driverless car technology: patent landscape analysis

1 Driverless Cars: Patent Landscape Analysis


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Table of Contents

Executive Summary ....................................................................................................................................... 4

Introduction .................................................................................................................................................. 5

Taxonomy .................................................................................................................................................... 10

Filing Trends ................................................................................................................................................ 11

Top Assignees .............................................................................................................................................. 12

Patent Strength ........................................................................................................................................... 13

LexScoreTM ................................................................................................................................................... 15

Licensing Heat Map ..................................................................................................................................... 16

Geographical Coverage ............................................................................................................................... 17

Taxonomy Definitions ................................................................................................................................. 18

Products ...................................................................................................................................................... 22


Executive Summary

Driverless cars represent a disruptive technological change in transportation as we know it. These

vehicles are capable of sensing, navigating, and communicating with their external surroundings without

any human intervention. They leverage various technologies including imaging, radar, laser optics, and

GPS to navigate through dynamically changing road environments.

Driverless cars can dramatically reduce the number of road accidents and traffic congestion, leading to

increasingly deeper research into technologies that enable them. It is expected that the usage of

driverless cars will reduce fuel consumption by 20% through adaptive propulsion systems, cloud

intelligence and improved driving dynamics. All these factors in addition to the “science fiction” which

surrounds the technology have made driverless cars one of the most talked about emerging

technologies of this decade. Driving is so ubiquitous to large populations that such a positive

revolutionary change in driving is indeed very attractive to the general public.

Governments around the world are also showing active interest in driverless car technologies. States in

the US, such as California and Florida, have already passed laws which approve the usage of

autonomous cars. Car makers and technology providers around the world are conducting extensive

research and development to accelerate the commercialization of driverless cars. Significant

technological efforts are being put in making commutes more safe and efficient and it won’t be long

before driverless vehicles become an integral part of our transport systems.

In subsequent sections of this report, we analyze the Intellectual Property (specifically, patents)

landscape of driverless car technology. We discover that the majority of IP generation has occurred in

Anti-Collision systems and Dedicated Short Range Communication technology. The top three companies

with the highest number of patents and patent applications are Toyota, Robert Bosch and Nissan.

Geographically, Japan has seen the maximum number of patent filings as the leading company Toyota is

based out of Tokyo. Japan is closely followed by USA, China, and the European Union.

Using LexInnova’s proprietary patent analytics tool, LexScore™, we identify Robert Bosch as the leader in

this technology domain with a high quality patent portfolio, high patent filing activity, and a longer

average remaining life of the patents/patent applications. Toyota has a large number of patent filings,

but the company but was found to have relatively lower average quality patents, and lesser average life

remaining on its patents/patent applications.


Introduction

While R&D on driverless cars has picked up in recent times, initial research on this technology can be

traced back all the way to the 1920s. During the 1920s Houdina Radio Control demonstrated a radio

controlled car in front of the New York public1. The driverless car research reached its next milestone

with the exhibition of “Futurama” in 1939. Futurama depicted cars which could use embedded systems

in and under roadways to guide themselves2.

During the 1960s Universities started to take up research on driverless car technology with The Ohio

State University and Stanford University being the pioneers. However all the research methodologies at

the time were focused on modifying roadways to guide driverless cars3. The 1980s saw the change of

focus from modifying road systems to improving cars to be autonomous irrespective of road conditions.

Mercedes-Benz’s robotic van demonstrated autonomous runs in busy city streets during this period,

making driverless technology famous. This decade also saw Carnegie-Melon University concentrating on

autonomous car research which helped it in achieving the leadership status it enjoys now.

Fast forward to the 21st Century, the competition to benefit from the commercialization of driverless car

technology has boosted the research and several prototypes are in pilot phase on the road. Ever since

the 1980s, car makers have been continually developing technologies for driverless cars. A major

catalyst in development has been the DARPA Grand Challenge introduced by the Department of Defense

in USA. Technology giants like Google, Baidu, and Apple have now stepped in to providing technology

support required for driverless cars. Google has successfully implemented its technology on six Toyota

Prius cars and an Audi TT4 car. Automotive giants like Toyota, Robert Bosch, and Nissan have also

dedicated significant resources and investment into research and pilot testing of driverless car

technology.

