AUTONOMOUS VEHICLES

A Seminar Report
Seminar Report submitted in partial fulfilment of the requirements for the award of the
Diploma in Mechanical Engineering under State Board of Technical Education, Kerala

BY

ADITHYAN.S.P
Reg. No:-23031022684

Under the Guidance of

Sri. ARUN KUMAR

LECTURER, Dept. of Mechanical
Engineering

DEPARTMENT OF MECHANICAL ENGINEERING CENTRAL

POLYTECHNIC COLLEGE, VATTIYOORKAVU,

THIRUVANANTHAPURAM

CENTRAL POLYTECHNIC COLLEGE, VATTIYOORKAVU

DEPARTMENT OF MECHANICAL ENGINEERING

CERTIFICATE
This is to certify that the Seminar Report entitled “AUTONOMOUS VEHICLES” IN
MECHANICAL ENGINEERING” is a Bonafede record of the work done by
ADITHYAN.S.P (Register No: 2301022684) during the academic year 2023-26 under
our guidance and supervision towards the partial fulfillment of the requirements for the
award of Diploma in Mechanical Engineering under the State Board of Technical
Education, Government of Kerala.

ARUN KUMAR Sri.ANOOP

Head of Department Head of Department

Dept. of Mechanical Engineering Dept. of Mechanical Engineering
 DECLARATION

I the undersigned solemnly declare that the seminar report entitled “AUTONOMOUS
CAR” is based on my own work carried out during the course of our study under the
supervision of Sri. CHINDHU V G. I assert the statements made and conclusions
drawn are an outcome of my research work. I further certify that the work has not been
submitted to any other institution for any other degree/diploma/certificate in this
university or any other universities abroad. I have followed the guidelines provided by
the university in writing the report. Whenever I used materials (data, theoretical
analysis, and text) from other sources, I have given due credit to them in the text of the
report and giving their details in the references.

ARJUN A R
19020318
 GOVERNMENT POLYTECHNIC COLLEGE
KALAMASSERY
www.gptckalamassery.
ac.in

INSTITUTION VISION AND MISSION

VISION

To become a centre of excellence committed to moulding technologically competent and

ethically motivated learners capable of contributing constructively to the sustainable
development of the society.

MISSION

1. To ensure a viable academic ambience conducive to intellectual growth and skill

acquisition.
2. To defect a symbiotic relationship between the industry and the institute.
3. To infuse a sense of personal integrity, self-reliance and civic responsibility.
4. To inculcate entrepreneurship skills and leadership qualities in the learners through.
a culture of innovation and excellence.
 Department of Mechanical Engineering

GOVERNMENT POLYTECHNIC COLLEGE

KALAMASSERY
www.gptckalamassery.
ac.in

DEPARTMENT VISION AND MISSION

VISION

Mechanical Engineering Department impart quality Education that mould technically

sound, socially responsible technocrats to meet ever changing industrial demands and
social needs.

MISSION

1. Have state of art infrastructure and resource for practical oriented skill development.
2. Impart relevant technical knowledge along with values and ethics.
3. Enhance creativity through innovative teaching learning methodologies.
4. Inculcate essential leadership qualities coupled with commitment to the society.

Department of Mechanical Engineer

ing

GOVERNMENT POLYTECHNIC COLLEGE

KALAMASSERY
www.gptckalamassery.
ac.in
 PROGRAM OUTCOMES (POs)

01 Basic and Discipline Apply knowledge of basic mathematics, science and

specific knowledge engineering fundamentals and engineering
specialization to solve the engineering problems.

02 Problem analysis Identify and analyze well-defined engineering

problems using codified standard methods.

03 Design/ development Design solutions for well-defined technical problems

of solutions and assist with the design of systems components or
processes to meet specified needs

04 Engineering Tools, Apply modern engineering tools and appropriate

Experimentation and technique to conduct standard tests and
measurements
Testing
05 Engineering practices Apply appropriate technology in context of society,
for society, sustainability, environment and ethical practices.

sustainability and
environment

06 Project Management Use engineering management principles individually,

as a team member or a leader to manage projects and
effectively communicate about well-defined
engineering activities.

07 Life-long learning Ability to analyze individual needs and engage in

updating in the context of technological changes.

