars nor drivers. It, therefore, becomes a problem dealing with the driverless
who tend not to obey the traffic rules, or tend to Overspeed. Ideally, the humans who also
ignores the traffic outlets such as flyovers and would tend to follow busy roads might also be at
risk as to the algorithms dictating the operation of the autonomous cars have no effect on them
(Maurer, Gerdes, Lenz, & Winner, 2016).
Other issues which are considered minor though they affect the autonomous cars

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Creation of a political as well as a legal minefield
As it stands, the laws which guide the autonomous cars are simple and at the same time
sophisticated. The aspects of simplicity are with regards to the fact that there are very few issues
which dictate the laws relating to autonomous cars. The sophistication as well lies in the same
point, such that coming up with these is a bit tricky issues, as one is left wondering whether to
enact the laws as well on the manufacturers. There are some states which have come upon with
the laws guiding the autonomous cars, however, most of these laws seem to contradict each
other. Further one can simply argue that a staff which has not been debated upon is likely to be
legal, but upon debate, answers might be difficult to find on such issues.
Being that there are less guiding common rules on the regulations of autonomous cars, various
companies are much afraid on investing on things which will likely be illegalized upon a debate
by the united states of America, setting very strict laws in the self-driving cars. By implication,
the autonomous cars present a very confusing scenario between the technological regulations as
well as the traffic regulations. It is more predictable than most automakers companies will not be
likely on the same page with the national regulations produced by the states.
Safety challenge
Currently, most of the traffic rules are focused around one major is; the driver. Most of the
assumptions are that the vehicles are under the control of humans, including their insurance,
licensing, as well as the traffic laws. The dilemma thus presents itself in autonomous cars. When
can we be in a position to tell that a certain autonomous car is at fault of an accident? Should the
insurance be pended on the owner of the car or the manufacturer themselves? How will these
ordinary cars and the self-driving cars co-exist naturally, and in a safe manner? Prior to the
public acceptance of the autonomous cars, these are some of the certain questions which need to

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be answered. A number of individuals have freely expressed themselves when it comes to their
safety with the autonomous cars, terming it less assuring.
Despite the ordinary cars killing more than a million persons every year, it will only take a few
periods for a few autonomous cars to results into some fatal accidents, which might render then
either unsafe or comply with various regulations. Various nations have been at the forefront of
coming up with rules which guide the autonomous cars legislations. Already, governments such
as the united states of America, have already installed a USDOT automated vehicle guidelines
which will play a significant role in the industry.
Possible solutions to the challenges faced by autonomous cars
Among the various possible solutions, is the construction of industry standards which stipulates
the accident faults thus proving the extent of safety in the autonomous cars upon coming into
collision with ordinary driven cars. Defined standards of blame are very critical, as there can be
incorporated into the av making software so that the policies which dictate the driving can be
programmed to follow the updated standards. In such a case, the accidents could not be caused
by the avs which might then attribute the faults to the av faults system. The major approach, that
would be valid in such a case is the responsibility sensitive safety model which had been earlier
publicized on the paper, “n a formal model of safe and scalable self-driving cars”.
RSS model
By definition, the RSS model is a mathematical model which is responsible for ensuring that the
autonomous cause operates in a responsible manner. It does this through the provision of
measurable and specific values for the human responsibility concepts and cautions; which
defines a safe state whereby the autonomous car will not cause an accident, irrespective of any
actions conducted, even the other ordinary cars. The reason as to why the principal aspect lies in

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the ability to assign fault is that even ordinary cars cannot result in some actions without safety
control measures. In ordinary situations, most of the drivers are likely not to cause accidents due
to their own faults, considered the 360-degree vision as well as the fast lightning reactions which
are to be incorporated into the autonomous cars. The formalization by the RSS ensures that no
braking of the traffic rules is experienced (Owczarzak & Żak, 2015)
Illustration
Assume that the rear vehicle was an autonomous car which is coupled with the mathematical
RSS model. The RSS model will continually evaluate all the actions by the use of software,
against a comprehensive set of scenarios related to driving while the av maintains a safe state.
The presence of the RSS model makes the sensors in the av systems behave in a manner likely to
be a black box where all the definitive data are collected and maintained throughout. The data
can then be applied in the determination of causes of faults in the autonomous cars.
Deployment of a cognitive system for control
Since the dynamic existing between humans and self-driving cars is very dynamic. So far, a new
cognitive technique which could be quite influential in determining whether the self-driven car
or the humans take control of the vehicle. The technique is with regards to various indicators
such as human emotional state, fatigue and the general mechanical function of the autonomous
car. There are onboard communications sensors which will be able to monitor the psychological
aspects of the human such as the direction of gazing as well as their heartbeat rate. From the
configuration, the cognitive system will be in a position to determine whether it is safe to
navigate in such a situation.
The system further, navigates on other obstacles which might as well be navigated in a better
position by humans. An instance is this, the system might detect an issue with the tire pressure,

