To study if Google Self-Driving Car will be feasible in Today’s World

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Iteration 1: Orientation

The first iteration on orientation is where I will meet some experts that have the knowledge on the cars and the need for automation.  These experts will help to shed more light on the area of the accidents through carrying out a market analysis of the same to validate the findings that support the need for automation. That will prepare me for the next iteration on brainstorming and training.

Plan

I made a plan to meet the experts in the area of driverless cars as well as the knowledge on the need for automation in cars in the present world. I made application letters to my resource persons and got feedback from all of them within a period of one week, and that gave me to go ahead to proceed with the meeting with the resource persons. The meeting was scheduled on April 4, 2016, to April 8, 2016.  The meeting would be taking place in Chestertown in one of my friends’ hall so as to avoid incurring many expenses and it would be taking place for four hours each day between 2 p.m. to 5 p.m. when the resource persons are known to be somehow free.  I planned to make sure that I had a solid plan for the areas that would be in the discussion for the five days in which the orientation would be taking place.

I planned to supplement the findings from my resource persons with my personal search on the Internet for the purpose of having an in-depth understanding of the area in which I am conducting research. The approach that would normally be useful in this research would be the survey approach and the empirical study because they help to save much time of fieldwork (J. Andrew, personal communications, April 4, 2016). For instance, I planned to carry out an empirical study of the accidents that take place and how the self-driven cars would help to reduce them. That would take place from the survey of other literature after which we would then examine the essence of automation of the vehicles, the area in which my resource persons have profound knowledge.

Action

In my action section, I was the requirement to put my plan into action and make sure that I met all the resource persons in the stipulated time, and we held a discussion of what we were to discuss. I made a plan and objectives of the meeting ahead of the first meeting and then contacted my resource persons who then turned up without fail. The resource persons were five in number, and they all had much experience in the area of self-driven cars; furthermore, two of them were in the Google’s self-driven car project. I used the first meeting taking place on April 4, 2016, to explain the objectives of the meeting and allowing the resource persons to introduce themselves before the meeting would commence. The introduction consumed around an hour, but it set a good base from where to start.

The rest of the days incorporated a thorough research on the areas of our concern so as to enhance my understanding of the need and impact of the driverless cars particularly in the area of accidents reduction and automation. We made the analysis of the accidents caused by the motor vehicles for a long period; between 1900 and 2014 and we came up with the graph as shown in the figure below. The aim of doing that was to learn how automation in cars, not only the self-driven technology, has resulted in the reduction of accidents. That would also help to determine how the driverless car, which is a better technology, can reduce the road accidents if it would have an implementation shortly (J. Andrew, personal communications, April 5, 2016).

The life of people is of paramount importance, and motor vehicle accidents are claiming much percentage of human life. After analyzing the accidents caused by the motor vehicles for the period shown in the graph above, also analyze the accidents caused by the Google self-driven car to determine the percentage of the reduced accidents per annum. That would also be useful in making crucial conclusions for the driverless car project and its usefulness in this generation (P. Hardeman, personal communications, April 6, 2016). We also examined the causes of the accidents to find out the accident to finding out the opportunity for automation aimed at reducing them with the introduction of the driverless cars. We also examined how Google has endeavored to redesign its technology based on the accidents caused by its self-driven car prototype so as to ensure that the fault is not repeated (Sanchez, 2015). We also examined the presence of hardware and software in the design of the driverless cars.

Observation

The orientation in question as I observed helped me to make several observations regarding the self-driven car and the car technology in general. I observed that human life is crucial and that it should be protected by all means particularly in endeavoring to curtail the motor vehicle accidents. The survey that we carried out showed that the death toll resulting from the road accidents. The record shows that between the year 1899 and 2014, the motor vehicle fatalities have been 3,613,732 in United Sates alone although the number of deaths per annum has been increasing. For instance as per the results on the graph, the percentage reduction in accidents between the year 1979 and 2005 is 14.97 percent (Longthorne, Subramanian  & Chen, 2010). The average accidents per year in the year 2012 alone were 92 people per day in 30,800 accidents caused during the year.