PROGRAM SPECIFIC OUTCOMES(PSOs)

01 Employability Students acquire technical and managerial skill that

make them employable

02 Problem solving Students acquire theoretical background of each course

that they are capable of applying it for solving real-
time problems
PROGRAM EDUCATION OBJECTIVES (PEOs)
On successful completion of the program, the graduates are expected
1. To take up challenging careers in suitable corporate, business or
educational sectors across the world.
2. To exhibit professionalism, ethical attitude, communication skills and
team work in the practice of profession, and adapt to current trends by
engaging in lifelong learning.
3. To be knowledgeable and responsible citizens with good team work
skills, competent leadership qualities and holistic values.
 ACKNOWLEDGEMENT

First of all, I would like to express my sincere gratitude and thanks to God almighty
whose blessings and grace always been there with us for the successful completion of
my seminar with great enthusiasm and pleasure that I bringing out this seminar.
First and foremost, I thank God almighty for all his blessings he showered on me. I
express my sincere thanks to Principal Smt. GEETHA DEVI R, Govt. Polytechnic
College, Kalamassery.
I would like to express our sincere thanks to our Head of the Department
Sri. CHINDHU V G, Department of Mechanical Engineering for the successful
completion of this seminar.
I express my sincere gratitude to Seminar Co-ordinator Sri. CHINDHU V G, Head of
Department of Mechanical Engineering for his cooperation and guidance for preparing
& presenting this seminar.
Last but not the least thankful to all members of our department for providing their
valuable support in this seminar. I also expressing our thanks to my parents and all
friends who give me extreme support for completion of this seminar.

ARJUN A R
Register No.: - 19020318
Dept. Of Mechanical Engineering

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ABSTRACT

An autonomous car is a vehicle capable of sensing its environment and operating without
human involvement. Also known as self-driving vehicles, they combine sensors and
software to control, navigate, and steer the vehicle with help of pneumatic and
mechanical systems. Widespread adoption of AVs could lead to a 90% reduction in
vehicle crashes.
Autonomous vehicles can reduce drivers’ stress and tedium, and increase their
productivity. They can be mobile offices and bedrooms, allowing passengers to rest or
work while travelling. This reduces travel time unit costs. Self-driving taxi and
microtransit services will be cheaper than human-operated taxis.

Optimistically, autonomous vehicles will be safe and reliable by 2025, and may be
commercially available in many areas by 2030. Autonomous cars depend on sensors,
actuators, complex algorithms, machine learning systems, and powerful processors to
execute software. Its main advantages are to Fewer traffic collision and to help to people
who are physically challenged it also reduces transportation cost by more than 40% and
main disadvantages are driver’s loss jobs and costly.

According to the latest report “Autonomous Cars, Robo-taxis & Sensors 2022-2042” ID
Tech Ex delves deep into the future of automated mobility. Then by 2050 autonomous
vehicles could theoretically meet the entire transport needs of the world, with less than one
accident per year.

Keywords: - Autonomous Car, Sensors, Actuators, Artificial Intelligence Software

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 CERTIFICATE

CHAPTER PAGE
TOPIC NO. NO.

