Advanced Driver Assistance Systems Human ...

Advanced Driver Assistance Systems Human-Machine Interaction Technologies Patents and Future Market Opportunities |

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Advanced Driver Assistance Systems Human-Machine Interaction Technologies Patents and Future Market Opportunities Alejandro Nava Cavazos, Walter Arellano, Ana Paola Azcárraga, Estefanía Leal, Abelardo Leal

Abstract This article examines the Advanced Driver Assistance Systems (ADAS), and how their development is paving the way towards autonomous vehicles. In this context we analyze the patents in ADAS regarding pupil dilatation systems, heart rate systems, brainwaves measurement systems, and skin conductance systems. Based on this information we identify the technologies related to this patents and their innovation stage, as well as their maturity level. Finally, through a secondary research, we find that Advanced Driver Assistance Systems have a strong market opportunity, which is growing, ad that is expected to grow in the following five to eight years. Keywords: Advanced Driver Assistance Systems, Pupil Dilatation Systems, Heart Rate Systems, Brainwaves Measurement Systems, Skin Conductance Systems The idea of having autonomous vehicles is becoming more popular and widespread every day. This would mean that cars would need to be able to analyze and perceive their environment, as well as make decisions based on this information. In order to make autonomous vehicles a reality in the future, research regarding this topic has been increasing in the last years. Research has led to making significant improvements in new developments and new patents in this field of knowledge.

have been emerging. In order to know how ADAS technologies that capture drivers’ health and condition signals and patents in this topic, throughout this paper we will expose our research results about this topic and identify their market opportunity in the future. This paper’s objective is to identify what the Advanced Driver-Assistance Systems patents are in the field of vehicle and driver signals integration. In order to do so, a research is conducted to contextualize what ADAS is, and their contribution to the autonomous vehicles development.

Innovation in this field has not only been limited to autonomous vehicles, but has also extended to the development of Advanced Driver-Assistance Systems, known as ADAS, which incorporate technology use to support drivers and make their journey safer. ADAS technologies research has also grown in the last years, and new developments

How ADAS are paving the way for Autonomous Vehicles? In recent years, the idea of autonomous cars has become more popular and widespread among drivers and scientists. However, there is still a long pathway to get to them. In this context the development of Advanced DriverAssistance Systems (ADAS) is increasing its popularity and technology in this area is on the rise.

Alejandro Nava Cavazos, Walter Arellano, Ana Paola Azcárraga, Estefanía Leal and Abelardo Rodríguez are Monterrey Institute of Technology and Higher Education (ITESM) students currently enrolled in the Strategic Business Prospective Class. This paper was done between January and May 2016 in collaboration with Ph.D. Ricardo Ramírez, Ph.D. David Güemes, and Ph.D. José Maraboto.

An autonomous car is “a car which is able to perceive its environment, decide what route to take to its destination, and 1


drive it” (Yeomans, 2014, p.6). The development and use of this vehicles will require several changes in the driving patterns because now all of the car occupants will be passengers. Moreover, the vehicles will be able to move without having humans on them. The new autonomous cars would create a significant change in the transportations systems we have today, allowing people to invest less time on them, and more time in other activities (Yeomans, 2014), improving significantly our life quality.

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Driver-Assistance Systems arise, which are part of Intelligent Transportation Systems. ADAS are considered to be systems that “have a direct supporting interaction with the driver or the driver task” (Thalen, 2006, p.8). The main goal of ADAS is to improve the vehicle’s driver and passengers’ safety, by changing the way in which vehicles are operated in order to detect errors, and prevent accidents through many technologies such as warning systems. The developments in Advanced Driver-Assistance Systems and their proliferation have made a lot of technologies available so that they are incorporated into the current drivercontrolled cars. So by creating new assisted driver functions, the totally autonomous cars becomes everyday more feasible and closer to be available (McKinsey, 2015). Some of the assisted navigation functions with which we are now familiar are: anti-lock braking systems, satellite navigation, and automatically activated safety mechanisms (Yeomans, 2014). These systems seem to be very simple and very common in a lot of cars nowadays. However, new Advanced DriverAssistance Systems are being developed and promise to help improve the vehicle's’ autonomy, so it is expected that with the ADAS developments, autonomous vehicles will eventually be an everyday reality. In this context, Internet of Vehicles is emerging and gaining more popularity. This concept refers to technology for information communication, environmental protection, energy conservation, driver signals, and safety (Huawei, 2015).

