Session C8
#58
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of Pittsburgh Swanson School of Engineering. This paper is a student, not a professional, paper. This paper is based on
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THE BENEFITS OF LIDAR TO ADVANCEMENTS IN DRIVER ASSISTANCE
SYSTEMS AND THE FUTURE OF DRIVER SAFETY
Stephen Gian, [email protected], Lora 1:00, Garrett Davey, [email protected], Budny 10:00
Abstract — The automobile industry is undergoing one of the
largest revolutions in its history thanks to the implementation
of advanced driver assistance systems (ADAS) in cars today.
These systems are composed of lasers, cameras, and radar that
work with the driver to improve safety and efficiency on our
roads. One standout system that may revolutionize the way we
think about transportation is called LIDAR (light detecting and
ranging). This system works by beaming high speed lasers 360
degrees around the vehicle from a module positioned atop the
car (for maximum sight lines); which then measures the time it
takes between the emittance of the laser and the reflection on
the object it collides with, creating a virtual 3-D
representation of the surroundings. Once the module has
completed its analysis of the surroundings (approximately
every five nanoseconds), pre-programmed algorithms detect
obstacles, lanes, and other cars and direct the car in such a
way that resembles the traditional human driver. Although
these systems are still relatively unheard of to the masses,
significant progress has been made in the evolution of said
technologies within the past two years bringing engineers
closer to the solution for self-driving cars. Autonomous cars
can be seen being tested in Pittsburgh, PA by the worldwide
online transportation company Uber. Although we are on the
horizon of the peak of this technology, there are still some
ethical questions to be answered about unmanned two-ton
machines on our roads. The autonomous car will also
transform our pre-conceived conceptions about transportation
and show us that much will change with coming of the
autonomous vehicle. LIDAR affords the opportunity for
innovators to utilize its technology in the advancement of the
autonomous car and a safer more efficient road in our future.
to digital promises to do to driving what the iPod and streaming
did to music” [1]. Anyone with a cell phone would agree that
getting music today is much more convenient than it was when
they were a child. Automobiles are going through a parallel
transition. In only ten years, the automotive industry has
transformed by applying the newest technology to the cars they
build. Advancements in radar, camera, and laser systems have
led the revolution in Advanced Driver Assistance Systems
(ADAS) [2].
A developing technology, called LIDAR (Light Detecting
and Ranging), is helping to improve the safety and efficiency
of our cars today, and will be essential for advancements in
driver assistance systems and autonomous technology. LIDAR
works by beaming rays of light 360 degrees around the vehicle
and measuring the time it takes for the light to reflect to create
a virtual 3-D representation of the surroundings. This map of
surroundings allows the car to recognize obstacles, hazards,
and lanes of travel with pre-programmed algorithms. LIDAR
systems are also beginning to be manufactured in more
affordable and compact packages, allowing this technology to
become available for more in depth testing and research.
Research and experimentation with vehicles using LIDAR is
proving to be a path that will lead us to the widespread use of
autonomous vehicles in the future.
THE TECHNOLOGY BEHIND LIDAR IN
AUTONOMOUS VEHICLES
The technology behind LIDAR was designed to tackle the
first problem encountered by engineers in the quest for a fully
autonomous vehicle: vision. Computers lack the sense of sight
that many drivers take for granted which is arguably the most
crucial sense to the operation of a vehicle. LIDAR modules
work by emitting lasers from a centrally located unit and
measuring the amount of time it takes for the system to detect
a reflection from the laser off an object. Once the module takes
these measurements and makes calculations about the distance
to the objects, it will create a three-dimensional map of its
surroundings and convert that into a digital copy. The module
also detects static and stationary objects in its vicinity and
accounts for them appropriately in the mapping of its
Key Words – Advanced Driver Assistance Systems (ADAS),
Automobile Industry, Autonomous Driving, Laser, LIDAR,
Sensor, 3-D Mapping
SELF-DRIVING CARS ARE THE FUTURE
The 2016 TIME Magazine article “Forget the Distant
Future, Smarter Cars Are Already Here” states that “Cars are
well into the biggest automotive revolution since Henry Ford
debuted his assembly line. This historic transition from analog
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Garrett Davey
surroundings. The onboard computer of many devices utilizing
LIDAR will then interpret the digital copy of its real-time
surroundings. And from there, in automobiles specifically,
software with pre-programmed algorithms guides the vehicle
as if a human were driving behind the wheel by staying on the
road, within the lanes, and turning with the curves. But above
all, one of the most important aspects to LIDAR in
autonomous vehicles is that it will keep passengers and
pedestrians safe by recognizing them before a human and
avoiding them at all costs. This will save lives and money by
preventing accidents on our roads. LIDAR is composed of
many different parts that make it a revolutionary technology
capable of changing the way we view transportation.