ACKNOWLEDGEMENT i

ABSTRACT ii

LIST OF FIGURES iv

1 INTRODUCTION 1

2 COMPONENTS OF AUTONOMOUS CAR 3

2.1 ULTRASONIC SENSORS 3

2.2 RADARS 4

2.3 CAMERAS 5

2.4 G.P.S. UNIT AND CLOUD SERVICES 6

2.5 LASER SCANNER 7

2.6 BACKUP SYSTEM 8

3 WORKING PRINCIPLE OF AUTONOMUS CAR 10

3.1 MAPPING AND LOCALIZATION 10

3.2 OBSTACLE AVOIDANCE 11

3.3 PATH PLANNING 12

3.4 THE ROAD AHEAD 13

4 CHALLANGES 15

4.1 CREATING MAPS IS DIFFICULT WORK 15

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 4.2 COMPLEX INTERACTIONS ARE TOUGH FOR ROBOTS
16

4.3 BAD WEATHER MAKES EVERYTHING TRICKIER 17

4.4 HOW SAFE SELF-DRIVING CARS REALLY ARE 18

4.5 CYBERSECURITY ISSUES 19

5 CONCLUSION 21

6 REFERENCES 23
LIST OF FIGURES
FIG. NO NAME PAGE NO.

1.1 WORKING MODEL OF AUTONOMOUS CAR 2

2.1 ULTRASONIC SENSORS 4
2.2 RADARS 5
2.3 CAMERAS 6
2.4 G.P.S. AND CLOUD SERVICES 7
2.5 LASER SCANNERS 8
2.6 BACK UP SYSTEM 9
3.1 WORKING OF SELF-DRIVING CAR 10
3.2 OBSTACLES AVOIDANCE 12
3.3 PATH PLANNING 13
3.4 SCANNING OF SPEED CONTROL BOARD 14
3.5 AUTONOMOUS CAR MODEL 15
4.1 CREATING AND MAINTAINING MAPS 16
4.2 COMPLEX SOCIAL INTERACTIONS 17
4.3 BAD WEATHER MAKES EVERYTHING TRICKIER 18
4.4 HOW SAFE SELF-DRIVING CARS REALLY 19
4.5 CYBERSECURITY 20

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 CHAPTER - 1 INTRODUCTION

For the past hundred year’s innovation with in the automotive sector as brought major
technological advances leading to safer, cleaner and more affordable vehicles. In the
decades of the 21st century the industry appears to be on the cusp of revolutionary
change with potential to dramatically reshape not just the competitive landscape but also
the way we interact with vehicles and indeed. The future design of our road and cities.
The revolution when it comes will be engendering by advent of an autonomous or self-
driving car.

Self-driving vehicles have been defined as vehicles in which operation occurs without
direct driver input to control the steering, acceleration and braking according to the
national highway traffic safety administration. In this type of vehicles, the driver is not
expected to constantly monitor the roadway while operating in self-driving mode. This
definition assumes that the vehicles will always have a driver however this isn’t
essential autonomous technologies are already able to perform all of the required
function for vehicles to move safely without any one board at all. The wide spread
adoption of driverless vehicles may seem distant vision something we would expect to
see in futuristic movie perhaps.

Self-driving cars are mainly depending on the instruction is given by the GPS system. It
gives the clear picture of road. On the road the complete technology solution shall
handle even the most complicated scenarios. Self-driving cars as a holistic solution that
generates exact positioning and complete 360 (degree) views of the cars surrounding.
This is achieved by a combination of multiple radars, cameras and laser sensors. A
redundant network of computers processes the information generating a real time map
of moving and stationary objects in the environment. The cameras have a high dynamic
range and can handle very quick changes in lighting condition example: When entering
a tunnel. Sensor is used to detect are identify the any objections to car on the road. It has
technology to detect the speed board in the highways and it goes on that speed. For this
car cloud services are attached. It connected to the traffic authorities control centres. It
has a backup system facility as in the aeroplanes that will ensure that autopilot will
continue to function safely also if an element of the system was to become disabled.
Modern society faces

Dept. of Mechanical Engg CPTC vattiyoorkavu

extensive future challengers to improve safety and reduce pollution and global
coemissions. Autonomous can cut fuel consumption by up to 50% in certain situations.
Impaired mobility and congestion can be added to the list of challenges.

Fig. 1.1 Working Model of Autonomous Car

✓ Ultrasonic sensors may be used to measure the position of object very close to
the vehicle, such as curbs and other vehicles when parking
✓ Signals from the GPS (global positioning system) satellites are combined with
reading from tachometers, altimeters and gyroscope to provide more accurate
positioning than is possible with GPS alone.
✓ LIDAR (light detecting and ranging) sensors bounces pulses of light off the
surrounding. Then are analysed to identity lane marking and the edges of roads.
✓ Video cameras detect traffic lights, read road signs, keep track of the position of
other vehicles and look out for pedestrians’ obstacles on the road.
✓ Radar sensors monitor the position of other vehicles nearby. Such sensors are
already used in adoptive cruise-control systems.
✓ The information from all of the sensors is analysed by a central computer that
manipulates the steering, accelerator and brakes. Its software must understand
the rules road, both formal and informal.