Although in recent years the technology required for autonomous vehicles has been under deep research, there are still several obstacles that must be addressed before this cars become reality. Because of these issues, it is not expected to have autonomous vehicles in the short or middle-term future (Yeomans, 2014). Most of the implications that must be addressed are related to safety, liability and legal topics. According to the Santa Clara University School of Law (2012), some of the legal implications that prevent the autonomous cars use include: the civil liability in case of a collision, the automobile insurance premiums, and regulatory issues in case of an emergency. In addition to these, highways regulation and design must be also modified in order to ensure total safety and equality among autonomous and human controlled cars (Sharma, 2012). Despite all of these challenges, autonomous cars are being developed, and some of them have started to be used in some places such as in Silicon Valley (Autotech Council, 2016). Even though autonomous cars accessible for everyone still have a long way to go, in recent years significant progress from totally human-controlled cars to autonomous cars has been taking place, and it is expected to increase in the following years (Autotech Council, 2016). This includes the steps for the introduction of autonomous technology elements to current cars. In this context the Advanced

Methodology In order to identify how humanmachine interaction systems in ADAS are evolving, in this paper we conducted a research that took several steps.

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1. We defined what ADAS are, and identified pupil dilatation, brainwaves measurement, heart rate detection, and skin conductance tracking systems as the human-machine interaction systems on which we will be conducting research.

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Throughout the patents analysis that we did, we found out there are 10 patents that track pupil dilatation and gaze control applied to drivers’ assistance in the vehicle (See Table 1). The oldest patent of this technology was registered by Coutler Jeffrey in 2005, then another one in 2007, and then between 2011 and 2013 most of them were registered. Out of the 10 patents, 8 were registered in the United States of America, and 1 was granted by the World Intellectual Property Organization (WIPO). Our research also found out that several international corporations are currently developing patents in this field. Example of these companies are: Volvo Technology Co., Eurocopter, Hyundai Motor Co., and Ford Global Technologies.

2. A deep patents research was done using Goldfire database. Goldfire is an innovation and technological development database, which includes diverse tools to identify the total amount of patents for a specific technology. 3. Technologies related to ADAS maturity level were identified and analyzed, using information provided by Gartner database. 4. Research about ADAS market opportunities in the present and for the future was held.

TABLE 1. PUPIL DILATATION AND GAZE CONTROL PATENTS NUMBER OF Owners PATENTS 10 1. Coutler Jeffrey 2. Neuroptics, Inc. 3. Volvo Technology Co. 4. Koninklijke Philips N.V. 5. Eurocopter 6. Hyundai Motor Co. 7. Lytix 8. Ford Global Technologies 9. Harman International Industries

5. We draw conclusions regarding ADAS current development, their growth potential, and their market opportunity. Results Part I. ADAS Human-Machine Interaction Systems Patents Analysis The human-machine interaction systems are those that provide communication between humans and a machine (Johannsen, 2006).

Note: Done with patents information provided by Goldfire, 2016.

For this paper, we focused on the human-machine interaction systems that allow signals transmission between the car and the driver, particularly those that capture driver signals, such as pupil dilatation detection, brainwaves measurement, skin conductance, and heart rate measurement systems.

What predominates of all of these patents is actually a monitoring system that works different in each case and through a data processor generate signals or have a different reaction to irregularities that can be determined with the human gaze.

