CCMN 432 - Google Autonomous Car Final Recommendation Report

Final Recommendation Report Autonomous Car CCMN 432 (4A0) Instructor: Dianna Nubla Group Members: Student Name Student Number Submission Date: August 10, 2015 Table of Contents Executive Summary ……………………………………………………………..……. 4 1.0 Introduction …………………………………………………………………...…....4 2.0 Technological Perspective………………………………………………………...5 3.0 Implementation Perspective 3.1 Designing …………………………………………………………………….... 3.2 Prototyping……………………………………………………………………… 3.3 Testing………………………………………………………………………….. 4.0 Environmental Perspective 4.1 Environmental Ecological Disturbances …………………………………. 4.2 The Effect of Carbon Footprint ….. 4.3 Environmental Life Cycle Assessment …………………………………. 4.4 Conclusion 5.0 Ethical Perspective 5.1 Liability of Accidents………………………………………………………….. 5.2 Trading of Lives……………………………………………………………….. 5.3 Terrorism and Trafficking…………………………………………………….. 5.4 Ethical Perspective Conclusion……………………………………………... 6.0 Business Perspective 6.1 Fuel Economy……………………………………………………………………. 6.2 Jobs………………………………………………………………………………. 6.3 Shipping Industry…………………………………………………………………. 7.0 Conclusion and Recommendation 8.0 References…………………………….…………………………………………... List of Diagrams Diagram 1: Perception’s Architecture List of Figures Figure 1: Autonomous car with all its components Figure 2: Distributed system architecture of autonomous cars Figure 3: Weight-fuel consumption relationship for future vehicles Figure 4: Job Displacement List of Tables Table 1: Self-driving car components Table 2 : testing accident monitored by the Google engineers Table 3: A comparison tale between a regular vehicle and an autonomous vehicle Table 4: Planning Layers Executive Summary Google inc. is a multinational technology company that operates more than one million servers around the world. Our goal is to serve the global audience and provide the best technologies to them including software and hardware (Google Inc, 2015).. Since 1950 the idea of a driverless car was present but no technologies or capabilities were available to research and adapt this idea (A history of autonomous cars, 2014). In 2009 Google Inc decided to adapt this project and develop it and study the feasibility of presenting it to the world as the greatest innovation of the auto industry. From studying the feasibility of the autonomous vehicle, results shows that this technology has huge positive impacts on the society and the Economy. The Autonomous cars will decrease the number of accidents, increase the fuel economy and it will also manage traffic and the roadway capacity (Autonomous Vehicle Technology, 2014). After analysing each perspective it turned out that this technology has the potential to have a negative impacts, however the positive impacts are greater which will allow us to recommend the self-driving cars as the new generation in the auto industry. throughout the report more detailed analysis will be presented and each perspective will have a conclusion that indicates the recommendation of the use of this vehicle from the point of view of that same perspective. lastly, the results of this report shows that the autonomous car is feasible to use. 1.0 Introduction Google is the largest multinational company which is focused primarily on the development and manufacturing of technology. Since the year 1998, the time that Google was founded, our main goal was to focus primarily on serving and providing convenience to millions of people around the world. whether we are creating a new browser or a new technology such as autonomous cars, we take meticulous care to deliver reliable and safe technology to our customers. In 2009, dependence of elderlies and physically impaired people, as well as the 1.2 million of deadly accidents worldwide annually are the facts that have encouraged google team to commit itself to devising and development of autonomous cars that could possibly reduce or eliminate those problems and shoulder the driving burden for elderlies, kids, or anybody with disabilities(Google Self-Driving Car Project, 2015). This ultimate recommendation report examines the possibility of implementing autonomous cars as a proper solution to reduce the number of accident fatalities and injuries. Based on our research findings and impact assessment from different aspects, we support our final recommendation. The research findings of the relevant aspects are listed as follows: 1. Implementation Perspective: discusses three categories: (1) Design, (2) Prototyping, and (3) Testing 2. Ethical Perspective: evaluates three topics: (1) The trading of lives to save other lives, (2) Who is liable when an accident occurs, and (3) Who is liable when an accident occurs 3. Technological Perspective: discusses three main categories (1) Technologies and Sensors, (2) Self-drive car testing, and (3) Features 4. Environmental Perspective: assesses three categories: (1) The Change in Ecological Disturbances, (2) Assess the Effect of Carbon Footprint on Human Health and Environment (3) Examine the Prospective Environmental Impacts Associated with the New Technology. 