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Disclaimer—This paper partially fulfills a writing requirement for first year (freshman) engineering students at the University
of Pittsburgh Swanson School of Engineering. This paper is a student, not a professional, paper. This paper is based on publicly
available information and may not provide complete analyses of all relevant data. If this paper is used for any purpose other than
these authors’ partial fulfillment of a writing requirement for first year (freshman) engineering students at the University of
Pittsburgh Swanson School of Engineering, the user does so at his or her own risk.
Colleen Molczan, [email protected], Mahboobin, 10:00 Audrey Case, [email protected], Mena Lora, 1:00
the accident could have been avoided if the Tesla had a
LiDAR unit, seeing as the LiDAR would have been able to
technology is the ability of machines to sense the world
more accurately measure the distance from the ground at the
around them. If airplanes, topographical drones, ocean
speed the car was travelling (around 60mph) [2]. LiDAR is
surveyors, and autonomous cars did not have this ability
a vital part of the vision of AVs, and adds a component that
they would become not only obsolete but also dangerous.
radar and cameras alone simply do not and cannot provide.
The development of various scanning and sensing
LiDAR is critical for the development of safe and reliable
technologies for machines is vital for the continuation of
AVs, because camera and radar alone is not enough. LiDAR
innovations of technology. LiDAR is one of the best methods
is a necessary component to AVs for the safety of everyone
of “vision” that a machine can have. LiDAR stands for
on the road. [3].
Light Detection and Ranging and is a remote sensing
In this paper we will further discuss how LiDAR works,
method that uses pulsed laser beams to judge the ranges
as well as benefits, and possible risks of LiDAR in the
(distances) between objects. This technology is vital to the
context of Autonomous Vehicles. We will further delve into
advancement of autonomy and as more complex systems of
the role that LiDAR plays in making AVs ubiquitous in the
LiDAR are designed its uses become even more widespread
future as well as analyzing the consequences faced if
than its current expanse. In this paper we will analyze one
LiDAR is not used in AVs. Furthermore we will discuss the
of the most important uses and applications of LiDAR
effects of this technology on society and sustainability;
technology in autonomous vehicles (AVs).
specifically how it has spurred the production of energy
LiDAR works by firing rapid pulse beams of light,
saving technology, has the potential to save tens of
sometimes as many as 150,000 pluses per second, and
thousands of lives, and can help bring along a more
measuring the amount of time it takes for those photons to
environmentally friendly society.
return to the sensor. The LiDAR unit then does a series of
calculations and makes a 3D map of its surroundings.
Because of LiDAR’s superior mapping capabilities it has
innumerable applications, including everything from tree
surveying, to AV sensing, to gravitational wave monitoring
in the atmosphere. Although all of these applications are
A LiDAR unit shoots out electromagnetic, and measuring
important one of the most innovative and interesting uses of
the amount of time it takes for those photons (traveling
LiDAR is the use of LiDAR in AVs which we will analyze in
light) to return to the sensor [4]. Using the known speed of
this paper as well as LiDAR’s sustainability both
light the distance of the point from the LiDAR can be
economically and environmentally.
calculated by multiplying the speed of light, 299,792,458
meters per second, by the time it took for the light to return
Key words -LiDAR, Autonomous Vehicle, laser mapping,
divided by two [4]. From that data and integrated GPS,
Sensing technology, driverless
Inertial Measurement Unit systems, and scan angles the
LiDAR unit is able to create a bunch of points called a point
cloud [4]. It connects those data points to create a highresolution map of its surroundings; LiDAR can normally
On May 7th 2016 a Florida man had Autopilot activated
map its surroundings with extreme accuracy for around one
in his Tesla when both he and the Tesla failed to recognize
hundred meters each way [5]. LiDAR has existed for many
a white 18-wheeler against a bright sky [1]. The Tesla
years used mainly for topographical mapping and
proceeded to accelerate under the 18-wheeler, killing the
bathymetric mapping, although it is used for a myriad of
passenger, then crashing into numerous power lines before
things. LiDAR can be applied to many pre-existing
finally coming to a stop [1]. This was the first recorded fatal
technologies to enhance their current capabilities. One
accident caused by an autonomous vehicle [2]. The Tesla
major example of this is the application of LiDAR as a
cameras were blinded by the bright light, and the height of
sensing method in Autonomous Vehicles.