LIDAR in autonomous vehicles consists of what is
basically a rotating module positioned at a high, central
location on a vehicle for maximum sight lines and greatest
distance viewed. The LIDAR module itself can be compared
to a small potted plant with openings for the lasers to be
emitted. The system works by sending out very bright pulses
of infrared light while rotating to ensure that three hundred and
sixty degrees of the vehicle are mapped at all times. These
sensors are running at approximately nine-hundred and five
nanometers, which means that this light is invisible to the
human eye and is extremely densely packed. Every five
nanoseconds a seventy-five to one-hundred watt burst of light
is emitted from the module. This light goes out as a very tightly
packed and collimated burst so it does not spread. It is
necessary for the light to be in this form because the LIDAR
must be able to keep track of the laser it emits so that it can
produce an accurate map of its surroundings. Once the lasers
reach their respective obstacles, the first object in its path will
reflect the laser beam and that is what registers with the module
back atop the vehicle. A timer begins when each laser is
emitted and ends when the reflection of light is detected by the
extremely sensitive sensors in the module. Since the speed of
the light is very constant at 3.00𝑥108 𝑚/𝑠, this yields a
distance from the vehicle that an obstacle lies. The computer
uses the equation
dimensional image that a computer can read and interpret [3].
Senior Engineer, Scott Boehmke of Uber Advanced
Technology Group (ATG), is well versed in the hardware of
LIDAR and agreed to speak with us about this developing
technology. He gave us insight into the future of autonomous
cars when he said “You can imagine if you drove around town
and you did this enough times, you can get a good idea of what
is static and what is stationary, what is something that’s new,
or something that’s most likely moving around. It might be a
pedestrian, it might be a car, it could be a box in the road.
Those comparisons help you to navigate the world” [3]. The
software also includes a section called “prediction” where it
will recognize moving objects and predict their path.
While this is how LIDAR functions in an autonomous
vehicular environment, LIDAR functions similarly in other
applications such as agriculture and tunnel mapping. This
technology when alone is nearly useless, but when paired to
machines that require the observations of its surroundings in a
three-dimensional manner, it can become a practical
alternative to constant human attention. And although this
technology only makes up a fraction of the autonomous car, it
is critical to its success because of its bridge between the
natural and mechanical worlds.
𝑚
𝑆𝑝𝑒𝑒𝑑 ( ) ∗ 𝑇𝑖𝑚𝑒(𝑠) = 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒(𝑚)
𝑠
FIGURE 1 [3]
Distance derived from speed and time measurements.
FIGURE 2 [3.5]
Figure [2] represents the car that Mr. Boehmke and his
team of engineers have developed for Uber Advanced
Technology Group (ATG). It can often be seen patrolling
the streets of Pittsburgh with a driver in the driver’s seat
in case of disengagement, and another engineer in the
passenger seat collecting data.
to find the distance from the vehicle the object lies. As the
LIDAR fires these beams over and over in a vertical line in one
single rotation, it takes in the world as we see it, but instead in
very short periods of time and distance, therefore creating a
view similar to what we see with our eyes. LIDAR
distinguishes itself from cameras because it is able to detect
depth, therefore making a three-dimensional map possible. It
is also capable of interpreting information over multiple
rotations and then integrating that over time to detect moving
objects in its path. No matter the size of the obstacle or the
slightest change of depth, the LIDAR will be able to detect it
with its extremely sensitive sensors and produce a three-
THE APPLICATIONS OF LIDAR TO THE
AUTOMOBILE INDUSTRY
LIDAR’s revolutionary technological capabilities can be
applied to a magnitude of different applications from
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surveying to cartography, but one of the foremost applications
of LIDAR is the autonomous vehicle. In Yong In, Korea
researchers are currently working on the answer to the
autonomous vehicle at the Hyundai MOBIS smart car research
center. And in recent years, the “practical achievement on
autonomous driving tasks of a personal vehicle becomes the
most concerned subject for car industries in the world” per the
article “Experimental Studies of Autonomous Driving of a
Vehicle on the Road Using LiDAR and DGPS” [4]. Leading
automotive companies of the world such as Mercedes-Benz,
Volvo, Ford, and more are currently competing against each
other in the development of the autonomous car. This
competition does not only include these companies, but also
global IT companies such as Google, Apple, and Uber. This
hyper competition between multi-billion dollar firms for the
world’s first autonomous vehicle will bring this technology to
the roads before many citizens would expect to be chauffeured
by their own vehicle. For the past 8 years or so, fleets of
autonomous vehicles have been tested in unison with human
drivers, which presents itself as an engineering miracle alone.