5. Business Perspective: focuses on the findings for three points: (1) Fuel Economy (2) Impact on Jobs, and (3) Shipping Industry The details of the ultimate studies and examination of their impacts of each aspect are explained in the subsequent parts. 2.0 Technological Perspective: First and Last Name The purpose of this report is to study the autonomous car, the newest innovation in the auto industry and the feasibility of using it. One of the major areas of the development of this car is the technological perspective thus, in this report three technical objectives will be discussed in depth: 1) technologies and sensors 2) testing and 3) available features in the car. 2.1 Technologies and Sensors The movement of this car depends on the essential components which are technologies and sensors. All these components work together in order to fulfill what a driver does. These components were built to complete each other. Although each one of them has a different function but they were all designed to cover up each other in case of a mechanical or technical damage. The figure below shows all components of the vehicle. Figure 1: Autonomous car with all its components (the new economy, 2013) Also, this able summarize all technologies and sensor used and gives a simple description of it including the main function. Technologies and Sensors Description Main Function 1. Light detection and ranging (LIDAR) A sensor that bounce light pulses off the surroundings Measure the lane making and the edges of roads 2. Video camera A camera to record videotape and images and transmitting it to a monitor screen Monitor detect traffic lights, road sign and pedestrian 3. Radar sensors Sends modulated waves to the central computer to be analysed Reliably detect the position of nearby vehicle 4. Central computer All the sensors above sends the signals, pulses and waves to the central computer which analyse and translate them Manipulate accelerator, brake pedal and steering wheel 5. Ultrasonic sensors Transfer ultrasonic sound waves to electrical signals Identify the position option the object very close such as parked vehicle and curbs 6. Global positioning system (GPS) This system send satellites signals to the central computer to be analysed provide accurate positioning for the vehicle Table 1: Self-driving car components (The economist, 2015) and (Banner engineering crop., 2015) 2.2 Testing the design A great progress has been done throughout the past six years and part of this progress is testing the design. The testing procedure is basically driving the car into public streets and monitor any accidents might occur to troubleshoot any challenges or bugs in the design. Currently a 1.8 million testing miles (Google self-driving monthly report, 2015) has been done and there are two mode of testing 1) Manual mode and 2) Autonomous mode. The manual mode is the mode where the safety testing drivers are driving the car, a 796,250 manual mode testing miles have been done since 2009. On the other hand, the autonomous mode means the software is driving the vehicle and no safety drivers interference (Google self-driving monthly report, 2015) and there were about 1,011,338 autonomous testing miles already done. The AVs were involved in 12 minor accidents for the past 6 years , accident for the past 4 years are summarized in the table below: Year Month Reason of Accident 2012 October Rear-ended by another vehicle 2013 March A vehicle traveling in the adjacent right hand lane veered into the side of the AV 2014 March Rear-ended by a vehicle that was hit by another vehicle 2015 April Av was stopped at red traffic, another car driver pass from behind on the right side. Slightly brushed the sensors May Vehicle approaching from behind collide with the rear bumper Table 2 : testing accident monitored by the Google engineers (Google self-driving monthly report, 2015) 2.3 Features A comparison has been done between a regular car and an autonomous car to present the differences in the features available in both. The features that play essential part in the vehicle are the ones that control the safety such as airbag and seatbelts. Also, the features that control the speed such as steering wheel , accelerator and brakes (Autonomous Vehicle Technology, 2014). Other features will also be presented in the comparison and a summary of it will be shown in table below : Feature Regular car Autonomous car Steering wheel Available N/A Accelerator pedal Available N/A Brake pedal Available N/A Seatbelts Available Available Inside airbag Available Available Outside airbag N/A Available Stop-start button Available(some new models ) Available Route screen display Available (some new models ) Available Table 3: A comparison tale between a regular vehicle and an autonomous vehicle (car and drivers, , 2013) 2.4 Conclusion A regular car is driven by a driver that controls all the parameters of the vehicle. Google has been working on giving the driver a break and allowing the car to drive itself using a bunch of technologies and sensors. After designing the car and testing it the results shows that the car can drive itself safely and reliably. All of the components shown in table 1 cooperate together to run the vehicle smoothly so it can give the chance to any disabled and nondisabled individual to have the freedom of moving around dependably. Testing the design under different scenarios and the positive outcome that was reported allows us to reliably present this vehicle and work toward publicly launching them in 2020 (Autonomous Vehicle Technology, 2014). 