the truck made the radar believe that it was an overhead
sign, making it not employ the breaks [2]. Experts agree that
Abstract—One of the most important innovations in
University of Pittsburgh, Swanson School of Engineering
Audrey Case
Colleen Molczan
model is particularly useful to Google because, according to
the product specifications on the Velodyne website it can
rotate 360-degrees horizontally which enables the car to
map not only possible obstructions in front of it, but to also
keep track of cars behind it, to its sides, and eliminates the
“blind spot” of the car [8]. The unit has the ability to scan
2.2 million points per second from 120m away with the
accuracy of within two centimeters [8]. This makes the
Velodyne LiDAR unit one of the most accurate units on the
market; this is vital for everything from averting accidents
to not running over curbs [8]. As shown in Figure one the
LiDAR is mounted on top of the car so as to avoid
obstructions and is used to gather these highly accurate
readings, along with the camera and radar sensors attached
at the front and the rear of the Google Car. All of these
sensors work in tandem to ensure that the Google Car
doesn’t move unnecessarily; all three are needed because
they together paint a clear picture. Individually however
they have their limits, as shown in the fatal Tesla accident
Those qualities of extreme accuracy and speed are what
make LiDAR a vital and life saving technology. AVs have
to be able to make split second decisions, and to do that they
need to be able to, in essence, see the whole picture. Tesla
does not use LiDAR technology in their AVs and simply
use cameras and radar [2]. It functions very similarly to how
radar (Radio detection and ranging) does, however LiDAR
uses light waves rather than radio waves [6]. Light waves
and radio waves are actually quite similar however they
have two fundamental differences that make LiDAR and
radar very different technologies. Radio waves operate at a
different frequency and have a different wavelength than
light [7]. Both the radio waves and the light waves are on
the electromagnetic spectrum meaning that they always
travel at the same speed, making their only differences the
previously mentioned wavelength and frequency [7]. A
wavelength is the distance from the crest of a wave to the
next crest of that same wave, and the frequency of the wave
is defined as the inverse of the period. The period is the
amount of time it takes for the wave to go through one
wavelength [7]. This is important to understand because
these two properties are what differentiate LiDAR and
radar. The frequency and wavelength of light enable LiDAR
to create more detailed and specific maps [6].
In some cases cameras and radar technology have the
ability to sense just as well as LiDAR. However the
consequences of having the sensing method of an AV
working ‘in some cases’ have proven to be deadly.
Data overload in AVs
One of the largest concerns cited by the opposition of
using LiDAR in AVs is the amount of data collected by
LiDAR units [2]. LiDAR is inherently useful because of
exact it is, in much of its applications it needs to be very
focused on small details. For example some uses of LiDAR
require that it accurately detects the area of leaves a hundred
feet above it, and for all of the thousands of leaves in the
canopy [10]. In order to do this the LiDAR has to collect
tens of thousands of data points, of the distances. This is not
a problem when the LiDAR is being used to create one map
at a time, however an issue can arise when a unit is mapping
360 degrees around itself as it speeds down the highway at
60 miles per hour. The amount of data storage it would take
to collect all the unfiltered data of a car driving just 10
minutes away is mind boggling. According to Alex Davis
of Wired a square mile LiDAR map can use up several
gigabytes of data [12]. Although that's not a problem right
now, this could be a huge problem in the future seeing as all
AVs would be collecting and updating this huge amount of
data and a huge storage problem would occur. Currently
with the LiDAR being used this problem has been relatively
undocumented, seeing as there are so few actual cars in
existence [11]. But before any more cars get this new
technology the data storage problem has to get solved.
Thankfully it has become a bit of a race to find solutions.