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CHAPTER - 2 COMPONENTS OF AUTONOMOUS CAR

Autonomous car or “Self-driving car are defined as a motor vehicle that uses an
artificial intelligence, sensor and global positioning system coordinates to drive itself
without the active intervention of a human operator”. When we compare autonomous
car and normal car both are totally different. In the basis of safety manner, comfort, of
the people, in the eyes of pollution and the parts include. Then the components include
in the self-driving car are;
Ultrasonic sensors

Radars

Cameras

Laser scanners

G.P.S. unit

Cloud based 3-d digital map

along this there is a backup system as in the aeroplanes. Now we discuss one by one,
how its work in the autonomous car.

2.1 ULTRASONIC SENSORS

A sensor is a device that detects and responds to some type of input from the physical
environment. There are many types of sensors are there but we use here ultra-sonic
sensors. Ultrasonic sensors may be used to measure the position of objects very close to
the vehicles, such as curbs and other vehicles and support autonomous drive at low
speeds. The sensors are based on the technology used for current park assist functions
enhanced with advanced signals processing. A typical example of when this technology
is useful is for detecting unexpected situations such as pedestrians or hazards on the
road close to the car.

It has four sensors looking backward, four sensors looking forward and four sensors
looking to the side

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 Fig. 2.1 Ultrasonic Sensors

2.2 RADARS

Radar is an objective detection system that uses radio waves to determine the range,
altitude, direction or speed of objective. In self-driving car 4 surrounded radars are use.
It has field of view greater than 140 degrees (Field of view is the area visible through a
microscope or stereoscope. The higher the magnification the small the field view.) It has
3 long range radar of field view greater than 20 degrees of range >150 meter. These four
radars behind the front and rear bumpers cone (on each corner of the car) are able to
locate objects in all direction. By sweeping both left and right, transmitting waves
bounces off signs, poles and tunnels, the monitor a full 360 degree around the car. The
two long range radars placed in the rear bumper of the car ensure a good rewarded field
of view. This technology is particularly useful when changing lanes because it can
defect fast moving vehicles approaching from far behind.

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 Fig. 2.2 Radars

2.3 CAMERAS

Cameras are a device for recording visual images in the forms of photograph film or
video signals. Here we use the trifocal cameras.
Trifocal cameras: In these mainly 3 cameras. The main camera is the popular aril alexia
and two small indie GS2K satellite cameras which creates 3D by combining 3d cine
photography. In addition, a trifocal camera placed behind the upper part of the wind
screen is 3 cameras in one providing a board 140-degree view, a 45-degree view and
along range yet narrow 34-degree view for improved depth perception and distant object
detection the cameras can spot suddenly appearing pedestrians other on expected road
hazards.

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 Fig. 2.3 Cameras

2.4 G.P.S. UNIT AND CLOUD SERVICES

G.P.S. means global positioning system. Signals from GPS satellites are combined with
reading from tachometers, 3-degree freedom of altimeters and 3-degree freedom
gyroscope to provide more accurate position than is possible with GPS alone. A
tachometer is an instrument measuring the rotation speed of a shaft or disk as in a motor
or other machine. It is usually display in RPM (revolution per minute). It is used to
control the speed of the engine. By matching the 360 degrees, image created by the
altitude of sensors with the wrap image. The car will get the information about its
position in relation to the surroundings. By combing the information from the sensors
and the map selfdriving car is able to choose the best course in real time factoring in
variables such as the curvature of the road speed limit, temporary signs and other traffic.

The cloud service is connected to the traffic authorities control centre. This ensures that
the most up to date traffic information is always available. The control centre operation
also operates also have the ability to tell the drivers to turn off the autonomous drive if
necessary.

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 Fig. 2.4 G.P.S. And Cloud Services

2.5 LASER SCANNER

Laser scanning is a versatile tool that can be applied to a multitude of surveying

challenges. High-definition 3D Laser Scanning allows for the effective and safe
completion of surveys of inaccessible, complex and irregularly shaped structures. The
scanner can identity objects in front of the car and ensure very high angle resolution. It
can also distinguish between objects. The unique laser sensor has a range of 150 meters
for vehicles and covers a 140-degree field view. These sensors bounce pulse of light off
the surrounding. These are analysed to identify lane markings and the edge of roads.