Amidst these developments, in May 2013, the National Highway Traffic Safety Administration (NHTSA)

has classified driverless cars into five levels based on the level of autonomous capabilities:

Level 0 - No Automation: Driver controls all the functions of the car. No Automation.

Level 1 - Function Specific Automation: One of the Control Systems is automated. For Example,

Automatic Braking or Stability control.

Level 2 - Combined Function Automation: At least two of the Control Mechanisms are automated in

unison. For Example Adaptive Cruise Control with Lane Keeping.

1 “Phantom Auto' will tour city”. The Milwaukee Sentinel. Google News Archive. 8 December 1926. 2 The Original Futurama. (n.d.). Retrieved from http://www.wired.com/2007/11/ff-futurama-original/ 3 "This Automobile Doesn't Need Driver". Palm Beach Daily News. Google News Archive. 1966).

4 Exclusive: Google Expands Its Autonomous Fleet With Hybrid Lexus RX450h. (n.d.).Retrieved from

http://www.wired.com/2012/04/google-autonomous-lexus-rx450h/

http://news.google.com/newspapers?id=MKskAAAAIBAJ&sjid=PaEFAAAAIBAJ&pg=3093,3999582


Level 3 - Limited Self Driving Automation: All the systems are automated. The car can sense critical

situations in which it cedes the control to the driver.

Level 4: Full Self Driving Automation: All systems are fully automated requiring no human intervention.

Fig.1: Levels of Driving Automation [NHTSA]5

The current decade will prove transformational for driverless cars with the technology transitioning

from concepts and pilot cars to actual production models. Toyota’s aptly named Highway Teammate

along with Nissan’s Level 3 autonomous car are expected to be launched into commercial market by

20206. Several other companies have geared up their research to provide fully autonomous Level 4 cars

to public as soon as possible, with technology giants like Google expected to lead the way.

There are many Level 1 and Level 2 cars in the market already. Some estimates put this number at 0.3

million worldwide. This number is estimated to skyrocket over the next 5 years with a CAGR of 134%

reaching an all level combined number of 10 Million autonomous cars worldwide7 by 2020.

5 Ministry of Transport « transportblog.co.nz. (n.d.). Retrieved from http://transportblog.co.nz/tag/ministry-of-transport/ 6 Toyota’s ‘Highway Teammate’ is meant to help humans, not replace them. (2015). Retrieved from

http://www.digitaltrends.com/cars/toyota-highway-teammate-self-driving-car/ 7 Greenough, J. (2015). 10 million self-driving cars will be on the road by 2020. Retrieved from http://www.businessinsider.com/report-10-million-self-driving-cars-will-be-on-the-road-by-2020-2015-5-6?IR=T


Fig.2: Estimation of Driverless Car market share and its growth8

Driverless technology is expected to expand beyond personal cars to public sector transportation as

well. Local governments in many metropolitan cities are aiming towards automated transit systems to

de-congest their cities in an effective manner. The first buses of this kind will be introduced in

Switzerland in spring 20169. The Chinese bus company, Yutong is running similar trials and is expected to

open services to public in near future. We are in the stage of level 2 cars and looking forward to a level 3

car in another half a decade’s time. Many believe that in another 50 years, we will see 100% penetration

of autonomous cars.

The graph below predicts the amount of sales by level of penetration of driverless cars into the automotive industry. It is estimated that by 2070, every car being bought will have Driverless technology installed as a primary requirement10.