The Google car case study is a prominent example of
how the LiDAR technology can be applied as a method of
sensing for an AV. Google ‘self driving’ cars have been
been in development for years, and LiDAR has become one
of the most vital sensing methods used by the Google Car
FIGURE 1[9]: the yellow on the diagram shows the
placement of LiDAR on the Google Car
Filtration of LiDAR data
Google specifically uses a Velodyne 64-beam laser, as its
LiDAR unit, shown in yellow on the figure above[9]. This
A Silicon Valley startup called Civil Maps has created
University of Pittsburgh, Swanson School of Engineering
Audrey Case
Colleen Molczan
what they believe to be the solution. In 2016 they raised a
6.6 million seed round fund (which for a start up is a very
good seed round) [12]. Civil Maps was able to create a
software that is able to distinguish between the necessary
data, such as street signs, stop lights, road lines, and ignore
unnecessary data like the leaves or the windows on a
building [12]. This technology is able to then use that data
to create a semantic map with each symbol being assigned
a meaning [12]. This enabled Civil Maps to turn a terabyte
of LiDAR mapping data into only the essential eight
megabytes that the car needs to function [12]. To put that
into perspective one terabyte of data is the storage of a nice
laptop, whereas 8 gigabytes is about the size of an mp3.
Beyond Civil Maps, other companies are searching for their
own methods of solving this data problem: Google, Uber,
and Here are all working on similar software. This in
essence means that soon enough this data storage problem
will be negated [12].
voltage able to pass through per ampere of current [14]. This
enables the GaN transistors to be more efficient and faster
than silicon transistors, and enables manufacturers to make
electronics smaller. These GaN transistors have come to the
market (and people’s attention) almost completely because
of these LiDAR problems [9]. Even though at this point
GaN transistor purchases for LiDAR manufacturing only
account for fifteen to twenty percent of EPC’s sales
[9].These transistors have the ability to make electric cars
cheaper and more powerful, data centers less energy
intensive, and laptop chargers significantly smaller [15].
LiDAR is not only an important part of AVs but it is also
encouraging engineers to look for solutions to problems that
previously they couldn’t because it wasn’t profitable, or
because they hadn’t even thought of that problem yet.
Fatal Accident Reduction
Journalist Mark Hoag in his article “Google vs. Tesla:
Two Different Philosophies on Self-Driving Cars,” states
that safety on the roads has become a serious priority for car
companies, and even tech companies [13]. According to the
USA Causes of Death report, road traffic accidents are the
number one cause of death for fifteen to nineteen year olds
in the United States [16], and over 90 percent of these
crashes are due to human error (this includes drunk driving)
as per the Stanford Law review [3]. If the human element
were removed from the equation, logically, the rate of fatal
car crashes would be reduced by over 90 percent as well.
Autonomous vehicles (AVs) equipped with LiDAR can
help save lives and reduce these statistics better than those
without LiDAR. The fatal Tesla Accident proved this; AV
experts claim that the accident would not have occurred if
LiDAR sensors were used with the camera and radar sensors
The Global Autonomous Vehicle Partnership believes
that the decreased death toll beyond its intrinsic value will
also benefit the economy [17]. Todd Litman, of the Victoria
Transport Policy Institute, claims that the benefits of AVs
with LiDAR on accident reduction are overestimated [18].
He also claims that the projected accident reduction would
not even occur until 2060 or later [18]. Even if Litman is
correct, having even a fraction of the fatal accident
reduction occur during our lifetime is amazing. Furthermore
the GAVP states that their projections are in the realm of
possibilities- and if it was possible to save that many human
lives people have a moral obligation to try.
High Cost of LiDAR Units
LiDAR has been extremely expensive, currently about
$80,000 for one sensor according to David Krambeck’s
research on AV pricing [11]. That is significantly more than
the cost of the radar and camera that is used by Tesla AVs
[13]. However currently there is a company called Efficient
Power Conversion (EPC), which sells Gallium Nitride
(GaN) transistors for use in LiDAR technology (among
other things) which would make the LiDAR technology not
only cheaper but also faster and more efficient [14]. A
Startup called Quanergy Systems that is utilizing the GaN
transistors is building a LiDAR system that could
hypothetically cost 1/80th of the current price [14].
Furthermore, Ford and Baidu have just made a joint
investment of $150 million s in Velodyne, which is the
company that leads the field in LiDAR for AVs [6]. The
investment was made in order to help Velodyne scale up,
thus decreasing the cost of individual LiDAR units [4]. In
all probability LiDAR will still be expensive, however
paying a couple of thousand dollars more for a car that will
be exponentially safer is a small price to pay.