3.0 Implementation Perspective: First and Last Name Implementation impacts have roughly three main topics which are designing, prototyping, and testing. The remaining parts of this research project regarding the implementation impacts will focus on my in-depth inquiries as well as a conclusion which will be drawn over the feasibility of the self-driving cars project from the implementation perspective. 3.1 Designing One of the most important aspects in building a safe and reliable autonomous car is its design, which consists of five important subsystems which are perception, localization, planning, control, and system management (Belbachir, Boutteau, Merriaux, Blosseville, & Savatier, 2013). Those five design subsystems are briefly described as follow: 1. Perception is the process that scans and perceives the surrounding environment of an autonomous car by optical and high-precision information which it receives by means of various types of sensors such as LIDAR(University of Bucharest, 2013). . 2. Localization is the process that obtains the precise location of the car on its path at all times(Levinson et al., 2011).. 3. Planning determines the behavior and motion of the autonomous cars based on the information acquired from the perception and localization subsystems(Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, & Intel Research, 2008). 4. Control performs the necessary control functions to perform well under unexpected situations as well as following the commands from planning subsystem by steering, braking, and accelerating the autonomous car. 5. System Management: System Management inspects and manages the functionality of the overall autonomous system through fault management system(Carnegie Mellon University,2013).. Even though the design of the autonomous cars has a distributive nature, all its design subsystems are mutually crucial to the existence and functionality of each other.Thus a failure or glitch in one subsystem will cause other design subsystems to fail. Therefore, extensive research and time should be spent at the prototyping stage to enhance the reliability and functionality of the overall design. 3.2 Prototyping Prototyping expands on the design subsystems and their various subcomponents. 3.2.1 Perception: Perception subsystem consists of three main subcomponents as shown in the diagram1, and it processes the data that receives from various sensors embedded in the car to determine the factors which are crucial to the operation of localization, planning, and control system. Those factors may be obstacle’s positions, obstacle’s speed, pedestrian cross position, road coordinates and etc (University of Bucharest, 2013). During the perception process, the data provided by the sensors will be passed to the detection subcomponent. The detection subcomponent detects every single obstacle on the path of the car; then the information of the detected objects will be passed to the classification subcomponent for identifying the nature of the detected objects and associating the respective objects to a particular class, whether they are vehicles, pedestrians, buildings or other types of entities. While, tracking precisely detects any changes in the position, speed, and direction of the already detected objects on the road. 3.2.2 Localization: Localization subsystem uses high-precision mapping systems to generates two dimensional detailed maps of the environment and processes the acquired maps in conjunction with high frequency ultrasonic position estimator, and motion-rotation sensors such as LIDAR, to continuously calculate the position, orientation, and speed of the autonomous car. 3.2.3 Planning: Planning is a three-layer design subsystem that incorporates three types of mission, behavioral, and motion layers (Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, & Intel Research, 2008). Planning layers Tasks Mission Creates a graph that encodes the connectivity of roads, their complexities, their directional edges, and the time required to traverse those edges (Colito, 2007).. Behavioral Executes commands generated by the mission layer, responsible for lane-driving, intersection handling, precedence, safety-decision makings, responding to unpredicted circumstances on the roads (Colito, 2007). Motion Generates a set of trajectories that are likely to navigate the vehicle towards its desired goal; then evaluate those generated trajectories according to their proximity to static or dynamic obstacles in the surrounding, and their smoothness and various other