Most experts would agree that engineers are eighty-five to
ninety percent of the way to perfecting the hardware, guidance
systems, and software that can reliably and safely drive
themselves [5]. But they would also agree that the last ten
percent is going to be the hardest to overcome. This last ten
percent includes rare situations where the technology is not
capable of seeing due to bright light exposure or when a road
is poorly marked. Other questions looming in the future of
autonomous vehicles might be who is at fault when an accident
does occur? Or who will an autonomous car put in danger first:
the driver or the pedestrian in an emergency situation? But for
those of you reading who aren’t quite ready to give up your
driving rights yet, don’t worry. Consumer Reports estimates it
will take decades before autonomous cars replace human
driven cars in significant numbers [5]. Even Mr. Boehmke
agrees that autonomous vehicles will not become part of our
daily commutes for many decades [3]. But to say the least, the
use of this technology in vehicles is one of the most exciting
innovations to come in our lifetimes. It will without a doubt
revolutionize the way people think about all transportation.
The first challenge posed to engineers while developing an
autonomous vehicle is how will a machine see its surroundings
just as a human would behind the wheel, and interpret this data
like the human brain? LIDAR is a practical solution to this
problem because it goes farther than a camera and takes depth
and distance into account. The hardware observes its
surroundings in three-dimensions (x,y,z), acting as the eye, and
the software interprets the moving image, acting as the brain.
And although the LIDAR itself only makes up a portion of the
system used in autonomous cars, it is still one of the most
important components because of its ability to imitate the
human eye.
LIDAR in vehicles has the possibility of making a car
completely autonomous by observing its surroundings and
translating that image into interpretable data for the computer
to read. Once the LIDAR has a valid image and the computer
is able to completely understand the received image, the
algorithms in the software guide the car through a complex
series of programs based off the image the LIDAR transmits
to the computer. LIDAR is being used in automobiles for the
sole purpose of creating the autonomous car. People have
already begun designing LIDAR packages fit for the use in
cars. According to the research proposal “A 2D Resonant
MEMS Scanner with an Ultracompact Wedge-like Multiplied
Angle Amplification for Miniature LIDAR Application”, this
application has already “…recently created a new demand for
low-cost, low-power and small-package three-dimension
LIDAR” [6]. This article proposes an ultra compact LIDAR
system that minimizes voltage usage, cost, and maximizes
reliability. This demonstrates the industries seriousness about
the autonomous car and how LIDAR plays an important role
in the development and design of autonomous systems.
The Benefits of LIDAR and Autonomous Vehicles to
Society
In 2014, ninety-four percent of accidents were attributed to
human error or choice, causing over thirty thousand deaths in
the United States and another one point two million worldwide
[7]. This statistic must be lowered, and can be done with the
help of autonomous vehicles. In an ideal world, a computer is
the safest driver of them all: it does not get distracted behind
the wheel, it does not drive drunk, and it does not speed. All of
which are the leading factors in accidents caused by humans.
So now Imagine a world where the roads are free of accidents
and deaths, because it is possible with the help of autonomous
vehicles.
Another benefit of autonomous vehicles is the time freed up
when spent as a passenger rather than a driver. Autonomous
vehicles utilize DGPS to guide them from point a to point b.
This means that drivers will suddenly no longer be a driver and
rather a passenger. That allows drivers to spend their time
doing something they’d rather do which prevents accidents and
gives the driver the opportunity to spend that time lost driving
on another task.
LIDAR in Modern Automobiles
Engineers have struggled to harness the powerful
capabilities of the human brain like the senses of sight, smell,
hearing, and touch in a system and translate them into data.
Although there is nothing manufactured quite like the human
brain (yet), LIDAR seems to be the solution when talking
about sight and autonomous vehicles because it serves as the
first step in the mechanical interpretation of the vehicle's
surroundings. The technology is revolutionary because it can
replicate the sense of sight that is taken for granted by many
humans. Cameras have been able to do this for over a century
now, but the challenge arises when translating that image into
data for a computer to read while also incorporating depth.
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Autonomous cars can also be the solution to a greener
highway when paired with the developing clean vehicle
market. The EPA has pushed for a greener highway in hopes
of raising the average mile-per-gallon to fifty miles per gallon
by twenty twenty-five, more than double the average today [8].