Development of new technologies
Those Gallium Nitride transistors mentioned in the last
section are one of the best technological advances that came
as a ‘side effect’ of the development of LiDAR. GaN
transistors had been a known quantity for years, but were
never fully developed or feasible until startups like EPC
started working on them as a solution to both the processing
speed and cost issues with current LiDAR units [12].
Gallium nitride is an ionic compound, with one tenth of the
resistance of silicon, resistance meaning the amount of
Effects on the Environment and the Economy
As if the lives saved by AVs is not a reason enough for
autonomous vehicles to be adopted, they have countless
other benefits. Those benefits range from increased
efficiency, to reduced need for parking spaces and garages
in cities, to decreased greenhouse gas emissions [17]. AVs
University of Pittsburgh, Swanson School of Engineering
Audrey Case
Colleen Molczan
are both more economically and environmentally
sustainable and are one of the most important steps we will
be taking to a better future.
Commuters from Wilton, Connecticut can spend as
many as four hours a day on the commute from CT to offices
in New York City. Imagine how much work those same
commuters could get done if they were able to conduct
meetings, code, draft presentations, and check their emails
instead of simply sitting in the cars. autonomous vehicles
are enabling workers to do just that. According to the Global
Autonomous Vehicle Partnership website if ten percent of
the cars on the road were autonomous more than thirty seven
billion dollars could be saved (through less wasted time and
fuel) as well as a lower death toll. The results if ninety
percent of cars on the road were autonomous is even more
astounding, the savings would be around 475 billion dollars
[17]. Those savings come from less time spent commuting,
more productivity during the commute, as well as from the
increase in services of taxi like cars [17]. The taxi like
service predicted by the GAVP stems from the idea that cars
spend most of their time parked in a lot, if they could drive
themselves they could pick people up, drop kids off at
friends houses, go to the car wash, all on their own. Cars
would most likely be shared and many fewer people would
just have their own car.
Under the assumption that fewer vehicles will be utilized
as projected by the GAVP there would be fewer greenhouse
gas emissions [17]. According to the US Department of
Transportation, transportation accounts for 28% of the
United State’s emissions [18]. If AVs were adopted widely
in the way that GAVP suggests, there would be fewer
vehicles on the road thus reducing the emissions.
However others including Todd Litman believe that these
environmental impacts will be reduced by the increase of
motor demand and the increase of empty vehicles driving
around cities [15]. The counter to this is of course that AVs
would change the culture and fewer vehicles would actually
be owned, instead a greater number of them would be shared
and empty cars would simply pick up other passengers.
are going to revolutionize almost every part of our lives. In
some ways AVs are going to make our lives easier, in other
ways they are going to force humans to further evolve.
For example, a majority of people work as truck drivers
in several states, not to mention the countless taxi, bus, uber,
and lyft drivers. All of these jobs will in essence become
arbitrary when the autonomous vehicle revolution comes.
Our economy will have to evolve, we will be forced to
figure out how to further innovate and educate people so
they won’t be unemployed. People believe that politicians,
interest groups, and regular citizens will stop AVs from ever
coming to market, but there is a flaw in that logic. When we
switched from Horse and Buggy to motorized vehicles, jobs
were lost. When we went through the second agricultural
revolution, much of America lost their jobs. Every great
technological advance changes society, cultures and the
world, that is what makes them “great,” and every huge
change comes with consequences and benefits.
Autonomous vehicles will help save lives, not only be
preventing accidents, but also by helping ensure our planet
will be safe for future generations. That kind of benefit
outweighs any temporary issues caused by an upset in the
After every major innovation, the world was forever
changed and the economy changed with it- for the better.
There is always going to be a bit of a falter, a misstep or two
so to speak, and the argument that there will be significant
opposition to AVs and that they are going to cause huge
changes in the economy and workforce are valid. Just as
there was a push back against the Model T and the automatic
seed planter there will undoubtedly be a push back against
AVs, however it is just as sure that the push back will not
stop the rise of AVs.