8 Greenough, J. (2015). 10 million self-driving cars will be on the road by 2020. Retrieved from

http://www.businessinsider.com/report-10-million-self-driving-cars-will-be-on-the-road-by-2020-2015-5-6?IR=T

9 The world’s first autonomous buses will debut in Switzerland in spring 2016. (2015). Retrieved from

http://www.digitaltrends.com/cars/first-autonomous-buses-debut-in-spring-2016/ 10 Autonomous vehicle implementation predictions. (2015). Retrieved from http://www.vtpi.org/avip.pdf

http://www.vtpi.org/avip.pdf


Fig.3: Estimation of Driverless Car Market Share in future.11

Driverless cars are expected to not only boost the sales of automakers, but also of mapping platform,

technology OEMs and automotive suppliers. Automakers like Tesla, BMW, etc. are buying devices from

automotive suppliers like Robert Bosch and from mapping firms like TomTom12 to enable higher levels of

automation and precision. Internet Search giants like Alphabet (Google) and Baidu are converting cars of

major automakers into autonomous cars using the technology they have developed on their own.

The world’s largest automotive supplier by sales, Robert Bosch, collaborated with the second-largest

high-definition mapping company by sales, TomTom to ensure continuous flow of high definition

mapping data13. TomTom’s maps are already being used in cars being tested by Bosch on highways in

the U.S and Germany. Bosch will use its engineering expertise to help make TomTom’s maps more

accurate and work seamlessly with data produced real time by the car using sensors. Universities have

stepped up as well to collaborate with various automakers and technology companies to accelerate the

progress in the field of driverless car research.

One of the leading research units in the field, Carnegie-Mellon University had announced a collaborative

research lab with General Motors back in 2008. Carnegie-Mellon has also collaborated with ride share

technology company, Uber to research on autonomous taxi Infrastructure which can run seamlessly in

major cities. Toyota has also identified the importance of universities and provided a combined funding

of $50 million to MIT and Stanford14.

11 Autonomous vehicle implementation predictions. (2015). Retrieved from http://www.vtpi.org/avip.pdf 12Who provides Google with its driverless car technologies? (n.d.). Retrieved from http://www.techworld.com/news/personal-

tech/driverless-car-tech-brings-bosch-big-bucks-3619431/ 13 How Bosch and TomTom are capitalizing on the driverless car movement. (2015). Retrieved from

http://fortune.com/2015/07/22/bosch-tomtom-driverless-car/ 14 Toyota Plans to Invest $50M in Driverless Car Research at Stanford, MIT. (n.d.). Retrieved from http://www.claimsjournal.com/news/national/2015/09/08/265605.htm

http://www.vtpi.org/avip.pdf


In a similar vein, the Engineering and Physical Sciences Research Council (EPSRC) and Jaguar Land Rover

have jointly funded up to 11 million euros into the project which will also include five other fronts of the

technology on which 10 UK universities will be working15.

At this key juncture of transformation from research to production, this report studies the intellectual

property of driverless car technology to identify innovators and potential leaders who will be positioned

to dominate in the near future.

15 University to contribute to Â£11 million driverless cars project. (n.d.). Retrieved from http://www.southampton.ac.uk/news/2015/10/driverless-cars-epsrc-funding.page


Taxonomy

Driverless Car technology is disruptive and definitely the game changer for the automotive Industry. The

transformation which can be achieved with this technology is incomparable to the progress made in the

last 100 years of automotive research. Though the current cost of commercialization and the equipment

makes it non-viable in its current form, the enormous potential of this technology has attracted all kinds

of companies, from Alphabet and Baidu to automotive leaders like Toyota, Volkswagen and Bosch to

heavily invest in the race to launch the first autonomous cars on a consumer scale.

In our study, we have classified patents/patent applications according to the broad technologies

involved in driverless car technology, such as Control Mechanisms, Communication Systems (such as

radar/lidar systems) and various kinds of ancillary equipment needed for these technologies to perform.

Our research finds technologies such as Adaptive Cruise Control and Anti-Collision Systems have the

highest number of patents/patent applications filings, followed by Braking Control Mechanism and

Communication Systems. Media and Sonar Systems have the least number of patent filings with only

396 and 597 patents/patent applications respectively.