factors. Finally, the best trajectory will be chosen and executed by the car (Jiwung Choi, 2014). Table.4. Planning Layers 3.2.4 Control: Through Control subsystems, curvature limits such as the minimum or maximum turning radius for an autonomous car, maximum acceleration and deceleration, and curvature limits which determines the maximum speed that a steering wheel can be rotated at will be dealt with (Carnegie Mellon University etal,2008) 3.2.5 System Management: System Management supervises the reliability of the autonomous car through fault management, which investigate the health of every single computing model as shown in the Fig.1 of the whole system one by one, and then will back up or fix any detected defect. Fig. 2.Distributed system architecture of autonomous cars Source:(Development of Autonomous Car—Part I: Distributed System Architecture and Development Process,2014) 3.3 Testing Verification of the autonomous systems occurs through algorithmic testing and regressive system testing. The development of Algorithms and their practicality are tested initially through software simulations. Once the algorithms become fully advanced and approved through those simulations, they would be executed on the autonomous car in the real world for the verification. Whereas, through regressive system testing the capability and reliability of every single components of the autonomous car against a series of standard circumstances, such as driving through lanes, navigating through a congested intersection etc., will be evaluated ( Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, & Intel Research, 2008).Even though meticulous testing and more extensive works are still required in determining how well the design and subcomponents of the autonomous cars can operate in different range of driving circumstances, the results gathered from algorithmic and regressive tests recommend the implementation of the autonomous cars. 3.4 Conclusion Even though the implementation aspects of autonomous cars may seem to be at its very early stage; many incremental electronic components have already been implemented into traditional cars for years. Indeed Cruise control, ABS (anti-lock braking systems), ECUs (electronic control units), automatically activated safety mechanism, and some other autonomous technologies have already replaced traditionally mechanical and electrical components of today’s conventional cars(Maynard, Beecroft, & Gonzalez, 2015). Moreover the implications from design, prototyping and testing stages endorse the investment in the autonomous cars. Therefore, I would recommend the execution of the implementation aspects on this technology. 4.0 Environmental Perspective: First and Last Name Over the years, environmental pollution such as increasing the level of carbon dioxide (CO2) in atmosphere become a major global warming environmental problem. In this part of the report, three principal objectives will be examined: (1) the environmental ecological disturbances, (2) the effect of carbon footprint, and (3) environmental life cycle assessment aspects. The overall assessment will determine the feasibility of the autonomous car from the environmental perspective. 4.1 Environmental Ecological Disturbances Environmental ecological disturbance can occur at several spatial scales. The ecological disturbance play an essential part in shaping the structure of population (T. Paine, R., n.d.). Therefore, ecological environmental pollution is the most significant disturbances that caused by human activities (Nappi, L., n.d.). Research by Bill Freedman (1995) illustrated that cars and trucks are one of the essential factors that responsible for the change of our ecosystem as it contribute to the emission of carbon dioxide. According to the Site-wide Navigation research (2014) the adoption of autonomous cars could improve land use as it automated to self parking. Moreover, the research showed that about 31% of business district parking space in most major cities are designated to parking (Site-wide navigation, 2014). In addition, the autonomous vehicle able to drop passenger off to the designated zone, drive themselves to remote,satellite parking lot, and then send the car owner a notification of its parking location (MacKenzie, A, 2013). 4.2 Effect of Carbon Footprint According to recent study of American ministry of transportation, the growth of carbon dioxide results from the increase in human activities which are burning of oil and gas. In most developed countries such as Canada, Australia and USA, a report published by Peters G.and Solli, C. (2010) revealed that approximately 72% of CO2 emissions are caused by road transport. As such the growth of carbon footprint result from the increase in the number of population caused by human activities. Therefore, cars are classified as as one of the leading contributors towards environmental pollution as it contributes to CO2 concentration in the atmosphere, and emission of other global warming harmful gases (What are the main sources of carbon dioxide emissions, n.d.). Thus , as a result