ADAS Pupil Dilatation and Gaze Control Detection Systems

ADAS Brainwaves Measurement Systems

The anatomy of the pupil revolves around the diameter, which is controlled by two sets of smooth muscles in the iris. Pupil dilatation can betray mental and emotional commotion within.

Brainwaves are produced by synchronized electrical pulses from masses of neurons communicating with each other. They are detected using sensors placed on the scalp. They are divided into bandwidths to describe their 3


functions, but are best thought of as a continuous spectrum of consciousness; from slow, loud and functional to fast, subtle, and complex.

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to identify patterns, and provide warning to the driver in case his state is not the appropriate one to drive. The newest patents is more specifically focused on finding out if the driver has fatigue or not, and show those warnings.

The patents analysis conducted found 10 patents that detect brainwaves using sensors, which are specifically used within vehicles (See Table 2). Out of the ten results, five of them were authorized between 2015 and 2016. These patents are related to detection systems to identify the driver’s mental state. These patents also include systems to track driver’s brainwaves patterns. A company that is developing patents in brainwaves measurement systems, as well as in the pupil dilatation and gaze control systems is Hyundai.

ADAS Skin Systems

Conductance

Detection

The Skin Conductance Sensor in ADAS, measures sweat gland activity on the hands, where it is commonly detected on the steering wheel or gear shift, It’s also measured with the help of a Galvanic Skin Response (GSR). Skin conductance is expressed in micro-siemens or micro-mho and increases when the arousal level increases. Our research found six patents about technologies for skin conductance detection (See Table 3). Five out of the six patents were granted by the United States, and one was granted by the United Kingdom. This information shows that most research regarding skin conductance systems in ADAS is being done in the USA. The companies that own the patents are: Koninklijke Philips Electronics; System Ltd. X.; NEC Laboratories America; Hall, Priddy, Myers & Vande Sande; Innerscope Research Inc.; and The Nielsen Company. The oldest patent that we found for these technologies was granted in year 2000 by the US Government to Hall, Priddy, Myers & Vande Sande. Then two other patents date to 2007, which are the ones of NEC Laboratories America, and Koninklijke Philips Electronics. Finally three more patents date of 2012, 2013, and 2016.

In addition to the newest patents, granted between 2015 and 2016, there were five patents developed between 2006 and 2012. The five patents were all granted by the Chinese Government and their requesters are Chinese companies. TABLE 2. BRAINWAVES MEASUREMENT SYSTEMS NUMBER OF Owners PATENTS 10 1. Hyundai Mobis Co. 2. National University of Singapore 3. Mohammed Aurooj Azam 4. Sia Technology Ltd. 5. 丰田自动车株式会社 6. 上海交通大学 7. 株式会社日立制作所 8. 丰田自动车株式会社 9. 三菱电机株式会社 10. 宋婉毓 Note: Done with patents information provided by Goldfire, 2016.

In the patents analysis we did, we found out that the predominating technologies regarding ADAS Brainwaves Measurement Systems being patented involve technologies that include using electrodes to measure drivers’ brainwaves 4


TABLE 3. BRAINWAVES MEASUREMENT SYSTEMS NUMBER OF Owners PATENTS 6 1. Koninklijke Phillips Electronics 2. System Ltd. X. 3. NEC Laboratories America 4. Hall, Priddy, Myers & Vande Sande 5. Innerscope Research Inc. 6. Nielsen Company

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some German companies interested in developing this technology (See Table 4). TABLE 4. HEART RATE MEASUREMENT SYSTEMS NUMBER OF Owners PATENTS 6 1. 代欣 2. 赫艾纳医疗公司 3. Sumitomo Riko Company Ltd. 4. 谢国华



All of these companies developed those patents with an objective of investigating the trends that Skin Conductance is coming up to. All of this investigation, for later on, developed commerce ideas, and sell them to automobile companies such as Honda, Toyota, and BMW. All of these investigation, to get a car the most selfsufficient it can get with the technology that scientists are developing.