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and cognitively decides that a human driver would be better placed to take control (Yaqoob et
al., 2019). Nonetheless, the system would do this after ensuring that it has analyzed the data it
has collected and that the driver is in a ready position to take on the wheel. Additionally, the
system might consider that both the humans and the autonomous car itself are unfit for driving
under such conditions, and thereafter slow down and pack in a safe location. The system, as well,
would learn about its environment by cross-checking on the past accident histories and other
autonomous during traffic patterns.
Taking the incidence of children running across the road suddenly, the human driver, in that
case, will slam the car, making it come to a halt and save everyone on board. After the incidence,
the person might not have regained is full consciousness, and thus might not be able to
efficiently operate the autonomous machine. In such a case, IBM would then suggest that the car
resume its normal duty of self-drive; till later on when the human has a chance to calm down.
Solving the cybersecurity issues
The cybersecurity issues are dynamic, and range from the hacking of the system, to breaching of
it becomes one of the issues which will raise concern over the social responsibility of the
autonomous cars. A more regulatory approach, which makes it a priority to the security,
promotion of best cybersecurity practices, as well as holding the automotive companies
accountable will be effective (Politis, Brewster & Pollick, 2015). However, attempts to address
the issue of cybersecurity seems to be a bit sophisticated. Its process of rulemaking takes a lot of
years, thus, situations that new vulnerability has been experienced takes quite a long time for
them to be addressed. Further, issues which require immediate attention are not easily handled.
The manufactures, when regulatory standards can be set, such that they have to meet certain
requirements for these issues to be met then it becomes quite easy to handle the cyber-attack

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 27
issues related. In aid of this, the National Highway Traffic Safety Administration should be at the
forefront in enacting the various policies, and among them includes: (Politi et al., 2017)
Requiring the autonomous car manufacturers to table a detailed report of the various possible
cybersecurity plans, procedures, and measures which can be taken in the event of an attack.
Also, the manufactures, through the National Highway Traffic Safety Administration makes
various sensitive answers relating the autonomous cars such as security public to minimize the
anxiety. Also, the National Highway Traffic Safety Administration can proactively act through
the hiring of independent cybersecurity experts who test the capabilities and the promises of the
manufacturers. Additionally, the manufacturers need to be held accountable in the events of
various incidents on the side of the autonomous car.
This approach presents various advantages, such as; it lessens the regulatory uncertainty for the
compliance between the manufacturers and the various industry groups. Additionally, with the
frequent update of the various cybersecurity plans by the various manufacturers, more robust
measures will be developed to heighten the security (Viswanathan & Hussein, 2017). However,
the regulations need to be limited, such that in case the regulations are made a little bit more
complex, deployment of the autonomous cars might really not take effect, and the loss of
millions of lives annually in road accidents will be deemed to go high.
Mapping
Provision of accurate data for autonomous cars has been one of the biggest challenges facing the
driverless cars. However, something can be done over the same. For instance; using a more
robust mapping software which captures data from over 15 million cars globally, and then using
the software to perform manipulations and analysis of the images.

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 28
Conventionally, the ordinary navigation maps depend on global position system data, which can
only capture data within a distance of 10 feet. However, autonomous cars require very accurate
data, which is within an inch or two. One challenge is that most of the cars do not have the
capacity of updating the maps on daily basis, thus; a crowded mapping platform will enable these
self-driving cars to upload their camera data to the cloud.
The mapmaker will then be able to perform analysis on the data and regularly update it. The
cameras require sensor data system which has high precision. There are various advantages
which are linked to this model. For instance, no additional hardware would be needed, as the
sensors which detect the various obstacles in the road are the same which can be used in the
capturing of images in the roadside. Further, the data which is captured is not as detailed as those
which are captured by the lidar sensors; thus, they do not result in a big stream of data. The hope,
also is that by the time the intel is releasing the 5g modem which has the capability of very fast
data transmission, it will find when these mapping systems are also ready (Pozna & Antonya,
2016).
Ordinarily, most of the images which are utilized by various autonomous car companies rely on
aerial data, which when closely analyzed, becomes difficult to transcribe int the real outlook of
the road. In reference to this, artificial intelligence can also be very useful. Research suggests a
neural network which imitates human, known as the road tracer. According to a report on which
appeared in the science daily, the road tracer is 45 percent more accurate than systems which are
currently utilized (van den Berg, Verhoef, 2016). The approach is very effective in the cities as
well as rural areas where digital mapping has not yet been done.
An instance also is when the road trace successfully mapped 44% of the road junctions using
various pictures captured in New York City. This figure is more than double the fraction

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 29
produced by other conventional approaches. In other conventional approaches, a pixel in a
picture is identified as either a road or something else, which is not accurately identified. Ideally,
misidentification of just a single pixel can be amplified into a bigger mistake on the map. The
rod tracer, on the other hand, utilizing the neural network process the data in a stepwise manner.
Some of the advantages which are associated with this technology include; low error data rate,
making the activity more practical.
Its improved advancement makes it able to account for various changes or correct the errors. In
terms of cost, it is found to be very cost-friendly and affordable and would be beneficial to both
large and small organizations. The diagram below illustrates lidar sensing and cloud-map