of consuming less amount of oil and gas as well as use of land will cut down the amount of air pollution caused by fuel vehicles and fulfill the environmental ecological sustainability. (Pettinger, T., 2012) 4.3 Environmental Life Cycle Assessment The autonomous car, also known as Self-Driving Car would be highly in-demand in the United State as well as other developed countries due to its environmental and economic benefits in term of reducing global warming gas emissions such as carbon dioxide and the use of oil (Nealer, R., 2014). One of the autonomous car advantages is that managing traffic flow and increasing roadway capacity which lead to reduction of carbon dioxide emission. The disadvantage of the autonomous car is the cost effective that will led to a higher cost than the regular car. The production and recycling of the autonomous car is expensive; however, its more cleaner sources of power generation as produced lower carbon emission when it burns comparing to fuel vehicles (Car Emissions and Global Warming, n.d.). 4.4 Conclusion In conclusion, the use of Google Self Driving Car will lead to reduction of the global warming gases as well as increasing the environmental life cycle. However, my point of the environmental research aspects leads to lower the cost of the manufacturing and increasing the environmental life cycle. Additionally, the autonomous car has a social and economic benefits to our society. Also, to implement the new technology it advixced to provide astduy area about financia. Research for additional information on ecological disturbance and life cycle assessment aspects of the environmental impacts. Determine the environmental advantages after 2 years of manufacturing in order to determine the life cycle assessment 5.0 Ethical Perspective: First and Last Name People drive vehicles every day to get to their jobs and pick up their children from school. Driving is a necessity in society, but it is also the most dangerous form of transportation, causing 1.24 million deaths per year (Road Traffic Injuries, 2015). I will be making a recommendation on the viability of Autonomous cars in regard to its ethical impacts; I will be using the following three topics to make my recommendation; 1. Liability in Accidents, 2. Trading of Lives, and 3. Terrorism and Trafficking. 5.1 Liability in Accidents Liability is questionable when Autonomous cars are involved because of the lack of human interaction, it leaves manufactures involved in the accidents as well, but with proper legislations liability can be fairly charged to someone. Autonomous cars are legal in Nevada, and has began implementing laws to distinguish liabilities during accidents. It is the vehicles occupants responsibility to manually drive the Autonomous vehicle when an accident is foreseeable . Autonomous vehicles are expected to notify occupants whenever the vehicle experiences a technological failure, this puts responsibility on occupants to be ready to drive the vehicle manually. Accidents caused by malfunction of a vehicle can be held against manufacturers by victims. Vehicle that are hacked and being remotely controlled are expected to be immediately changed to manual mode. Implementing specific laws to govern the liability problems associated with Autonomous cars can make ambiguities in liability distinguishable as long as people are aware of the laws (Douma, Palodichuk, 2015). 5.2 Trading of Lives Autonomous cars can potentially find themselves in a situation where an accident is inevitable and there are no good outcomes regardless of how the car reacts. In these situations people could be hurt even if they aren’t directly involved with the accident based on the vehicle software, but innocent people are affected by vehicles even when they are not Autonomous. 75% of all car accidents are resulted from human error, which includes distracted driving and impaired driving (Forrest & Konca, 2007, 29-30). These accidents result in the death of many innocent lives, whereas Autonomous cars remove human error but occasionally causes the death of a possibly innocent to save other lives. When a person drives a car, an inherent risk is taken the moment they drive on the road. The possibility of getting into an accident is always there regardless of how it happens, the probability of it happening is the biggest concern rather than the end result itself in any probabilistic phenomena. Autonomous cars remove the biggest factor in car accidents, which is human error, and the loss of innocent lives occur even when there are no Autonomous cars (Hevelke & Nida-Rumilin, 2014). 