The patents research found out that there are several technologies using hear rate measurement systems in ADAS patented. An example of it is an automotive seatbelt that detects heart rate. Another system also detects if the driver has drunk alcohol or not. Finally it is important to mention that Ford and Toyota have already developed and implemented these technologies in certain models of their vehicles.

ADAS Heart Rate Measurement Systems The ADAS engaged in the heartbeat detection is based on driver monitoring electrocardiogram (ECG). The purpose of the ADAS is to detect early heart conditions or any other problems to avoid traffic accidents to heart failures of the driver.

Part I. Findings Discussion Based on our research findings we can argue that patents of Human-Machine Interface Technologies for Advanced Driver Assistance Systems have been developing since 2005 (See Figure 1). Some of the first patents that began to be granted are the ones related to skin conductance and pupil dilatation and gaze control. Then from 2007 and 2010, there was no major research or patents in any of the technologies related.

We found six patents in Heart Rate Measurement Systems in ADAS. Their development has been occurring since 2003 and the most recent date from 2014. These are based on a variety of devices that fit monitor both general health, as specific to the measurement of ECG driver. Most of the technologies associated with the ADAS are emerging in a cycle, the most recent 2013 and 2014. While the other begun in 2013, are in a state of adolescent time, which have already implemented various vehicles. Those companies that have already developed these technologies, mostly are of Chinese origin, however there are also

Then, starting 2010, patents in all the researched systems; which are pupil dilatation and gaze control, brainwaves measurement, skin conductance, and heart rate; began to increase (See Figure 1). In particular, recent research and new patents in the last two to three years have been focused on heart rate and brainwaves measurement, and one of 5


them in skin conductance; all of these applied to Advanced Driver Assistance Systems.

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The following thirteen technologies are related to the ADAS Human-Machine Interface Systems that were previously mentioned. These technologies were analyzed using the Gartner database Hype Cycle curve.

Figure 1. ADAS Human-Machine Interaction Technologies Timeline

The Hype Cycle Curve is divided in five key phases, which are: technology trigger, peak of inflated expectations, through of disillusionment, slope of enlightenment, and plateau of productivity (Gartner, 2016) (See Figure 2). Technologies under the first phase, technology trigger, is when a breakthrough emerges, and there is no proven commercial viability for the technology. The next phase is the peak of inflated expectations, under which technology early publicity stories start to be published. Some of these stories become successful, and some others fail. After achieving the peak of inflated expectations, the technologies usually get into the trough of disillusionment. In this phase, interest in the new technologies decrease and some producers start to fail. After this phase, some technologies survive and get to the next one, which is slope of enlightenment. Under this phase, new pilots start to be developed by new companies. After passing through the four previous phases, technologies get to the plateau of productivity. Once in this last phase, mainstream adoption starts to take off (Gartner, 2016).


In addition to this, our research also found out that the main countries in which ADAS patents are currently being developed are: 1. United States of America 2. China 3. Japan 4. Germany Part II. Technologies related to ADAS Human-Machine Interaction Systems Maturity Level After analyzing the patents related to pupil dilatation and eye gaze, brainwaves, skin conductance, and heart rates in Advanced Driver Assistance Systems, we decided to analyze the technologies that are related to them. In order to do so, we decided to use the Gartner Hype Cycle Curve shown on Gartner Database (Gartner, 2016). The Hype Cycle Curve shows which technologies are commercially available, their maturity level, their adoption rate, and how they are relevant to solve current issues (Gartner, 2016). Through the use of the Hype Cycle Curve we will be able to see which technologies are related to the patents we identified and how long it will take for these technologies to be commercialized.