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 Fig. 2.5 Laser Scanners

2.6 BACKUP SYSTEM

In addition of all these systems, there is a backup system facility is present as in the
aeroplanes. It is use full if any one component is not working properly while moving.
On that time, it gives a backup system to that component and makes the car moving
safely. This is very essential to the autonomous car. For example: the probability of a
brake system failure is very small but a self-driving vehicle needs a second independent
system to brake the vehicle to a stop as it un likely that the driver will be prepared to
press the brake pedal.

In the event of a technology failure, Waymo’s system is designed to bring the vehicle to a safe
stop. To design its technology to automatically handle faults and failures without relying on a
human driver to take back control, Waymo has completed thousands of hours of development
and testing.

Waymo has installed backups for its vehicle’s most critical safety systems, which
include redundant steering and braking, backup power and computing, and a sensor
suite with overlapping fields-of-view.

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 Fig. 2.6 Back Up System

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 CHAPTER - 3

WORKING PRINCIPLE OF AUTONOMUS CAR

Fig. 3.1 Working of Self-Driving Car

3.1 MAPPING AND LOCALIZING

Prior to making any navigation decisions, the vehicle must first build a map of its
environment and precisely localize itself within that map. The most frequently used
sensors for map building are laser rangefinders and cameras. A laser rangefinder scans
the environment using swaths of laser beams and calculates the distance to nearby
objects by measuring the time it takes for each laser beam to travel to the object and
back. Where video from camera is ideal for extracting scene colour, an advantage of
laser rangefinders is that depth information is readily available to the vehicle for
building a three-

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dimensional map. Because laser beams diverge as they travel through space, it is
difficult to obtain accurate distance readings greater than 100m away using most state-
of-the-art laser rangefinders, which limits the amount of reliable data that can be
captured in the map. The vehicle filters and discreteness data collected from each
sensor and often aggregate the information to create a comprehensive map, which can
then be used for path planning.

For the vehicle to know where it is in relation to other objects in the map, it must use
its GPS, inertial navigation unit, and sensors to precisely localize itself. GPS estimates
can be off by many meters due to signal delays caused by changes in the atmosphere
and reflections off of buildings and surrounding terrain, and inertial navigation units
accumulate position errors overtime. Therefore, localization algorithms will often
incorporate map or sensor data previously collected from the same location to reduce
uncertainty. As the vehicle moves, new positional information and sensor data are used
to update the vehicle’s internal map.

3.2 OBSTACLES AVOIDANCE

A vehicle’s internal map includes the current and predicted location of all static (e.g.,
buildings, traffic lights, stop signs) and moving (e.g., other vehicles and pedestrians)
obstacles in its vicinity. Obstacles are categorized depending on how well they match
up with a library of pre-determined shape and motion descriptors. The vehicle uses a
probabilistic model to track the predicted future path of moving objects based on its
shape and prior trajectory. For example, if a two-wheeled object is travelling at 40 mph
versus 10 mph, it is most likely a motorcycle and not a bicycle and will get categorized
as such by the vehicle. This process allows the vehicle to make more intelligent
decisions when approaching crosswalks or busy intersections. The previous, current
and predicted future locations of all obstacles in the vehicle’s vicinity are incorporated
into its internal map, which the vehicle then uses to plan its path.

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Fig. 3.2 Obstacles Avoidance

3.3 PATH PLOTTING

The goal of path planning is to use the information captured in the vehicle’s map to
safely direct the vehicle to its destination while avoiding obstacles and following the
rules of the road. Although manufacturers’ planning algorithms will be different based
on their navigation objectives and sensors used, the following describes a general path
planning algorithm which has been used on military ground vehicles.

This algorithm determines a rough long-range plan for the vehicle to follow while
continuously refining a short-range plan (e.g., change lanes, drive forward 10m, turn
right). It starts from a set of short-range paths that the vehicle would be dynamically
capable of completing given its speed, direction and angular position, and removes all
those that would either cross an obstacle or come too close to the predicted path of a
moving one. For example, a vehicle travelling at 50 mph would not be able to safely
complete a right turn 5 meters ahead, therefore that path would be eliminated from the
feasible set. Remaining paths are evaluated based on safety, speed, and any time
requirements. Once the best path has been identified, a set of throttle, brake and

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 steering commands, are passed on to the vehicle’s on-board processors and actuators.
Altogether, this process takes on average 50ms, although it can be longer or shorter
depending on

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the amount of collected data, available processing power, and complexity of the path
planning algorithm. The process of localization, mapping, obstacle detection, and path
planning is repeated until the vehicle reaches its destination.