“This is possible because the combustion engine-based cars are
now gradually transformed into motor-driven electric cars,
which can be thought of as mobile robots. Eventually, once
mobile robot technologies for unmanned navigation have been
intensively developed they can be directly applied to
autonomous driving tasks of electric cars” according to the
article, “Experimental studies of autonomous driving of a
vehicle on the road using LiDAR and DGPS” [4]. This will
benefit society by making the future a healthier place for
coming generations, sparing them of terminal lung diseases
and cancer from pollution directly created from the millions of
vehicles in use today.
A final benefit to autonomous vehicles may be a connected
grid that could possibly make commutes faster while still
obeying the all traffic laws. If all cars were synced to a
common grid and programmed to their final destination, most
predictable congestion could theoretically be eliminated from
commutes. This would be possible because the main source of
congestion, human incapability of driving, would be
eliminated by the computer driver and a streamlined flow of
vehicles could be possible. Cars connected in a common
system would rather move as one system then individually
unrelated cars, making it possible for the aforementioned
congestion to be diminished making everyone’s driving
experiences less stressful and safer.
FIGRURE 2 [8.5]
An example of what LIDAR observes and translates to
computer image
This would be an example of what the LIDAR hardware
observes and translates that into something readable by
computer code. The software then makes the decisions on how
the car drives itself.
THE ETHICS OF AUTONOMOUS
VEHICLES
Ethical Dilemmas Raised by the Possibility of
Pedestrian/Driver Injuries
The biggest concern about autonomous vehicles or
autonomous technology is the question of whether we should
trust technology to safely maneuver a two-ton machine with a
human inside. Even with the most updated LIDAR system and
complex coding, the computer in a self-driving car lacks one
thing that humans have: the ability to think for itself. Scott
Boehmke cites a specific example of a time when critics of this
technology might make a case against it, a situation where a
driverless vehicle is in a position where it must choose between
injuring two different pedestrians, or choose between injuring
the driver of another vehicle and the person inside itself [3].
This ethical dilemma is recurring throughout media, as seen in
the article “Driverless Cars Will Face Moral Dilemmas” by
Larry Greenemeier of Scientific American, which opens with
“A self-driving car carrying a family of four on a rural twolane highway spots a bouncing ball ahead. As the vehicle
approaches a child runs out to retrieve the ball. Should the car
risk its passengers’ lives by swerving to the side—where the
edge of the road meets a steep cliff? Or should the car continue
its path, ensuring its passengers’ safety at the child’s expense?”
[9].
In a situation like this where a vehicle with autonomous
technology seriously injures someone, would result in lawsuits
and harsh litigation, and probably jeopardize the future of
autonomous vehicles. Last year, a crash involving a Tesla in
its autopilot mode resulted the fatality of the driver. Per the
article “Nation’s first known self-driving car fatality happened
in Williston” from The Gainesville Sun, “...the vehicle was on
a divided highway with Autopilot engaged when a tractor
trailer drove across the highway perpendicular to the Model S.
Neither Autopilot nor the driver noticed the white side of the
tractor” [10]. After the crash, Tesla said that “Had the car hit
the front or rear of the trailer, even at high speed, its advanced
Local LIDAR – Uber Technology Inc. in Pittsburgh
While researching this intriguing technology, we had the
opportunity to speak with a hardware engineer, Scott Boehmke
(as mentioned before), working for Uber ATG here in
Pittsburgh. He was able to give us a great deal of information
on the LIDAR system and how it worked. Without his insight
our paper would be significantly less thorough and
comprehensive. Uber chose Pittsburgh as its testing site for
autonomous vehicles because of its advanced terrain like tight
turns, steep and frequent hills, and oddly shaped and marked
roads. The data collected in Pittsburgh will help in the
development of the autonomous car one day available for sale
by the public. It is an incredible opportunity for us to be able
to see the technology of the future on our streets being
spearheaded by leaders in the engineering field like Mr.
Boehmke. He was able to give us invaluable insight into the
developing autonomous vehicle industry.
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crash safety system would likely have prevented serious injury
as it has in numerous other similar incidents, the company
added” [10]. This specific example illustrates why critics may
raise ethical concerns; Would the driver had noticed the trailer
if he didn’t put his trust in the autopilot mode of the Tesla?
Someone may argue that autonomous vehicles are more
dangerous this way in that they give the driver a false sensation
that they don’t need to pay attention to the road as much as
they normally would.