Through the use of the Hype Cycle Curve we will be able to see which technologies are related to the patents we identified and how long it will take for these technologies to be commercialized. 1. Gaze Control: involves determining the angle or position of a user's visual attention, usually through use of cameras or light reflected from the eye. Its current maturity level is adolescent, which means it will reach the Hype Cycle plateau of productivity in 5 to 10 years (Johnson, 2015).

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2. Automobile IP Nodes: are IP addresses assigned to individual vehicles or systems within the vehicle for the purpose of enabling a variety of connected-car and Internet of Things applications and services utilizing wireless data communication technologies. Its current maturity level is emerging, and it is expected it will reach the plateau of productivity in 5 to 10 years, because it currently has a market penetration of 1% to 5% of target audience (Hines, 2015).

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actual market penetration is of 5% to 20% of target audience and it will reach the plateau of productivity in 5 to 10 years (See Figure 2) (Koslowski, 2015). 8. Autonomous Vehicles: are those that can drive itself from a starting point to a predetermined destination in "autopilot" mode using various in-vehicle technologies and sensors. Its existing maturity level is embryonic and has a current market penetration of 1% to 5% of target audience (See Figure 2) (Koslowski, 2015).

3. Sensor fusion: refers to algorithms that aggregate and transform many disparate sensor inputs to provide useful outputs to a device or system. Its current maturity level is adolescent and it is expected that it will reach the plateau in 2 to 5 years (See Figure 2) (Reitz, 2016).

9. Internet of Things: is the network of dedicated physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment. Its maturity level is emerging, has an actual market penetration of 1% to 5% of target audience (See Figure 2) (Tully, Velosa, 2015).

4. Biometric Driver Identification: is an automotive access control and convenience technology that measures biometric identifiers. Its maturity level is emerging and it has a current market penetration of 1% to 5% of target audience (See Figure 2) (Hines, 2015).

10. Drive by wire: is an electronic control system that uses electromechanical actuators and electronic sensors instead of direct mechanical or hydraulic linkages for the primary driver control functions of steering, braking and acceleration. Its current maturity level is emerging, has a market penetration of 1% to 5% of target audience and the plateau will be reached in 2 to 5 years (See Figure 2) (Hines, 2015).

5. Lane Assist: includes lane departure warning, lane changing and lane keeping. Using one or several optical sensors for interpreting road lane markers; it then gives an audible, visual or haptic warning to drivers when they drift from their lane. Its maturity level is adolescent and it will reach the plateau of productivity in 5 to 10 years (See Figure 2) (Blanco, 2015). 6. Gesture Control: ability to recognize and interpret movements of the human body to interact with and control a computer system without direct physical contact. Its maturity level is early mainstream and has a current market penetration of 5% to 20% of target audience (See Figure 2) (Elizalde, 2015).

11. Gesture control: Gesture control is the ability to recognize and interpret movements of the human body to interact with and control a computer system without direct physical contact. Its current maturity level is emerging, has a market penetration of 1% to 5% of target audience and the plateau will be reached in 2 to 5 years (See Figure 2) (Elizalde, 2015).

7. Haptics in automotive: has the potential to add new forms of driver communication to a vehicle, and to improve the overall usability of vehicles and their information applications. Its

12. In Vehicle Ethernet: allows multiple in-vehicle systems. These include infotainment and Advanced Driver Assistance Systems. Its maturity level is adolescent, has a current market 7


penetration of 5% to 20% of target audience, and it is expected it will reach plateau of productivity within 5 to 10 years (See Figure 2) (Blanco, 2015).

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Describing our findings regarding the technologies related to ADAS Humanmachine Interface patents, we found out that most of these technologies are currently in an adolescent, emergent state, and it is expected that their full research and market potential will be fully reached within 5 to 10 years. In order to get into this results, we used the Priority Matrix tool provided by Gartner database (2016) (See Figure 3). Our research results show that the technologies in this development horizon are: automobile IP node, autonomous vehicles, internet of things, in-vehicle Ethernet, driver monitoring system, gaze control, lane assist, and haptics in automobile.