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 30
Lidar performance
Addressing the challenge of bad weather.
The deployment of the autonomous cars has been not been successful due to failure to adapt to
various changes in weather, resulting in the Teslas case, where the road lines could not be
detected. Most of the sensors become irresponsible in such kind of weathers situations, and
might wrongly misinterpret the snowflakes as obstructions. However, an algorithm which was

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 31
developed by the University of Michigan can aid in addressing these challenges. Ordinarily, the
lidar sensors, produce a burst of lasers as the cars drive.
The car utilizes these bursts to generate a high-resolution 3d map of the environment. In this
proposed algorithm, the car will be in a position to analyses the burst as well as the echoes which
they generate so as to figure the instances which they are hitting the snowflakes or the raindrops
(Rödel et al., 2014). When the laser goes through the snow or a raindrop, a fraction of it will hit
the flake/raindrop, while the other section will get diverted towards the ground. By listening to
the echoes of the lasers getting diverted, the algorithm will generate a picture, reconstructing a
whole ground plane of the incidence. Besides, the algorithm will confirm the persistence of a
certain obstacle, for instance; a laser beam will possibly hit a raindrop twice, ruling it an
obstacle.
Addressing the software issues
So far, the cost of developing software’s seems to be more than just a dream. One solution to his
issues is by having a backup driver who will be in charge of monitoring the system, and in case
of a hitch, shuts up the system and restarts it (Sadigh, Sastry, Seshia, & Dragan, 2016).
Addressing the ethical concerns
When confronted with ethical situations, the decision made by the autonomous vehicle relies on
the software’s which has been programmed to run it. The casualties, which might be the
passengers or rather the pedestrians usually have little to do/say in such circumstances, and the
decisions lie fully with the autonomous system. Ethical issues raise philosophical debates which
people may not come to an agreement. The appropriate procedure, therefore; will be to do a
thorough societal consultation, and come up with various recommendations. These
recommendations would further be looked into by the governmental regulatory authorities, who

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 32
after which develops a common ground over the same. At such a position, the decision would
then be incorporated into a suitable program, which will be able to make decisions on behalf of
the autonomous cars when faced with an ethical situation (Seif & Hu, 2016).
Addressing the reckless drivers
The solution to addressing the challenge of the reckless drivers is by equipping the cars with
devices knowns as transponders, these transponders have the ability to communicate the speed,
position, as well as the direction of other vehicles. Also, the techniques are termed as V2V
communication, and ordinarily, the airplanes utilize the technique in order to prevent possibilities
of collisions. The technique will be most suitable upon the deployment of a significant number of
vehicles having a similar capability (Tettamanti, Varga & Szalay, 2016).
The future of autonomous cars
The idea of autonomous vehicles was not successful and well accepted in the beginning.
However, coupled with the various developments which are taking place, we are looking into a
future whereby fully autonomous vehicles will be the norm of the day. The smart cities shall be a
reality, and the vehicle shall have transformed into a room, moving on wheels (Tian, Pei, Jana &
Ray, 2018). Further, the vehicle users shall be fully connected with what is going on around
them, and the autonomous systems shall be linked to their mobile ecosystems as well as home
systems. Individuals shall be able to control possible all task within their disposal, everywhere
and anywhere.
Conclusion
The future of autonomous cars seems to be so bright, however, its implementation has not been
successful as far as it is concerned. During the inception phase of the idea, it received various
criticisms on some of the many aspects of its operation, and probably lack of sufficient answers

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 33
to these concerns have been the reason behind its slow success. For instance, these issues are
majorly technological, in addition to social issues such as the trolley problem, presented as an
ethical matter. Delving deeper, the technological issues include digital mapping, bad weather,
lack of better software systems, reckless drivers, among others. This dissertation, however, has
attempted to raise some probable solutions, which when taken keenly, can be the antidote
towards achieving the full implementation of the autonomous cars. Some of the various steps
proposed in the dissertation include:
 Adaptive cruise control to assist in speed regulation during dangerous circumstances
 Installation of many sophisticated and complex sensors, lidars and radar systems for
detection purposes
 Enhanced digital mapping to improve navigation in various weather systems
 Societal consultative measures on the ethical dilemmas surrounding the implementation
of autonomous cars.
 Having a backup driver who will be in charge of monitoring the system, and in case of a
hitch, shuts up the system and restart’s it.
 The setting of regularly updated regulatory standards which needs to be met by the
automotive car manufacturers to help to address the cybersecurity issues.
The intricate implementation and research on these matters proposed can be of great significance
to ensuring the deployment of fully autonomous cars.

DEVELOPMENT OF DRIVERLESS CARS IN FUTURE 34
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