Analyzing situations in which human intuition is replaced
with artificial intelligence using LIDAR and autonomous
technology effectively illustrates that there is rationalism for
ethical concerns. However, the future of LIDAR shows
promise for minimizing these concerns. New developments
from the engineering community and automobile industry
show that specific ethical dilemmas can be targeted with
advancements in LIDAR systems to ensure the continuing
growth of autonomous vehicles.
eight experiment sequences, the proposed method was tested
in moving vehicles, stationary vehicles, vehicles that would
stop and go, and data was collected in both rural and urban
areas, from highways to alleyways. This research turned out to
be very valuable and successful. Per the article, “Experiments
on the KITTI dataset, using point-cloud data obtained by a
Velodyne LIDAR and localization data from an Inertial
Navigation System (GPS/IMU), demonstrate the applicability
of the proposed method for the representation of dynamic
scenes. The system was proven robust and accurate, as the
result of both a quantitative and a qualitative evaluation” [11].
The results of these experiments are important because they
show that there is a vast potential for new methods of 3D
perception of dynamic environments using laser and sensor
technology, which is one of the key components for intelligent
vehicles to operate in real-world environments. The highly
descriptive 3D representation created using an intelligent
vehicle equipped with a Velodyne LIDAR and Inertial
Navigation System (GPS/IMU) “...has an application in safety
systems of the vehicle to avoid collisions or damages to the
other scene participants” [11]. If an autonomous vehicle is
already equipped with smart enough technology that avoids
collisions in the first place, it has a higher potential to
completely avoid situations where the system must choose
between the safety of the driver and the driver of another car,
or choose between hitting a young child or an elderly adult.
This is just one example of a solution to the ethical dilemma
cited by Scott Boehmke, where the LIDAR system on an
intelligent vehicle replaces a careful, defensive driver.
Solutions to Ethical Dilemmas Through Research on New
LIDAR Methods
In reference to his example about LIDAR systems having
to calculate a decision about which person to injure in a worstcase scenario situation, Scott Boehmke continues; “...I think
that we are striving to a solution to the problem that doesn't get
into these type of situations, where it needs to make ethical
decisions like that. You can be a very defensive driver and
never ever have an accident, even as a human. So why can't we
get the cars to be that careful also?” [3]. This is one specific
example of how the research and development of LIDAR is
contributing to the solution of an ethical concern. Engineers at
companies like Uber Technologies Inc. are striving to ensure
that LIDAR can ensure the safety of the driver of an
autonomous vehicle and obstacles this vehicle must face when
in motion. For example, a July 2016 article from Institute of
Systems and Robotics, Department of Electrical and Computer
Engineering, University of Coimbra - Polo II, called “3D
Lidar-based Static and Moving Obstacle Detection in Driving
Environments: An Approach Based on Voxels and MultiRegion Ground Planes,” proposes a solution to obstacle
avoidance [11]. This in-depth article details the analysis of a
Velodyne LIDAR, the same system Uber uses in their
autonomous vehicles, and how this LIDAR, along with
computing power, can utilize different methods to determine
the mobile status of different obstacles and predict where these
obstacles are going to be in relation to the vehicle to avoid
collisions.
Two contributions researched in this article are: 1) A
piecewise surface fitting algorithm, based on a ‘multi-region’
strategy and Velodyne LIDAR scans behavior, applied to
estimate a finite set of multiple surfaces that fit the road and its
vicinity, and 2) A 3D voxel-based representation, using
discriminative analysis, for obstacle modeling [11]. Various
experiments were conducted using this two-part method, and
results were analyzed so it could be evaluated. In a total of
THE FUTURE OF LIDAR AND
AUTONOMOUS VEHICLES
The last section explored a specific example of a team of
researchers that developed and analyzed an experiment to test
new methods for obstacle detection and tracking using a
LIDAR system. Research like this is extremely valuable to the
future of autonomous vehicles, not just for technical purposes,
but because it de-mystifies the futuristic idea of vehicles that
drive themselves. It shows that our current systems can be
improved upon indefinitely; similarly to the way Apple
updates the iPhone, existing LIDAR can be researched and
experimented upon to make the old version obsolete. In the
timeline of universal autonomous driving, one of the biggest
limiting factors is money. For example, one of the key points
mentioned in the article “3D Lidar-based Static and Moving
Obstacle Detection in Driving Environments: An Approach
Based on Voxels and Multi-Region Ground Planes” was that
the 3D measurements in the form of a point-cloud required
large memory and high computational power, which is
expensive to produce [11]. Even Scott Boehmke is skeptical
about a speedy transition to autonomous vehicles for this
reason. He stated that the LIDAR used on their self-driving
cars at Uber has been quoted around $75,000 a piece, not
including the automobile [3]. This is a substantial cost,
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considering the transaction price for a new car in March 2016
was $33,666 [12]. When asked “Do you foresee a future where
our vehicles are driverless or have a driverless feature?”