Table.1: Taxonomy


Filing Trends

The number of patents/patent application filings in the driverless car technology has constantly

increased from 1995 to 2008. The economic recession of 2008-09 affected majority of the automobile

makers and decreased their cash flows. This meant the manufacturers couldn’t allocate as much funds

as they otherwise would have to research and development. This forced them to slow down research on

driverless cars. This explains to fall in number of patents/patent applications in 2009.

The filing trend for driverless car technology has mostly been on the upward trend. The number of

patent/patent applications being filed has witnessed a dramatic rise since 2009 as reflected by the slope

of the graph. From 311 filings in the year 1996, the number has risen to a whopping 1,861 in the year

2013. The dip after 2013 is because many of the applications filed haven’t been published yet. It is safe

to assume that the technology is still continuing on its positive growth trend and the number of patent

filings for the year 2015 might cross the 2,500 mark.

Fig. 4: Patent Filing Trend in the field of Driverless Cars over the years

0

500

1000

1500

2000

2500

3000

Nu

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of

Pat

en

ts

Filing Year


Top Assignees

The figure below shows the number of patents/patent applications related to driverless cars. Based on

our research, Toyota, Robert Bosch and Nissan have the most patent filings with 3110, 2665, and 1169

filings respectively. Volkswagen-Porsche (1140 patents/patent filings) has strong portfolio in signaling

and collision responsive systems while Daimler (961 patents/patent filings) have strong portfolio in

Collision Responsive Systems, Collision Detection and Pedestrian Safety Systems. Mitsubishi (231

patents/patent filings) has concentrated on Signaling and Vehicle Steering Systems, while Panasonic

(220 patents/patent filings) has patents on Vehicle Steering and Passenger Safety Systems.

The list of top 20 assignees is dominated by automobile manufacturers like Toyota, Nissan, etc.

Automobile suppliers like Robert Bosch, Valeo SA and Mando Corporation also have a significant

number of patents in the areas of Signaling and Steering Systems. Alphabet holds 238 patents/patent

applications, majority of which are in V2V and V2I communications.

Fig. 5: Top Assignees with the diameter of the circle representing their Intellectual Property


Patent Strength

The patents in our report are ranked automatically by our proprietary tool that relies on an algorithm

developed by Mark A. Lemley, Kimberly A. Moore, John R. Allison, and R. Derek Trunkey in their research

paper, "Valuable Patents." Historical research has proven that 97% of the litigation-worthy patents in a

portfolio are found in the top bracket of patents ranked by using this algorithm.

The table below shows a break-up of high strength patents/patent applications in driverless car

technology, under various technology areas. The highest number of high strength patents filings, with

484 active patents/patent applications fall under the ambit of Collision Responsive Systems, but this

number corresponds to only 7.3% of the total filings under this technology area. Vehicular Safety

Systems have the lowest number of high strength patents, with only 25 patents/patent applications.

Digital Computing Systems have a relatively high share of high strength filings, with 15.28% of high

strength patents/patent filings while only 1.25% of patents/patent applications which fall under the

technology head Adaptive Braking systems have high strength.

Table 2: Taxonomy representing high strength patents.


The table also shows a break-up of high strength patents/patent applications in driverless car

technology, under various technology heads. Collision Responsive systems have highest number of high

strength patents, with 484 patents/patent applications followed by digital computing with 464 patents/

patent applications filings.

The figure below shows a break-up of high strength patents in the respective portfolios of top assignees.

While Toyota has the largest number of patents pertaining to driverless technology, Robert Bosch has

the largest number of high strength patents.

Fig. 6: Number of high strength patents of each company


LexScoreTM

We use LexInnova’s proprietary LexScoreTM framework to identify driverless technology intellectual

property portfolio strengths and weaknesses. The figure below depicts the competitive positioning of

the top 20 assignees in this domain. The assignees are compared on the basis of quality score, average

lifetime and the number of patents in their portfolio.