13. Driver Monitoring Systems: is an in-vehicle system that employs sensing technologies and analytics to determine the driver's state of alertness for the purpose of ensuring the continuous safe operation of the vehicle. Its current maturity level is emerging and has a market penetration of 1% to 5% of target audience. It is expected that plateau of productivity will be reached in 5 to 10 years (See Figure 2) (Blanco, 2015). Figure 2. ADAS Human Machine Interface Related Technologies Hype Cycle Curve

Our findings suggest that the technologies which are closer to get more widespread use, and therefore, the ones in which more research is being done are: gesture control, sensor fusion, biometric driver ID, and drive-by-wire. It is expected they will become more popular in the next two to five years. Currently, all the technologies that were researched have a current market penetration between 1% and 5%. This implies that their actual adoption is quite low. However, when these technologies get into the plateau of productivity, mainstream adoption begins, and this is when their full market potential will be reached. When their use is more widespread, our research shows it is expected that their use will be more constant, and at the same time, new market segments might be attracted, increasing their market penetration. Therefore we could argue that technologies related to ADAS will consolidate in the next 5 to 10 years (See Figure 3).

Note: Adapted from: Gartner Human-Machine Interface Hype Cycle, 2015, http://www.gartner.com/document/3102919?ref=TypeAh eadSearch&qid=7509781d2e892c3bb4aea7d5922c308a.

Part II. Findings Discussion Based on our research we found out that technologies used for Advanced Driver Assistance Systems is varied, and is related to different types of technologies. This findings show that different technologies, as well as companies from different disciplines of science, will be working in developing ADAS technologies. This development will be supported by the technological evolution, the ADAS also have an important relationship with the internet and the way in which this interacts with the vehicle, both technologies that make it as the vehicle itself. 8


Figure 3. ADAS Human-Machine Interface Related Technologies Priority Matrix

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91% (McKinsey, 2016). Satisfaction levels achieved by ADAS imply that in the future, autonomous and semiautonomous vehicles can also have high customer satisfaction. ADAS Future Market Opportunities Predictions about the future of Advanced Driver-Assistance Systems show there is a strong potential for their growth in the following three to five years. This is due to several reason which include market trends, as well as research trends. There are two main reasons why it is expected in the near future demand for ADAS features will increase. The first one is ADAS features prices to the final customers will fall. This will be caused by the increase in the technologies available with the car, or separated. A fall in prices will significantly increase market opportunities because the main reason cited by the people surveyed by McKinsey (2016) was that these items were too expensive. Another reason that might encourage ADAS adoption is an increasing awareness towards driving and vehicle safety. Therefore, drivers might be more willing to invest some money into their safety by purchasing ADAS features. According to Visiongain (2015), the average growth of the ADAS market between 2016 and 2020 will be of 5%10%, while form 2020-2025 a market growth of 10%-15% is expected (See Figure 4).

Note: Adapted from: Gartner Human-Machine Interface Hype Cycle, 2015, http://www.gartner.com/document/3102919?ref=TypeAh eadSearch&qid=7509781d2e892c3bb4aea7d5922c308a.

Part III. ADAS Current and Future Market Opportunities ADAS Current Market Opportunities According to McKinsey (2016), based on a survey applied in China, the United States, Japan, Germany, and South Korea, 70% of car buyers were aware of Advanced Driver-Assistance Systems features, but only about 30% had experienced them, from which only half of them bought them for their vehicles. In China and Germany the ADAS adoption rate is above 20%, located in 28% for the first country and 23% for the second one. This results imply there is still a low purchasing rate of ADAS technologies. The ADAS features that are requested the most by customers are: advanced emergency braking, pre-collision warning, and blind-spot monitoring (McKinsey, 2016).