Boehmke responds “I guess way down the road that may be
true, but the technology is still fairly expensive, and not
necessarily very sexy. You probably wouldn't run out and buy
a car that looks like one of our cars, and pay the premium to
have it be self-driving. So, we’re not going to see everyday
vehicles for a consumer driving everywhere for a while still.
But it’ll happen” [3]. The end of his statement gives an
optimistic look to the future, as does the IEEE article “Lidar
That Will Make Self-Driving Cars Affordable” by Evan
Ackerman. This article argues that solid-state LIDAR, which
“...uses an optical phased array to steer laser pulses rather than
a rotating system of mirrors and lenses” can revolutionize the
autonomous vehicle industry because of its affordability and
compactness [13].
At the Massachusetts Institute of Technology, researchers
and students are in the process of developing a system of solidstate LIDAR that can be condensed onto a single 0.5- by 6millimeter chip that can be fabricated in commercial CMOS
foundries. Although MIT’s prototype has a range of only a few
meters, “...there is a clear development path toward a 100meter range and a per-chip cost of just $10” [13]. The market
for small, affordable LIDAR systems such as the one being
researched and developed by MIT is immense compared to the
market for the standard bulky, expensive Velodyne HDL-64E
systems. Therefore, Velodyne is working with investments
from larger companies such as Ford and Baidu to “...make a
$100 automotive LIDAR sensor available within the next few
years” [13]. If a large well-known company like Velodyne can
produce compact, ergonomic LIDAR systems at a cost of
$100, it could mean the commercialization of affordable selfdriving cars soon.
assembly line began rolling in 1913, automobiles have been
notoriously unsustainable until modern developments. The
gases released from the exhaust pollute our air and earth,
collisions result in countless injuries and fatalities, and traffic
congests our streets and obstructs the natural beauty of the
world. Autonomous vehicles driven by LIDAR systems
present sustainable solutions to these unsustainable tendencies.
Imagine a technology smart enough to replace what was
once only able to be completed by hand. It has been done
before with fully automated assembly lines and can be done
again with autonomous vehicles. Although the current focus of
autonomous systems is on the personal vehicle, many other
vehicles are operated by humans and have the potential for full
automation. Public buses and commercial trucks are some of
these vehicles that have the potential to one day be
autonomous. This opens a whole realm of possibilities to
transform transportation on a basic level. Autonomous
vehicles will be able to reinvent the definition of
transportation; instead of a person being responsible for every
aspect of transportation from one place to another, such as gas,
directions, focus, and concentration, a new era of
transportation will show them that one day it will be as simple
as telling your car where you want to go and it will drop you
off steps away from the entrance and even park itself. When
you’re ready to leave, just hail the car with your smart phone
and once again you’re off. The possibilities are endless when
you think about how much this invention could transform our
world. Autonomous vehicles will revolutionize public
transportation by fully automating bus routes in endless cycles
that never run late and are always reliable. Large scale mass
autonomous transportation of goods could also become a
possibility eliminating the complicated logistics of drivers and
captains, completely replacing the human truck driver
allowing for quicker delivery and a faster economy. Public
transportation can be greatly improved with autonomous
systems allowing more extensive roots, longer hours, and
increased reliability.
Autonomous driving integrates modern, upcoming
generations, and older generations of society because of the
combination of computers with mechanically-driven cars.
Automobiles have been around since before our grandparents
can remember, but LIDAR is a relatively new technology.
Each generation is more familiar with each technology,
respectively.
Therefore,
intragenerational
and
intergenerational equity is possible because both young and
old people have something to relate to and be excited about.
This first step towards sustainable development is exciting
because it promotes decision-making towards environmental
and economical productiveness. Once society understands the
benefits of autonomous driving, the sustainable characteristics
of the topic will result in forward thinking and actions from
society towards a result of a cleaner environment and better
overall quality of life.