5.3 Terrorism and Trafficking The autonomous cars bring about problems regarding drug trafficking, and terrorism, because they are prone to being hacked. Autonomous cars can be hacked and controlled remotely to cause accidents intentionally, but keeping a manual option for Autonomous cars allows hacking to be stopped as long as occupants are vigilant for signs of a hacked vehicle. Autonomous cars can also be used to carry explosives without a person in it, promoting bomb threats, but the purchase of explosives are monitored, allowing any suspicious purchases to be traced. Giving Police officers the power to remotely pull over cars helps stop the drug trafficking problem caused by autonomous cars as they will be easily identified when the vehicle is carrying no passengers. Though autonomous cars bring about some problems, solutions are available for all of them with the cooperation of the people within society (Douma, Palodichuk, 2015). 5.4 Ethical perspective conclusion The autonomous cars bring about some controversy ethically, but many of these issues presented have solutions. Though not all of the solutions are certain to solve every incident, the overall benefit provided by autonomous cars outweighs the disadvantages. The unfortunate loss of lives that may occur during accidents with autonomous cars due to outcomes being the product of an algorithm, is not much different from the unfortunate lives that were lost to drunk drivers in table 2, besides the fact that autonomous cars do it save more lives. Based on all the evidence, the autonomous cars provide far more benefit than disadvantages, proving them to be viable. 1905019050 Figure 2 Drunk driving deaths from 1982 to 2013 Source: Foundation For Adcanced Alcohol Responsibility 6.0 Business Perspective: Sanaz Dianat The objective of this report is to provide you with a recommendation on the possibility of implementing autonomous cars in Toronto. This part will discuss my studies and ultimate recommendations on the evaluation of three topics of 1) fuel economy, 2) jobs, and 3) shipping industry. 6.1 Fuel Economy Self-driving cars will prevent ineffective acceleration or slowing down; driving at an ideal velocity to attain the greatest conceivable fuel efficiency. In 2004, the total fuel cost in America was estimated to be 424 billion dollars. Post-implementation results reveal 4.2 billion dollars of annual saving due to a good utilization of fuel (Marchau & Van Der Heijden, 2003). According to statistics, installation of autonomous cars has contributed to an additional saving of 8.5 billion dollars in the USA due to less mass (Palay, 1984, 265-287). To analyze it more in depth, these cars are lighter than a current average vehicle, and they will save 2% fuel for each 100 pounds of reduction in weight. In general, installation of autonomous cars will save about 25% fuel annually, which is estimated to be around 104 billion dollars (Palay, 1984, 265-287). Figure 3: Weight-fuel consumption relationship for future vehicles Source: Annual Energy Review (2012). The above diagram also illustrates that there is a direct relationship between a car weight and its relative fuel consumption. More in depth, as the car weight increases, its fuel usage grows accordingly. In addition, it shows that the fuel consumption of an average light truck is more than an average car because it is heavier. Thus, implementation of intelligent cars expands economical aspect of fuel consumption. 7.2 Impact on Jobs Intelligent cars affect labour job adversely because many drivers will be displaced from their position. Conforming to an Occupational Employment Statistics survey of the Boston metropolitan area, with execution of autonomous cars, 2760 cab drivers will be unoccupied (Belbachir, Boutteau, Merriaux, Blosseville, & Savatier, 2013, 1362-1367). Taxi drivers are not the only people , who are in danger of losing their job; Municipal transportation workers, truckers, parking attendants, traffic police, auto mechanics, and insurance company employees are other examples of individuals being displaced from their occupation, as illustrated in the below diagram (Gonder, Earleywine, and Sparks, 2012, 450-461). Figure 4: Job Displacement Source: http://onlinelibrary.wiley.com (2014). As a consequent, autonomous cars will remove many individuals from their position. 7.3 Shipping Industry By the installation of autonomous cars, the profitability of shipping companies will increase as well. According to an Occupational Employment Statistics survey in 2004 of the Boston metropolitan area, shipping firms save a total amount of $531,681,600 annually as a result of implementing autonomous cars because they do not pay cargo drivers any longer (Lassila, Tikka, Haakana, & Partanen, 2012, 186). Based on another study by Occupational Employment, 10240 truck drivers will be unemployed as a result of self-driving cars; however cost-effectiveness of these companies will increase by $322,969,600 per year (Forrest & Konca, 2007). Hence, autonomous cars improve the profitability of shipping corporations. 7.4 Business Perspective Conclusions My investigation on autonomous cars shows that their benefits outweigh the disadvantages. To analyze it more deeply, although these cars impact job occupation negatively, they improve the economical condition of fuel consumption as well as profitability of shipping industry corporations. As a consequent, from the business point of view, intelligent cars project is cost- beneficial and is recommended. 