Fig. 3.3 Path Planning

3.4 THE ROAD AHEAD

Car manufacturers have made significant advances in the past decade towards making
self-driving cars a reality; however, there still remain a number of technological barriers
that manufacturers must overcome before self-driving vehicles are safe enough for road
use. GPS can be unreliable, computer vision systems have limitations to understanding
road scenes, and variable weather conditions can adversely affect the ability of on-board
processors to adequately identify or track moving objects. Self-driving vehicles have
also yet to demonstrate the same capability as human drivers in understanding and
navigating unstructured environments such as construction zones and accident areas.

These barriers though are not insurmountable. The amount of road and traffic data
available to these vehicles is increasing, newer range sensors are capturing more data,
and the algorithms for interpreting road scenes are evolving. The transition from
humanoperated vehicles to fully self-driving cars will be gradual, with vehicles at first
performing only a subset of driving tasks such as parking and driving in stop-and-go

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traffic autonomously. As the technology improves, more driving tasks can be reliably
outsourced to the vehicle. This car moves in the road as the speed control board in the
high ways as shown in fig.

Fig. 3.4 Scanning of Speed Control Board

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 Fig. 3.5 Autonomous Car Model

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 CHAPTER - 4

CHALLENGES

The equipment and technologies used are costly the main equipment’s used in this
technology are radar, lidar, position sensor, GPS module, Multicore, heterogeneous
processor, JAUS interoperable communication systems, high resolution cameras are very
costly now. Complex artificial intelligence software the brain of the robotic car is its
intelligent real-time decision-making software to design and implementation of this part
of the system is much more complicated.

Present road conditions may vary and which will affect the decisions made by the software
since our system is mainly based on pure artificial intelligence, the non-ideal conditions and
decisions made by other human drivers may vary. This may affect the ideal operation of the
robotic car.

4.1 CREATING AND MAINTAINING MAPS – DIFFICULT

First, a quick clarification: Lots of car companies, from GM to BMW to Tesla to Uber,
are working on various species of autonomous technology. Some of this is partial
autonomy, as with Honda's Civic LX, a car now on the market that can stay within its
lane. But I'm mostly going to focus on full autonomy — cars that don't need drivers at
all.
And right now, Google seems to be the furthest along with that technology:

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 Fig. 4.1 Creating and Maintaining Maps

4.2 DRIVING REQUIRES COMPLEX SOCIAL INTERACTIONS TOUGH FOR

ROBOTS

A far more difficult hurdle, meanwhile, is the fact that driving is an intensely social
process that frequently involves intricate interactions with other drivers, cyclists, and
pedestrians. In many of those situations, humans rely on generalized intelligence and
common sense that robots still very much lack.

Fig. 4.2 Complex Social Interactions

4.3 BAD WEATHER

Compounding these challenges is the fact that weather still poses a major challenge for
self-driving vehicles. Much like our eyes, car sensors don't work as well in fog or rain or
snow. What's more, companies are currently testing cars in locations with benign
climates, like Mountain View, California — and not, say, up in the Colorado Rockies.

Olson classifies this as a real, but lesser, hurdle. "Weather adds to the difficulty, but it's
not a fundamental challenge," he says. "Also, even if you had a car that only worked in
fair weather, that's still enormously valuable. I suspect it might take longer to overcome
weather challenges, but I don't think this will derail the technology."

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 Fig. 4.3 Bad Weather Makes Everything Trickier

4.4 APPROVAL FOR SAFETY

Another big obstacle for self-driving cars isn't technical — it's political. Before
selfdriving cars can hit the roads, regulators are going to have to approve them for use.
One thing they're going to want to ask is: How safe are these things, anyway? And here's
the tricky part: We probably won't know! Kalra laid this all out in a recent paper for
RAND. As noted above, drivers in the United States currently get into fatal accidents at a
rate of about one for every 100 million miles driven. Ideally, we'd want self-driving cars
to be at least that safe. But it's unlikely we'll be able to prove that any time soon. Google
only drove its cars 1.3 million miles total between 2009 and 2015 — not nearly enough
to draw rigorous statistical conclusions about safety. It would take many decades to drive
the hundreds and hundreds of millions of miles needed to prove safety.