We use our proprietary algorithm (based on bibliographic information and claim characteristics of an

invention) to calculate the quality of inventions. The diameter of the circles represents the relative

number of filings of patents/patent applications of each company. The circles that are present in the top

right region represent the assignees with portfolios which are exemplary in terms of both quality and

the average remaining lifetime. Ford is lying in the top right region, but its circle diameter is relatively

small as compared to that of General Motors which has more average life but slightly less patent

strength. Nissan is leading in terms of average strength of the portfolio, but lacks in average portfolio

lifespan. Hyundai’s portfolio has a high average lifespan, but the average patent strength is very less.

Toyota has the highest number of patents/patent filings followed by Robert Bosch.

Fig. 7: LexScore Analysis – Driverless Cars

Bosch, 2655

Toyota, 3110

Nissan, 1169

VolksWagen(Porsche), 1140

Continental Ag, 1041

Daimler Ag, 961Honda, 952

General Motors, 907

Fuji Heavy, 350

Ford, 521

Hitachi, 446

BMW, 442

Hyundai, 643

Zeppelin Gmbh, 265

Valeo Sa, 413

8

13

18

23

28

33

7 8 9 10 11 12 13 14

Ave

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Average life remaining of Portfolio


Licensing Heat Map

We use LexInnova’s Licensing Heat Map framework to identify sub-domains in the field of driverless car

technology where licensing activity is expected to be high. The size of the sections (representing

different technology domains) in the Heat Map indicates the number of patents/patent applications

filed in that domain. The size in other words represents the relative importance of each sub-domain,

while the color represents the likelihood of future licensing activity in that domain. We study the patent

holding patterns to color code the technology sub-domain for future licensing activity.

In this heat map, Red (and shades thereof) signifies a high chance of licensing activity in a certain sub-

domain, whereas Green (and shades thereof) represents a low chance of licensing activity in the sub-

domain. We follow 80-20 rule to decide the colors, where Yellow is assigned to the domains that lie on

the average median, i.e. 20% assignees having 80% of the patents/patent applications. The color drifts

towards shades of Red if 20% assignees possess less than 80% of the patents/patent applications, while

it drifts towards shades of green in the opposite case.

According to our analysis, Optical and Collision Detection systems are the sub domains which have the

highest possibility of licensing activity. Vehicle Speed Control systems, Collision Responsive and Adaptive

Braking systems are the sub domains which represent a relatively low chance of licensing.

Fig. 8: Heat Map representing most licensed areas of Driverless Car Technology


Geographical Coverage

The figure below represents the geographical filing trend of patents/patent applications related to

driverless car technology. Japan has seen the maximum number of patent filings in this technology

domain, closely followed by USA. China, Germany and South Korea have also seen a good number of

patent filings. Since the research of autonomous car technology is expensive and initially people with

high spending capacity are likely to be the target audience for it, only the developed nations and a few

developing nations have a good number of patent filings. Major car makers in the autonomous car

industry like Toyota being based out of Japan make it the leading country with 6492 Patents/Patent

Application. The US being the home country of tech companies like Alphabet and major car makers like

Ford and GM has 6047 Patents/Patent application under driverless car technology.

Germany also has a good number of intellectual property filed because of its massive auto industry and

being the home of major car makers like BMW and Volkswagen.

Fig. 9: Map representing jurisdiction with highest to lowest filing situations


Taxonomy Definitions

This table broadly discusses different segments into which the driverless car technology and intellectual

property has been classified. It also discusses various IPC classes which fall into each of those categories.

S.No Taxonomy Head Definition

1 Vehicle Propulsion Control

Patents which include mechanisms that help control Engine

Propulsion and Transmission Control of autonomous cars have

been included in this class. This head has B60W, F02D and B60K

as major IPC classes.

2 Vehicle Speed Control

Patents which discuss mechanisms that control speed of a

vehicle depending on the conditions of operation have been

included in this class. IPC Classes with high number of patents in

this head are B60K3100, B60W3016 and B60W1010.

3 Vehicle Steering Control

Patents that include about mechanisms which control steering of

the vehicle during transit. This Control Mechanisms Act upon the

stimulators in environment around the car. B62D IPC Class talks

extensively about this.