I also observed that for quite a long time, the first accident caused by Google’s self-driven car was on February 14, 2016, when it ran into an oncoming bus while changing lines. However, Google said that the driver of the bus was to blame due to careless driving. I also observed that Google’s autonomous cars have been involved in accidents before, but those accidents are minor as compared to the ones caused by the other motor vehicles and furthermore the company is making changes to address that. That is because Google’s cars have the ability to recognize hand signals from the traffic officers, and they are capable of thinking of speeds that no human being can match (Pinto, 2012). The goal of Google is to come up with a car that drives better than the humans beings do, but they also say that perfection is not achievable.

The great promise that these driverless cars have is the improved safety. With that laudable advantage, there comes another benefit; a less-expected advantage that may help one to pay for the connected car: the car premiums are far low. The focus on safety as the first and foremost goal of Google means that there will be fewer injuries, fewer accidents, and fewer fatalities. As a researcher, I also observed that the autonomous driving cars are the most important advance that has been made so far in the automotive safety industry (Sykora, 2015).

Through the self-driven car, the visually impaired or the aging loved ones would not have to give up their independence. That time spent commuting can be diverted to doing what one wants to do (G. Ernest, personal communications, April 7, 2016. I observed that there were also over two million traffic accidents taking place across the globe every year. The introduction of Google’s driverless car can have those accidents reduced to do usually dramatically involve human error. Imagine if everyone can get around safely and easily, irrespective of one’s ability to drive. Many cars have some technology that works minus human intervention and it includes airbags, anti-lock brakes, self-parking, and collision control among others (Garrett & Tharp, 1969)

However, it is only a few cars that have full autonomy whereby the cars can make their decisions. Those cars are still under human control even though that assumption is becoming more difficult to maintain as the advanced technologies for driver assistance like electronic stability controls do help the drivers to retain the control of the vehicle when they should not (Martinesco & Etgens, 2015). The self-driven car technologies do come with warnings that there is no insult due to software or design faults. The establishment of liability can also be difficult in case evidence shows that the driver interfered with technology, or there is overridden driver assistance technology. But in general, I observed that automation of the cars can be helpful in reduction of accidents to a great deal.

Reflection

The orientation session was an enriching session from which I learned many things regarding the driverless car technology and the essence of automation in the motor vehicles. Through the orientation session, I had a good time to interact with the team of experts with whom we were carrying out research. The application of Participatory Action Research methodology helped me to gain maximally from the research as I actively participated in the same throughout the session. The five days of in-depth research and introduction into the self-driven car technology made me enthusiastic to gain more knowledge from the remaining iterations.  The resource persons had willingness while responding to my queries and they made sure that I understood a concept before proceeding to the next one of making further explanations. They helped me to realize that the collection of evidence is helpful in validating given claims in any topic involving research.

The search that I also conducted as a researcher on the Web ahead of the first meeting and during the session had a great contribution to the success of this iteration on orientation. From the same I got some ideas concerning Google’s self-driven car and the trend in the automation in motor vehicles including it essence in the current world. The search also helped me in coming up with the plan the objectives of the iteration. As I also contacted the resource persons early enough, I got a good time for planning for this iteration, thus experiencing the success. The iteration helped to address some of the misconceptions that I had concerning the self-driven car of Google. From the same I came to realize that my research topic is an interesting area for doing research and I would carry on that motivation to the other iterations to have them accomplished successfully.

There were, however, many things that I had to carry out during this session on orientation to self-driven car technology and the basic research on the traffic accidents.  The limited time could not allow me to carry out in-depth research on the topic even though the iteration was meant to give me a mere introduction and the background of the technology.  In the other iterations, I would make sure that I dedicate more time to the research work so as to make sure that comprehensive knowledge is gained from the same. I would also integrate the areas that were left out during iteration so as to make sure that I fully address all issues by the end of my research. The other thing that I think did not go well with this iteration is the area of incorporating many resources. I would make sure that as many resources as possible have incorporation in the subsequent research work so as to gain maximally from the same.