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 Fig. 4.4 How Safe Self-Driving Cars Really

4.5 CYBERSECURITY

"Another issue is cybersecurity," says Kalra. "How do you make sure these cars can't be
hacked? As vehicles get smarter and more connected, there are more ways to get into
them and disrupt what they're doing." This shouldn't be impossible to fix. Software
companies have been dealing with this issue for a long time. But as Vox's Timothy Lee
has written, it will likely require a culture change in the auto industry, which hasn't
traditionally worried much about cybersecurity issues. Olson raises a related issue: Many
car enthusiasts already modify their own vehicles to improve performance. What
happens if they do this for self-driving cars and inadvertently compromise the
computers' decisionmaking ability? "Just as an example, someone puts on oversized
wheels that distorts' the cars sense of how fast it's going," he notes. "It's hard to stop
anyone from doing that."

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 Fig. 4.5 Cybersecurity

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 CHAPTER - 5

CONCLUSION

Despite massive improvement in a traffic safety 1.2 million of people are still in kill
traffic every year. For reduce this problem autonomous car technology is very helpful.
Allowing the car to act automatically is crucial when moving towards the future cars
will not crash at all. The present system for auto braking lane keeping aid and adaptive
cruise control are examples of the first steps towards autonomous driving. Then other
features include road edge and barrier detection with steer assist, which detect if the
near about to drive off the round and autonomously applies steering torque to bring the
vehicles back on track. Autonomous driving will carry significant consumer benefit, it
will fundamentally change the way we look at driving cars. As a driver in the future,
you will be able to plan your drive with a mix of autonomous and active driving,
allowing for efficient use of your daily journey. You could safely interact via phone or
tablets or simply relax. Autonomous driving safely there by paves the way for more
efficient time management behind the wheel. In addition to simplifying people`s lived
and transforming the everyday commute from last time to quality time self-driving cars
create environment benefits. Autonomous driving car is no longer available due to
exceptional weather conditions, technical malfunction or the end of the rotate has been
reached. On this time the driver is promoted by the system to take over again. But
except this car is very useful to the consumers. It is not only useful but also the safer
when compare to the other cars which are present.

To summarize, the technology underlying semi- and fully autonomous vehicles is

welldeveloped and poised for commercial deployment. Major automotive companies
and software developers have made considerable progress in navigation, collision
avoidance, and street mapping.

Governments can accelerate or slow the movement towards self-driving vehicles by the
manner in which they regulate. Addressing relevant issues and making sure regulatory
rules are clear should be high priorities in all the countries considering autonomous
vehicles.

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There remain broader societal and ethical considerations, though, that must be
considered as we move closer to commercialization. For example, if an automated car is
facing the outcome between hitting one child or a group of 10 kids, how does it make
that choice? One can imagine a wide variety of ethical issues that come along and
software designers have to make choices regarding how to deal with them.

In addition, there are important ramifications for the workforce. Uber has around one
million drivers on the road. Phasing in autonomous vehicles likely will mean that at
least some of these individuals will lose their jobs and require retraining for other
positions. Learning how to navigate these economic and social ramifications is a major
challenge facing the world.

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REFERENCES

1) Autonomous Vehicles: Opportunities, Strategies and Disruptions, By Michael E.

McGrath
2) Engineering Autonomous Vehicles and Robots, By Shaoshan Liu
3) http://www.cnet.com/news/a-ride-in-volvos-autonomous-car-how-the-next-step-
indriver-safety-requires-replacing-the-driver/
4) http://www.wired.com/2015/02/volvo-will-test-self-driving-cars-real-
customers2017/
5) http://www.theverge.com/2015/2/23/8091455/volvo-drive-me-self-driving-car-
test2017
6) http://www.SeminarsTopics.com
7) https://www.youtube.com/watch?v=SyMGRqh8J2k
8) https://www.google.co.in/search?q=volvo+self+driving+cars&biw=1366&bih=6
9) 3&source=lnms&tbm=isch&sa=X&ei=5x5JVZLmOYTMmwW5hYDQAw&sqi=2
&ved=0CAgQ_AUoAw
10) Introduction to Self-Driving Vehicle Technology (Chapman & Hall/CRC Artificial
Intelligence and Robotics Series)

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