4 Vehicle Stability Control

Patents which discuss mechanisms to control Stability during

Vehicle cruise. Major IPC classes are B60W03002 and

B60G017015.

5 Others(ACC)

This category is created to include a multitude of diverse IPC

classifications that could not be properly categorized into any of

the preceding technology heads. The patents with such

classifications constitute the Miscellaneous Others technology

domain.

6 Collision Detection Systems

Patents which discuss about detecting impending collision of an

Autonomous car have been included in this subhead. Major IPC

classes are B60W3008 and B60Q00152.

7 Collision Responsive Systems

Patents which discuss mechanisms to control a vehicle in the

face of an impending collision have been included in this

subhead. Major IPC Classes are B60T007220 and B60R0210134.

8 Adaptive Braking This category is created to Segregate Patents and Patent Classes

which talk about mechanisms which asses the environment


conditions around the vehicle during cruise and apply braking

mechanisms accordingly. B60T IPC Class talk extensively about

this and hence has been included in this class.

9 Automatic Braking

This subcategory has been created to separate patents which

talk about automatic braking from the class of adaptive braking.

This Subhead includes patents and patent mechanisms which

talk about braking mechanisms which get activated at a certain

predefined stimulus in the environment around.

10 Cruise Assist

Patents of this subhead are particularly applicable to Level 1 and

Level 2 Autonomous cars. This Subhead includes classes which

talk about driver assist systems during vehicle cruise. For

Example, Braking Assist, Steering Assist etc.

11 Parking Assist

Patents of this subcategory particularly are applicable to Level 1

and Level 2 Autonomous cars. This Subhead includes classes

which talk about mechanisms which assist drivers during parking

maneuvers.

12 Warning/Alarm Systems

Patents which talk about warning and alarm systems, Audio and

Visual, which assist drivers. For example, Drowsiness Warning,

Hand-free warning.

13 Lane Keeping

Patents which discuss mechanisms which control vehicles in

cruise to switch lanes or to maneuver through lanes during

traffic have been included in this category. Major IPC classes

included in this are head are G05D001020 and B60W03012.

14 Digital Computing

Patents which talk about systems to process (Coagulate and

Calculate) information from various parameters and feed it to

the Cruise mechanisms have been included in this subhead.

Major IPC classes included in this subhead are G01C and G06F.

15 Image Processing Systems

This head is created to segregate patents which talk about

Environment/Image acquisition and the follow-up processing

systems from the above mention computing systems. Major IPC

classes are G06T and G06K00900.

16 Signaling Systems

Patents and patent classes which discuss about equipment used

in signaling the driver or the environment around, the

information and statistics of vehicle cruise have been included in

this subhead. IPC Class B60Q talks extensively about this and


hence have been included.

17 Optical Instruments

Patents which discuss optical instruments like Camera and Studio

Setup which gather visual information from surroundings and

send it to the cruise mechanisms to assist in vehicle cruise have

been included in this subcategory. Major Classes include

B60Q00144 and B60R01104.

18 Passenger Safety Equipment

All the patents which discuss infrastructure that can ensure the

safety of passengers travelling inside a driverless car have been

included in this subcategory. IPC class B60R02 and its family

extensively talk about this and hence have been included in this

subhead.

19 Pedestrian Safety Equipment

Patents which discuss devices which prevent Pedestrian Collision

and Vehicle maneuvers which follow up have been discussed

under this subcategory. B60T007040 is major IPC class that fall

into this subhead.

20 Vehicular Safety

Patents which discuss about Safety systems in an autonomous

car like Secure command systems, Anti-Malware and Anti-theft

systems have been in included in this class.

21 Propulsion Equipment

Patents which discuss infrastructure which enable propulsion

and transmission particular to autonomous cars have been

included in this subhead. B60K006200 and B60K006547 are the

major classes which discuss these domains.

22 Radar/Lidar

All the patents which concentrate on systems which use Radar or

Laser based Radar to send or receive information have been

classified into this subhead. G01S01* takes the highest

precedence in this class.