Holistically the basics of transportation will be redefined at
the most acute level when all types of transportation are
automated. People will eventually never know the
SUSTAINABILITY AND ITS IMPACT ON
SOCIETY
According to the 2012 Rio+20 United Nations Conference
on Sustainable Development, sustainability is defined as such:
“Sustainable development emphasizes a holistic, equitable and
far-sighted approach to decision-making at all levels. It
emphasizes not just strong economic performance but
intragenerational and intergenerational equity. It rests on
integration and a balanced consideration of social, economic
and environmental goals and objectives in both public and
private decision-making” [14]. There are two deeper meanings
derived from this definition: 1) For a development or
innovation to be sustainable, it must satisfy the interest of
quality of life pertaining to modern society without taking
away from other generations, the environment, or the economy
and 2) It must promote forward-moving decision making in
public and private society. In our modern society, for an
engineering topic to be valuable it most likely has advantages
that pertain to some form of sustainability. Since Henry Ford’s
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Garrett Davey
inconvenience of a full parking lot when they’re car could have
driven itself to the next town and back by the time they were
done in the store and ready to be picked up at the door. This
technology will also revolutionize the preconceived
stereotypes of a two, three, or even four car family when one
car could theoretically replace all four. The improvements for
society are boundless when introduced to the autonomous
vehicle. The next hardest part will be convincing the world that
autonomous vehicles are a safer, cleaner, more efficient mode
of transportation compared to their current daily commute.
pollution, just to name a few. LIDAR has the potential to
change the automobile industry and our lives for the better, and
we’re just steps away from the peak of the revolution.
SOURCES
[1] K. Steinmetz. “Forget the Distant Future, Smarter Cars Are
Already Here.” Time Magazine. 4.7.2016. Accessed
1.10.2017.
http://content.ebscohost.com/ContentServer.asp?T=P&P=AN
&K=113323734&S=R&D=aph&EbscoContent=dGJyMNLr4
0Sep644yNfsOLCmr0%2Bep7RSsai4Sa6WxWXS&Content
Customer=dGJyMO7f8oy549%2BB7LHfi%2B4A
[2] “Advanced Driver Assistance Systems (ADAS).”
AutoBlog 1.1.2016. Accessed 1.10.2017.
http://www.autoblog.com/driver-assist-technology/
[3] S. Boehmke. Conference call on Zoom. Hardware
Engineer. Uber Technologies, Inc. Advanced Technology
Group. Pittsburgh, Pa. 2.2.2017.
[3.5] Abboud, Sarah. “Self-Driving Uber Sensor Suite”. Uber
ATG.
[4] J. Ku Kim, J. Wook Kim, J. Hyung Kim, T. Hyung Jung,
Y. Jun Par, Y. Ho K, and S. Jung. “Experimental Studies of
Autonomous Driving of a Vehicle on the Road Using LiDAR
and DGPS”. 10.16.2015. Accessed 1.26.2017.
http://ieeexplore.ieee.org/document/7364852/
[5] Plungis, Jeff. “Driving Into the Future.” Consumer Reports.
4.2017. p.13-17.
http://www.consumerreports.org/autonomous-driving/selfdriving-cars-driving-into-the-future/
[6] L. Ye, G. Zhang, Z. You. “A 2D Resonant MEMS Scanner
with an Ultracompact Wedge-like Multiplied Angle
Amplification for a Miniature LIDAR Application.” Sensors,
2016 IEEE. Accessed 1.26.2017.
http://ieeexplore.ieee.org/document/7808932/
[7] “On the Road.” Waymo. Accessed 3.2.2017.
https://waymo.com/ontheroad/
[8] D. Kiley. “EPA Firms to Move up Fuel Economy
Regulations Before Trump Takes Office.” Forbes. 11.30.2016.
Accessed 3.2.2017.
https://www.forbes.com/sites/davidkiley5/2016/11/30/obama
s-epa-moves-to-firm-up-fuel-economy-regs-before-trumptakes-office/#2f1a6ce6c482
[8.5]
“HDL-64E”.
Velodyne
Lidar.
http://velodynelidar.com/hdl-64e.html
[9] L. Greenemeier. “Driverless Cars Will Face Moral
Dilemmas.” Scientific American. 6.23.2016. Accessed
3.1.2017.
https://www.scientificamerican.com/article/driverless-carswill-face-moral-dilemmas/
[10] C. Swirko. “Nation’s First Known Self-Driving Car
Fatality Happened in Williston.” Gainesville.com 6.30.2016.
Accessed 1.10.2017.
http://www.gainesville.com/news/20160630/nations-firstknown-self-driving-car-fatality-happened-in-williston
WHY LIDAR IS SO IMPORTANT
Throughout history, cars that drive themselves have always
been something out of a science fiction movie or a children’s
cartoon. Autonomous vehicles have been projected to be a
thing of the distant future; something humans will not achieve
until the time of the Jetsons. In a way, common media has
created a stigma around the idea of self-driving vehicles, that
they are something fun to think about, but not realistic or
productive. However, modern developments in LIDAR
systems suggest that this is not necessarily the case.