Iteration 2: Brainstorming and Training

The brainstorming and training iteration are the second iterations of my research on dealing with the misconceptions on Google’s self-driven car in today’s world. I will get training from experts on the driverless cars and the misconceptions that are involved in the driverless cars’ understanding among people and the general development lifecycle of software.  They will also handle the process of adopting technology and how to deal with resistance to the technology. I would carry out most of the research on the Web especially the section dealing with technology.

Plan

I planned to brainstorm with the other experts in this area of technology and software development with the aim of enhancing my insight on the research topic. I planned to carry out this research work between April 11, 2016, and April 14, 2016, and the time would be three hours each day running from 9 AM to 11 AM.  I planned to maintain the same venue for the last iteration since it was within the proximity, just 2 hours drive from where I stay. I planned to make good objective for this session that would make sure that I take into consideration all the areas on which I was to do research during this iteration. I planned to supplement the resource persons and the Web search with several other resources such as books, magazines, and journals among others.

There are five misconceptions concerning Google’s autonomous car on which one has to understand to enhance their insight (P. Ibrahim, personal communications, April 12, 2016). Those five misconceptions are highlighted below:

  • The autonomous car systems will evolve gradually from the driver assistance systems.
  • The first models comprising the fully autonomous cars are targeted at the consumers, and so they will be availed for purchase.
  • The project will take decades before most of the motor vehicles on the road are capable of self-driving.
  • The driverless cars are controlled using the classical computer algorithms, i.e., the if-then rules.
  • The public demonstration of these autonomous cars offers an indication of the capabilities they have
  • The driverless cars should make the right ethical judgments.

I planned to leverage this lists of misconceptions in enlarging my knowledge concerning the underlying forces as well as the paths that are likely to dictate the future of the self-driven cars. It would also help me in assessing the expertise of the experts and authors who are making publications about autonomous cars (K. Jensen, personal communications, April 11, 2016).

I also planned to incorporate in this training the tracking of the Google’s self-driven car project and the phases of the system development because this is also a system. I also planned to learn about the difficulties and the challenges that the company has experienced while developing the driverless cars and how they have managed to address them effectively.  I also planned to study from the resource person and the various resources, the challenge of adopting new technology and they should be handled. It would be a through training that would also incorporate other basics concerning the process of and the process of technological development including a feasibility study, planning, design, development, testing, implementation, and post-implementation. That can give me the crucial knowledge that would be useful to me as a technologist in the future.

Action

Before April 11, 2016, I made the required preparations concerning this iteration on brainstorming and training. I did some practice regarding the way to conduct a brainstorming session and how to arrange the training session to make sure that I do not leave any stone unturned concerning the issues I was required to address. At exactly 9 AM on April 11, 2016, I met the resource persons in the hall we had agreed to meet in, ready for the day’s activities.  I stood up and gave the experts the direction of the way things would go during this iteration so as to make sure that, throughout the session, we are on the same page. We began with the addressing of the misconceptions of Google’s self-driven car on the first day of the iteration. We addressed the following misconceptions as highlighted in the planning section:

  1. The autonomous car systems will evolve gradually from the driver assistance systems.
  2. The first models comprising the fully autonomous cars are targeted at the consumers, and so they will be availed for purchase.
  3. The project will take decades before most of the motor vehicles on the road are capable of self-driving.
  4. The driverless cars are controlled using the classical computer algorithms, i.e., the if-then rules.
  5. The public demonstration of these autonomous cars offers an indication of the capabilities they have
  6. The driverless cars should make the right ethical judgments.