23 Sonar

All the patents which concentrate on systems which use Sonar as

the primary medium for information gathering have been

classified into this subhead. G08G001 is the primary IPC class in

this subcategory.

24 V2VCommunication Systems

Patents which talk about communication between vehicles using

Dedicated short range Communication Systems have been

classified into this subcategory. B60W030095 and B60R001120

are the major IPC classes.


25 V2I Communication Systems

All the patents which talk about communication between host

vehicle and other parts of the environment around the host

vehicle using Dedicated short range communication systems

have been classified into this subhead. B62D1010 and

G08G109000 are the major classes in this subcategory.

26 Navigation

Patents which discuss systems which transfer information

regarding navigation of the vehicle have been classified into this

subhead. For Example, GPS and Inertial Navigation Systems.

27 Media

Patents which consist of communication systems like radio and

video sets which are particular to autonomous cars have been

classified into this subhead.

28 Wired Patents which discuss Wired communication systems that can be

installed in autonomous cars have been place under this

subcategory.

Table 3: Taxonomy Head Definitions


Products

Toyota’s Lexus GS Highway Teammate

The car is a modified Lexus GS equipped with autonomous driving technology. The car has already been

tested on Tokyo’s Shuto Expressway in a series of trials covering functions like merging onto or exiting

the highway, and maintaining or changing lanes. The driver can switch into automated mode only after

passing through a toll gate and entering an on-ramp16. The car uses detailed maps and its own sensors

for orientation purpose to keep track of everything around it. Toyota has mentioned that the technology

is being tested and is expected to be production-ready by 2020.

Fig. 10: Toyota’s Lexus GS Highway Teammate17

Tesla Model S

Tesla Model S car is the king of the semi-autonomous car market today. The vehicle has proven to be

self-efficient. It does not ask the driver to take over frequently. It is equipped with automatic steering,

wheel and braking control. The vehicular Communications System in this car is also futuristic. 18All the

Tesla Model S cars function through a network. They can share and access information processed by

other cars.

16 Toyota’s ‘Highway Teammate’ is meant to help humans, not replace them. (2015). Retrieved from

http://www.digitaltrends.com/cars/toyota-highway-teammate-self-driving-car 17 Nguyễn, T. N., & Trần, L. V. (2007). Giải thuật lai cho bài toán sắp hàng đa trình tự sinh học = Using Ga-sa hybrid algorithm for

multiplesequence alignment problem. JSTD Tạp Chí Phát Triển Khoa Học Và Công Nghệ, 10(4). 18 Tesla “Owns” Semi-Autonomous Car Market. (2016). Retrieved from http://cleantechnica.com/2016/02/08/tesla-owns-semi-autonomous-car-market/


Fig. 11: Tesla Model S19

Google X Driverless Car

Google is currently test driving its Google X Driverless Car on U.S. roads20. The car is has registered 1

million test miles on the roads of California and Texas. Testing fleet includes both modified Lexus SUVs

and new prototype vehicles that are designed from the ground up to be support full autonomous

driving. Recently U.S. vehicle safety regulators have said the artificial intelligence system piloting a self-

driving Google car could be considered the driver under federal law. This statement by U.S. vehicle

safety regulators has amplified the chances of seeing the driverless cars on the road by 2018.21

Fig. 11: Google Driverless Car22

19 Tesla's "insane" Model S car could eradicate taxis. (2014). Retrieved from http://www.dezeen.com/2014/10/14/tesla-model-

sd-electric-car-driverless-autopilot/ 20 Google Self-Driving Car Project. (n.d.). Retrieved from https://www.google.com/selfdrivingcar

21 Exclusive: In boost to self-driving cars, U.S. tells Google computers can qualify as drivers. (2016). Retrieved from

http://www.reuters.com/article/us-alphabet-autos-selfdriving-exclusive-idUSKCN0VJ00H. 22 There's one big difference between Google and Tesla's self-driving car technology. (n.d.). Retrieved from http://www.techinsider.io/difference-between-google-and-tesla-driverless-cars-2015-12.