Autonomous driving using LIDAR is a perfect example of
how engineers use science for real-world applications.
Although LIDAR may seem very complicated and futuristic to
the average person, the physics behind it are easy to
understand. The simple scientific idea of using a laser, sensor,
and basic kinematics equation to calculate the distance to a
certain point in space is the basis of 3D mapping. This
kinematics equation is simple enough for a regular nonscientist to understand, when explained in layman’s terms.
With this background knowledge, the idea of a 3D map
generated by a rapidly spinning laser and sensor system can be
visualized.
If the average person can visualize the idea that an
engineered device can visualize and interpret the world the
same way humans do, understanding autonomous vehicles is
not far away. The reason why all of this is important is because
the ability of society to understand something in the scientific
community makes that topic seem more relevant and less
futuristic. The truth is that we are not far away from
commercializing and normalizing self-driving cars, and while
the scientific community may understand this, the average
person might still think this concept is irrelevant. That’s why
all this matters.
LIDAR is the key to the normalization of the autonomous
vehicle industry. Research that results in the advancement of
LIDAR systems not only strengthens the technology, but
creates solutions to ethical dilemmas that come along with
autonomous technology. Eventually, we will get to a point
where most or all automobiles are equipped with some type of
LIDAR system that will provide the vehicle with either
Advanced Driver Assistance Systems or some type of selfdriving or autopilot mode. The benefits to society of this
revolution are endless; some of the benefits include safer
streets and highways, time-efficient traffic, and reduction in
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[11] A. Asvadi, C. Premebida, P. Peixoto, U. Nunes. “3D
Lidar-based Static and Moving Obstacle Detection in Driving
Environments: An Approach Based on Voxels and MultiRegion Ground Planes.” 7.11.2016. Accessed 1.26.2017.
http://web.a.ebscohost.com/ehost/command/detail?sid=f4847
929-1358-4029-9297360aafadbffb%40sessionmgr4009&vid=20&hid=4209
[12] “New-Car Transaction Prices Up 2 Percent In March
2016, Along With Increases In Incentive Spend, According To
Kelley Blue Book.” Kelley Blue Book. 4.1.2016. Accessed
2.28.2017.
http://mediaroom.kbb.com/new-car-transaction-prices-up-2percent-march-2016
[13] E. Ackerman. “Lidar that will Make Self-Driving Cars
Affordable.” 10.14.2016. Accessed 2.28.2017.
http://rt4rf9qn2y.search.serialssolutions.com/?genre=article&
title=IEEE%20Spectrum&atitle=Lidar%20that%20will%20m
ake%20selfdriving%20cars%20affordable%20%5BNews%5D.&author=
Ackerman%2C%20Evan&authors=Ackerman%2C%20Evan
&date=20161001&volume=53&issue=10&spage=14&issn=0
0189235
[14] Rio+20 United Nations Conference on Sustainable
Development. Accessed 23.30.2017.
https://sustainabledevelopment.un.org/rio20.html
to give special thanks to Scott Boehmke, a Hardware Engineer
at Uber Technologies, Inc. who allowed us to interview him
with questions and quote him in our paper.
ADDITIONAL SOURCES
J. K. Gurney. “Crashing into the Unknown: An Examination
of Crash-Optimization Algorithms Through the Two Lanes of
Ethics and Law.” 3.8.2016. Accessed 1.10.2017.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2622125
C. H. Jang, C. S. Kim, K. C. JO and M. Sunwoo. “Design
Factor Optimization of 3D Flash Lidar Sensor Based on
Geometrical Model for Automated Vehicle and Advanced
Driver Assistance System Applications.” International Journal
of Automotive Technology, Vol. 18, No. 1, 147-156.
10.12.2016. Accessed 1.26.2017.
http://link.springer.com/article/10.1007/s12239-017-0015-7
ACKNOWLEDGEMENTS
We would first like to thank Dr. Daniel Budny for putting
together the Swanson School of Engineering First Year
Conference and giving us the priceless opportunity to establish
ourselves in the engineering community. We also would like
to thank our conference co-chair, Danielle Broderick, and
conference chair, Jared Andes for guiding us throughout the
writing and preparation processes. We would like to thank
Emma Solak and Amanda Brandt in the Pitt Writing Center for
getting us started and giving us helpful advice for our paper.
We’d also like to say thank you to our friends and family for
believing in us, and taking the time to travel to Pittsburgh to
watch our engineering careers blossom. Finally, we would like
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