7.0 Conclusion and Recommendation The viability of autonomous cars is ultimately decided based on the combination of all the researched perspectives. The autonomous car must be viable from a business perspective, otherwise businesses would have no incentive to produce and upgrade them. The following table summarizes the final opinion of each researched perspective. Perspective Recommendation Technological Perspective The Autonomous car has proven to be technologically successful as it has been tested over 1,011,338 miles (Google self-driving monthly report, 2015). Implementation Perspective Many of the components required in Autonomous cars are already found in many cars, with proper name testing Autonomous cars can be viably implemented into society, therefore Autonomous cars are viable (Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, & Intel Research, 2008). Environmental Perspective The environment is greatly benefit by the use of Autonomous cars because of its reduction in Greenhouse gas emission, making it a viable choice for the future of the environment (Car Emissions and Global Warming, n.d.). Ethical Perspective 10,076 people died because of drunk driving in 2013, Autonomous cars help stop impaired driving which will reduce a large number of lives lost in car accidents (foundation for advanced alcohol responsibility, 2013). The ethical benefits of Autonomous cars outweigh the disadvantages, making Autonomous cars viable ethically. Business Perspective Autonomous cars will save 25% fuel annually, and saves the shipping industry $531,681,600 annually (Lassila, Tikka, Haakana, & Partanen, 2012, 186; Palay, 1984, 265-287). Overall Autonomous cars are better for business but cause a large loss in jobs making it unviable in this perspective (Gonder, Earleywine, and Sparks, 2012, 450-461). All the perspectives find favour in using Autonomous cars except the business perspective. The loss of jobs is a problem, but many other benefits are gained from the usage of Autonomous cars. The reduction of car accidents, the saving of fuel, the reduction in greenhouse gas emissions, all together are more valuable, making Autonomous cars a viable project to implement into society. Although we recommend Autonomous cars, the following recommendations have been made to further improve the future of this project. Research options to ethically solve the problem of Autonomous cars being inevitable accidents. Create enough jobs to compensate for the jobs that were lost. Research better ways of stopping Autonomous cars remotely without possibly creating corruption within Police officers. 8.0 References A. Hevelke, J. Nida-Rumilin, (2014). Responsibility for crashes of autonomous vehicles: An EthicalAnalysis., 620-622 (Lin, 2013). http://link.springer.com.ezproxy.lib.ryerson.ca/article/10.1007%2Fs11948-014-9565-5# Douma F., Palodichuk A. S., (2012), Criminal Liability Issues Created by Autonomous Vehicles Foundation for Advanced Alcohol Responsibility. (2013). http://responsibility.org/get-the-facts/research/statistics/drunk-driving-fatalities/ Lash, S. (1996). Environment, Knowledge and Indeterminacy: Beyond Modernist Ecology?, Environmental Knowledge and Public Policy Need: On Humanizing the Research Agenda. In Risk, environment and modernity towards a new ecology (pp. 12-27, 269-279). London: Sage Publications. MacKenzie, A. (2013, December 21). Volvo's autonomous self-parking car. Retrieved August 11, 2015, from http://www.gizmag.com/volvo-announces-self-parking-car/28010/ Nappi, L. (n.d.). What is an Ecological Imbalance? - Definition & Explanation. Retrieved July 30, 2015, from http://study.com/academy/lesson/what-is-an-ecological-imbalance-definition-lesson-quiz.html Pettinger, T. (2012, November 3). List of CO2 Emissions per Capita. Retrieved July 30, 2015, from http://www.economicshelp.org/blog/6131/economics/list-of-co2-emissions-per-capita/ Road Traffic Injuries, (2015) http://www.who.int/mediacentre/factsheets/fs358/en/ T. Paine, R. (n.d.). Ecological disturbance | ecology. Retrieved August 11, 2015, from http://www.britannica.com/science/ecological-disturbance Site-wide navigation. (2014, January 6). Retrieved July 14, 2015, from http://www.rand.org/news/press/2014/01/06.html "How Does a Self-driving Car Work?" The Economist. The Economist Newspaper, 12 May 2015. Web. 05 Aug. 2015. http://www.economist.com/blogs/economist-explains/2013/04/economist-explains-how-self-driving-car-works-driverless "Google Self-Driving Car Project Monthly Report." Google Self-Driving Car Project Monthly Report (n.d.): n. pag. Google Self-Driving Car Project. Web. 27 July 2015. http://static.googleusercontent.com/media/www.google.com/en//selfdrivingcar/files/reports/report-0515.pdf "Google’s Driverless Cars." The New Economy, 17 Dec. 2013. Web. 8 Aug. 2015. http://www.theneweconomy.com/insight/google-driverless-cars What are the main sources of carbon dioxide emissions? (n.d.). Retrieved July 30, 2015, from http://whatsyourimpact.org/greenhouse-gases/carbon-dioxide-sources Belbachir, A., Boutteau, R., Merriaux, P., Blossevile, J., & Savatier, X. (2013). From . autonomous robotics toward autonomous cars. http://ieeexplore.ieee.org.ezproxy.lib.ryerson.ca/xpls/icp.jsp?arnumber=6629656 Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, Intel Research (2008). Autonomous driving in urban environments: Boss and the Urban Challenge. https://www.ri.cmu.edu/publication_view.html?pub_id=6189 Choi, J. (2014). Kinodynamic Motion Planning for Autonomous Vehicles. http://www.intechopen.com/books/international_journal_of_advanced_robotic_systems/kinodynamic-motion-planning-fo Colito, J. (2007). Autonomous Mission Planning and Execution for Unmanned Surface Vehicles in Compliance with the Marine Rules of the Road. https://www.aa.washington.edu/research/afsl/publications/colito_thesis_2007/thesis.pdf Carnegie Mellon University, General Motors Research and Development, Caterpillar, Inc., Continental AG, Intel Research (2008). Autonomous driving in urban environments: Boss and the Urban Challenge. https://www.ri.cmu.edu/publication_view.html?pub_id=6189 Fisher, M., Dennis, L., & Webster, M. (2013). Exploring autonomous systems and the agents that control them. http://cacm.acm.org.ezproxy.lib.ryerson.ca/magazines/2013/9/167136-verifying-autonomous-systems/fulltext Levinson, J., Askeland, J., Dolson, J., & Thrun, S. (2011). Traffic Light Mapping, Localization, and State Detection for Autonomous Vehicles. Retrieved July 30, 2015, from http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5979714&url=http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5979714 Jo, K., Kim, J., Kim, D., & Sunwoo, M. (2014). Development of Autonomous Car—Part I: Distributed System Architecture and Development Process. Retrieved August 11, 2015, from http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6809196&url=http://ieeexplore.ieee.org/iel7/41/4387790/06809196.pdf?arnumber=6809196 Belbachir, A., Boutteau, R., Merriaux, P., Blosseville, J., & Savatier, X. (2013). Intelligent vehicles: FROM AUTONMOUS ROBOTICS TOWARD AUTONMOUS CARS. Washington, DC: IEEE. From http://ieeexplore.ieee.org.ezproxy.lib.ryerson.ca/xpls/abs_all.jsp?arnumber=6629656&tag=1 Forrest, A., & Konca, M. (2007). Autonomous Cars and Society: SOCIO-ECONOMIC IMPACTS. Washington, DC: Worcester. From http://europa.eu.int/information_society/activities/policy_link/brochures_2006/documents /intelligent_car PDF Gonder, J., Earleywine, M., and Sparks, W. (2012). Analyzing vehicle fuel saving opportunities through intelligent driver feedback: SAE International Journal of Passenger Cars-Electronic and Electrical Systems, 5(2), 450-461. From http://papers.sae.org/2012-01-0494/ Lassila, J., Tikka, V., Haakana, J., & Partanen, J. (2012). Electric cars as part of electricity distribution - who pays, who benefits. IET Electrical Systems in Transportation, 2(4), 186. From http://journals1.scholarsportal.info.ezproxy.lib.ryerson.ca/details/20429738/v02i0004/186_ecapoedwpwb.xml Marchau, V. A. W. J., & Van Der Heijden, R. E. C. M. (2003). Innovative methodologies for exploring the future of automated vehicle guidance. Journal of forecasting, 22(2?3), 257-276. From http://onlinelibrary.wiley.com/doi/10.1002/for.853/abstract Maynard, T., Beecroft, N., & Gonzalez, S. (n.d.). Autonomous vehicles: Handing over control: Risks and opportunities in insurance. Retrieved August 11, 2015, from https://www.lloyds.com/news-and-insight/risk-insight/library/technology/autonomous-vehicles Palay, T. M. (1984). Comparative institutional economics: the governance of rail freight contracting. The Journal of Legal Studies. Chicago: The University of Chicago Press. From http://www.jstor.org/stable/724236 Sweeney, A. (2012). Annual Energy Review 2011: U.S. Energy Information Administration - EIA - Independent Statistics and Analysis. Washington, DC: U.S. Department of Energy. From http://www.eia.gov/totalenergy/data/annual/index.cfm Car Emissions and Global Warming. (n.d.). Retrieved July 13, 2015, from http://www.ucsusa.org/our-work/clean-vehicles/car-emissions-and-global-warming#.VaRLRflViko Drever, C., Peterson, G., Messier, C., Bergeron, Y., & Flannigan, M. (2006). Canadian Journal of Forest Research. Retrieved July 14, 2015, from http://www.nrcresearchpress.com/doi/abs/10.1139/x06-132#.VaRWAvlViko Lash, S. (1996). Environment, Knowledge and Indeterminacy: Beyond Modernist Ecology?, Environmental Knowledge and Public Policy Need: On Humanizing the Research Agenda. In Risk, environment and modernity towards a new ecology (pp. 12-27, 269-279). London: Sage Publications. Peters, G., & Solli, C. (2010). The Carbon Footprint of the Nordic Countries. In Global carbon footprints methods and import/export corrected results from the Nordic countries in global footprint studies (pp. 67-103). Copenhagen: Nordic Council of Ministers. Rodrigue, D. (n.d.). The Environmental Impacts of Transportation. Retrieved June 30, 2015 http://people.hofstra.edu/geotrans/eng/ch8en/conc8en/ch8c1en.html Nealer, R. (2014, September 18). The Equation. Retrieved July 10, 2015, from http://blog.ucsusa.org/how-clean-are-electric-cars-a-life-cycle-assessment-of-advanced-vehicle-technologies-656