Figure 4. ADAS Expected Market Growth

Even though ADAS adoption rate is still low, customer satisfaction among buyers is very high. This is highlighted in their willingness to repurchase these features, implying their performance was good. According to the survey, willingness to repurchase is over 85% in the five countries, having China the highest with

Note: Adapted from Visiongain Automotive Advanced Driver Assistance Systmes (ADAS) Market Report 20162026, 2016, https://www.visiongain.com/Report/1602/Automotive-

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Advanced-Driver-Assistance-Systems-(ADAS)-MarketReport-2016-2026.

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from 2016 to 2026. This will be due to three main reasons:

Another important reason that is driving ADAS technology market growth is collaboration between companies and key players (P&S Market Research, 2016). The strategic alliances include technology firms, but they are also taking place together with the automotive industry most important players. An example of this is the partnership between Mobileye, Safran and Valeo, who have been collaborating in the design of front facing camera solutions, as well as products based on sensor fusion with the microprocessors Mobileye has developed (P&S Market Research, 2016). Another example of this alliances is the collaboration between Ford and RWTH Aachen University in Germany, to identify the customer preferences regarding the ADAS systems adoption. It is expected that due to collaboration, more technology will be available to the end consumers in the following years, making it easier for them to find the one that fits them the most. At the same time, this will probably make Advanced Driver Assistance Systems cheaper, so their market will grow up to 22% from now on until 2022 (P&S Market Research, 2016).

1. More transportation awareness among consumers.

safety

2. ADAS features will become cheaper. 3. Collaboration between companies and key players in the industry will increase. With this information we can say that patents in Advanced Driver Assistance Systems will be very profitable in the following five to ten years. In addition to this, we also found out that the ADAS features more requested by the customers are: 1. Advanced Emergency Braking 2. Pre-collision Warning 3. Blind-spot Monitoring This information proves to be very useful because these features have a high demand, suggesting that they represent a market opportunity for new and existing companies in the ADAS and automotive industry. Future Research In this paper we found out the patents being developed regarding ADAS Pupil Dilatation Detection, Brainwaves Measurement, Heart Rate, and Skin Conductance Systems. A worthwhile direction for future research would be analyzing the patents by region and countries in which they are developed. Such research would provide a clear perspective regarding which countries are the ones in which more investigation is taking place.

It is important to mention that while the market and the demand is increasing, the return on investment will be decreasing. This will be due because competition will increase, and with the increase in the supply, prices will also fall. Part III. Findings Discussion Based on the information we found out through the secondary research on ADAS current and future market opportunities we can say that nowadays Advanced Driver Assistance Systems have a low market penetration, which is about 20% to 23% of the target market (McKinsey, 2016). However customers’ willingness to repurchase is high. Based on this information we could argue that market growth of about 22% is expected

Conclusions Throughout this paper we identified that patents in Advanced Driver Assistance Systems including HumanMachine Interaction Technologies have been increasing their number since 2005. 10


The Human-Machine Interaction that have more patents are:

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The growth of these and other ADAS features will be due to three main reasons:

A) Pupil dilatation and gaze control

1. More transportation awareness among consumers.

B) Brainwaves measurement Also, in the last two to three years have been focused on heart rate and brainwaves measurement, and one of them in skin conductance; therefore patents in these filed are expected to increase their number. We also found out that the main countries in which ADAS patents are currently being developed are:

safety

2. ADAS features will become cheaper. 3. Collaboration between companies and key players in the industry will increase. Considering all the previous information we conclude that Advanced Driver Assistance Systems and the Human-Machine Interaction technologies related to them are currently emerging, and have a strong market potential for the future.

1. United States of America 2. China 3. Japan 4. Germany

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Based on the ADAS related technologies research, we found that these technologies are currently in their emerging or adolescent level, which means their market penetration is between 1% and 5%. We also found out that most of them are expected to achieve their full market potential within the next five to ten years. These technologies are: automobile IP node, autonomous vehicles, internet of things, in-vehicle Ethernet, driver monitoring system, gaze control, lane assist, and haptics in automobile.

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