That is not to say that the issues that are going to
be caused by AVs should be ignored, on the contrary, just
as policymakers work to determine liability in AV
accidents, to decide on ethics codes for AVs, to update
infrastructure to accommodate AVs, they must also work to
find jobs for people who will be displaced and unemployed
due to this innovation.
LiDAR is a prime example of a technology that
will not only change the future of technology, but that will
also force a huge change in our society. It will save lives,
drive innovations, help the environment, save billions of
dollars, and make hundreds of careers pointless. LiDAR
serves as a great reminder that innovation does not occur in
a vacuum and that engineers are responsible not only for
making cool technology, but also for understanding the
implications of it.
Inarguably the current system of transportation is
unsustainable. The number of transportation related deaths,
the amount of fossil fuels consumed, and the amount of
carbon dioxide emissions are all much too high.
Transportation methods and systems have to adapt and
change, and both the engineers and the policy makers of the
world agree on this. Autonomous vehicles equipped with
LiDAR, are going to be a huge step in the right direction for
sustainability but like all technological advances they come
with their downsides.
“Self-driving cars will be the most significant development
in motoring since Americans swapped horses for cars”,
according to Ford CEO Mark Fields. Autonomous Vehicles
[1] J. Bogage. “Tesla Driver Using Autopilot Killed in
Crash.” Washington Post. 6.30.2016. Accessed 2.12.2017
University of Pittsburgh, Swanson School of Engineering
Audrey Case
Colleen Molczan
[2] A. Singhvi. & K. Russell. “Inside the
Self-Driving Tesla Fatal Accident.” New York Times.
[3] W.B. Smith “Human Error as a Cause of Vehicle
Crashes.” Stanford Law School. 12.18.2013. Accessed
[4] “How LiDAR works.” LiDARUK. 2.2.2015. Accessed
[5]A. Iliaifar, . “LIDAR, lasers, and logic: Anatomy of an
autonomous vehicle.” Digital Trends. 9.10.2013. Accessed
[6]M. Vincent. “Ford and Baidu Invest 150 Million in
LIDAR technology for Autonomous Cars.” The Verge.
[7]A. Bridges. “Explainer: What are lidar, radar and sonar?”
Science News for Students. 5.1.2015. Accessed 2.10.2017.
[8] Velodyne LiDAR. (2016, 01 1). HDL-64E. Retrieved
10 31, 2016, from Velodyne:
[9] M. Shean. “Googles Self Driving Car Diagram.”
[10] A. Singhvi & K. Russell “Inside the Self-Driving Tesla
Fatal Accident.” New York Times. 1Accessed 10 31, 2016,
[11] D. Krambeck.“Tesla vs Google: Do LIDAR Sensors
Belong in Autonomous Vehicles?” All About Circuits
[12]A. Davies “Clever AI Turns a World of Lasers Into
Maps for Self-Driving Cars.” Wired. 7.15.2017.Accessed
[13] M. Hoag.
“Google vs. Tesla: Two different
philosophies on self-driving cars.” Innovatively. 3.5.2015.
Accessed 1.17.2017.
[14] K. Fehrenbacher. “How This Tech in Self-Driving
Cars Is Paving a Road Beyond Silicon.” Fortune Magazine.
7.9.2016 Accessed 1.31.2017.
[15] R. Matheson. “Making the New Silicon.” MIT News.
7.29.2015. Accessed 2.12.2017.
GENDER.” World Life Expectancy. 1.6.2016. Accessed
[17]The Opportunity.
Global Autonomous Vehicle
[18] T. Litman. “Autonomous Vehicle Implementation
Predictions: Implications of Transport Planning.” Victoria
Transport Policy Institute. 2015. pp. 12-19.
“The Challenges.” Global Autonomous Vehicle
We would like to dedicate this paper to our
families for pushing us to look for the solutions for real
world issues throughout our education process.
Furthermore, we would like to express our gratitude to
Professor Mahboobin, and Professor Mena Lora for
teaching us how to code which helped our writing logic
because coding is valuable language in and of itself. And to
my dogs, who are both named Zinduka, thank you for
deleting part of my essay by mistake, that part was bad
anyway. Also my cat for preventing me from typing, again
I’m not the best writer out there.
University of Pittsburgh, Swanson School of Engineering