Many widely repeated statements concerning the autonomous cars that can be attributed to the narrow perspectives that people have on these vehicles (Buehler, Iagnemma & Singh, 2009). We also brainstormed on the lack of understandings of the nature of the world, distributed process that drives the technology forward. From the first perception, I learned that the driver assistance systems cannot evolve gradually to entail continuous driving capability. I learned that these assistance systems need a huge and discontinuous jump in capability that will, in turn, place their capabilities close to the ones of the fully autonomous cars (N. Gomez, personal communications, April 12, 2016). I also learned from the second misconception that the first fully autonomous cars will not be available for sale to the consumers, but they will operate in few selected urban regions. We also examined the reason as to why the self-driven cars may not take decades to become a reality based on their benefits and the quick adoption of technology.

The resource persons also addressed the misconception about the envisioning the self-driven cars as being controlled by algorithms that have millions of elaborate rules specifying how these driverless cars should act for every situation. These cars do not contain those if-then rules, but they rather rely on pattern recognition and machine learning approaches that have been followed from the field of artificial intelligence (Wallach & Allen, 2010). Regarding the fifth misconception, the resource persons said that the public demonstration of the cars in question is used to capture not the public’s imagination, but also to mask the fundamental shortcomings from which they suffer. They also gave several supporting statements to show that the problem with making ethical judgments is largely irrelevant for the Google’s self-driven car.

I also got training and other information from various resources on the limitations of these self-driven cars as well as the technological adoption process. I also learned about the stages that Google’s self-driven car has undergone to the present, and the misconceptions, as well as the adoption, challenges that they had a deal with so as to reach where they are. I also got training on the basics of system development ranging from the project initiation through to maintenance and support. Those were the basic lifecycle for software system development and it gave my much insight because it was tailored to the Google’s driverless project. They also trained me on the way to properly manage such a huge and market-oriented project to ensure that it is successful. The essence of doing that was to help me understand fully how the autonomous car project can be effectively managed to achieve anticipated benefits.

Observation

As a researcher, I made several observations from this iteration on brainstorming and training. I observed that the driver assistance systems do not require any driver supervision. That supervision can only work for the systems that operate for few seconds or minutes like the parking assistant, but they cannot be relevant for those systems driving continuously (N. Gomez, personal communications, April 13, 2016). I observed that the reason for irrelevancy for non-gradual evolutions because humans lack the capability for sustaining the start for several hours that is in the requirement to immediately counter the possible deficiencies of the driver assistance system. The driver assistance systems that operate continuously on a given highway should have the capability of coping up with the rare situations like bicyclists and pedestrians on a highway, animal, sudden rainfall, and accidents unfolding among other issues (Thierer & Hagemann, 2014). I observed that for a driver assistance system to evolve to a driverless car, it should pass all the risk scenarios that a fully driverless car must be capable of handling.

I also observed that the self-driven car of Google has a major problem of only operating in designated regions and thus cannot operate in any area. For that reason, Google’s driverless cars cannot be availed to the consumers for purchase because these consumers will be expecting the cars to operate in any region. I observed that if the Google driverless car should operate in as many regions as possible, it should have a detailed map, algorithms that support all the weather conditions, not only dry weather but also the heavy rain and snow weather conditions. Google has only made its driverless car in such a manner that it can only operate in the sunny areas having light rains minus snow (Oge, 2015). That is one of the challenges Google has to address so as to make this project a success. It also needs to address the issue of the possibility of hacking of this autonomous car.

I also observed that people have the misconception that the driverless cars may take decades to become fully operational, but the fact of the matter is different. That misconception comes from the notions that automotive innovations took the manufacturers several decades before they had inclusion in most of the cars (Rogers, 2010). The researcher also observed that the limited additional benefits of the earlier automotive technologies are the ones responsible for the slow diffusion of those technologies. There are several benefits that can accrue from the self-driven cars including increased safety, quick return on investments, and reduction in driver expenses, lower insurance premiums, and several other benefits, others that may not be envisioned currently (Fagnant & Kockelman, 2014). The driverless cars are critical as they enable the technology that will affect almost every sector of the industry.

I also observed that the adoption of such a crucial technology is prone to many challenges that the developers have to deal with before they can have it fully adopted. Technology adoption is defined as the choice of acquiring and using innovation or invention. I observed that the contribution of a new technology can only have realization when that technology has wide diffusion and usage. The diffusion alone can emanate from a series of decisions regarding the use of the technology, the decisions that result from the comparison of the unprecedented benefits and uncertain costs of the adoption of the new technology (Martinsen, 2010).  I observed that an understanding of those factors impacting this choice is paramount both for the economists that study the growth of the technology as well as the creators and producers of these technologies.

Reflection

The iteration on brainstorming and training was very enriching to me as a research of the feasibility of Google’s self-driven car. First, I got to learn on how to structure and to manage a brainstorming session through the prior research I conducted on the Web. The resources including the resource persons that I also leveraged helped me to achieve the success that I achieved from this iteration. Especially the brainstorming on the misconceptions of Google’s self-driven car helped me to understand the trend in the technology and what we expect of the future. I came to get the knowledge in many areas in which I did not have the proper insight. The way is structured the iteration also helped me to chronologically and comprehensively address issues in detail. It also gave me insight towards the way of structuring the subsequent research activities and tasks.

The resource persons trained in the areas that were very useful to understanding my research questions. I got to learn that there are many areas of which I did not have knowledge before regarding the feasibility of adopting the new technology of autonomous cars. I felt that if I were in Google’s driverless car project, I would make a great contribution to the same as I learned on the way to handle issues. The knowledge I got from the iteration would help me not only on the topic of research but also in other areas including project development. Every organization is involved in the development of projects (Burke, 2013) and so that knowledge was a great input to my career as a technology expert. I also got the problem-solving skills on the way to address technical issues of any particular task.

In most of the areas, the iteration went on well as I had anticipated with only a few areas that I would suggest for improvements in the future. Much time was lost during the introduction on the first day, but in the future, I would make sure that the introduction takes place earlier in the material day when the research is to commence. That will help to save the time for other crucial tasks of the research. The area of system development process was also not adequately addressed, and I felt that many issues were left out as the resource persons concerned with it rushed through due to time limitations. I would make sure that I dedicate much time to the same during my personal research to make sure that I address all areas.

References

Buehler, M., Iagnemma, K., & Singh, S. (Eds.). (2009). The DARPA urban challenge: autonomous vehicles in city traffic (Vol. 56). springer.

Burke, R. (2013). Project management: planning and control techniques. New Jersey, USA.

Fagnant, D. J., & Kockelman, K. (2014). The future of fully automated vehicles: opportunities for vehicle-and ride-sharing, with cost and emissions savings (No. SWUTC/2014/600451-00081-1).

Garrett, J. W., & Tharp, K. J. (1969). Development of improved methods for reduction of traffic accidents (No. HS-007 882).

Longthorne, A., Subramanian, R. & Chen, C. (2010). An analysis of the significant decline in motor vehicle traffic fatalities. Retrieved from http://www-nrd.nhtsa.dot.gov/Pubs/811346.pdf

Martinesco, A., & Etgens, V. H. (2015, October). General outstanding considerations on legal issues applied to autonomous vehicles. In 22nd ITS World Congress.

Martinsen, T. (2010). Technology learning in a global–local perspective:-the interplay between technology diffusion, niche markets and experience curves.

Oge, M. (2015). Driving the Future: Combating Climate Change with Cleaner, Smarter Cars. Skyhorse Publishing, Inc..

Pinto, C. (2012). How autonomous vehicle policy in California and Nevada addresses technological and non-technological liabilities. Intersect: The Stanford Journal of Science, Technology and Society, 5.

Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.

Sanchez, D. (2015). Collective technologies: autonomous vehicles.

Thierer, A. D., & Hagemann, R. (2014). Removing Roadblocks to Intelligent Vehicles and Driverless Cars. Wake Forest Journal of Law & Policy (2015), Forthcoming.

Wallach, W., & Allen, C. (2010). Moral machines: Teaching robots right from wrong. Oxford University Press.



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