Cynthia Castellon Technology Review #2 PDF

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Running head: TECHNOLOGY REVIEW #2

Technology Review #2 Cynthia Castellon September 22, 2020

Running head: TECHNOLOGY REVIEW #2 Introduction Autonomous vehicles is one of the most significant inventions made in technological sect. It involves the creation of vehicles that can operate with no human intervention. Important to note, autonomous cars can sense their environment minimizing accidents and other criminal activities that are likely to take place. In this bibliography, various sources citing the development of autonomous vehicles are annotated. These sources have been obtained from reputable platforms like ACM Digital Library, Dissertations & Theses (Pro-Quest), IEEE Computer Society Digital Library, and Science Direct. The annotations outline how the cited sources will be used to satisfy fundamental stakeholder needs in the technological sect, which involves risk management, decreased vulnerabilities, and how attacker use technology to carry out their malicious activities. Annotated Bibliography

Baron, B., Spathis, P., Rivano, H., & de Amorim, M. D. (2016). Offloading massive data onto passenger vehicles: Topology simplification and traffic assignment. IEEE/ACM Transactions on Networking, 24(6), 3248-3261. Traffic load over time has been on a growing trend, and hence there has been a need to create an offloading system that should help in alleviating it. This method involves the application of different transmission methods which are cost-friendly for an extension of the operators’ transport capacity. The main challenge being addressed in this research is the ability to assign data that would ensure the flow of vehicles while bearing with the road network complexity (Baron et al., 2016). The research suggests that a large capacity transmission system could be created from the road network used to offload huge transfers of data from the internet.

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The security challenges that arise from this automation are a possibility of failure, which would create havoc in the system. However, the technology could be applied in ensuring the continuous flow of vehicles in the system regardless of the road network complexity. Important to note, the research reveals that the technology used to develop the machines can help to minimize risks. Revealing greater application of technology like its robotic nature, the vehicles are synchronized with appropriate software that play a vital role in combating cyber-security threats. Furthermore, the technology helps in minimizing accidents because the vehicles can detect the nature of the environment, they are in thus, taking the appropriate action.

Burgei, D. (2017). Autonomous edge cities: Revitalizing suburban commercial centers with autonomous vehicle technology and new (sub)urbanist principles (Order No. 10801028). Available from ProQuest Dissertations & Theses Global. (2026698535). Retrieved from http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/2026698535?accountid=14580 Due to the growing technology, autonomous vehicles have come a long way to replace driver-assisted vehicles. This has created autonomous edge cities where the distractions caused by vehicle traffic are minimized hence maximizing the parking spaces and increased safety within the transport infrastructure. Suburban commercial centers could experience less pedestrian traffic as a result of the maximum utilization of autonomous vehicles. This research illustrates the rapidly emerging technology of driverless cars and their significance in improving the convenience of accessibility within the suburban commercial centers (Burgei, 2017). There are possible risks associated with autonomous vehicles. If not well secured, they could be interfered with by hackers and hence could be remotely controlled and hence could create damages. Some of the key aspects identified in this research that satisfies executives include the

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fit in critical infrastructure conditions. as described, the technology used in Autonomous vehicles helps them to securely operate in environment that other vehicles cannot. The vehicles are technology modified to prevent cybersecurity threats invasion. And this has helped in boosting its functionality in the market as far as service delivery is concerned.

Gao, G., Xiao, M., Wu, J., Huang, L., & Hu, C. (2018). Truthful incentive mechanism for nondeterministic crowdsensing with vehicles. IEEE Transactions on Mobile Computing, 17(12), 2982-2997. This research presents the design of an incentive mechanism used in vehicles as a nondeterministic crowdsensing system. The paper seeks to solve the challenges involved when designing an incentive mechanism for a crowdsensing system. The main challenge faced is that the cover problem is non-trivial and hence the design would only be based on trials. The problem is solved through the research proposal of a reverse-auction-based incentive mechanism that determines participants’ payments with minimal social costs. With this solution, the research considers the quality of sensing data. The security implications would be that the system becomes safer for the users with minimal risks to the system. However, there might be other risks and vulnerabilities involved in the application of this technology. The payment methods may be at risk of cyber-attacks which may incur unnecessary loses.

Liu, Z. (2020). Strategic infrastructure planning for autonomous vehicles (Order No. 28092332). Available from ProQuest Dissertations & Theses Global. (2439464388). Retrieved from http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/2439464388?accountid=14580

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The adoption of autonomous vehicles technology comes with the environmental, societal and economic benefits. The research investigates the optimization and modelling of the network infrastructure with an aim of promoting the autonomous vehicle technology. The problems that hinder the realization of autonomous vehicle technology include a possible congestion pricing problem or challenges in traffic assignment. The challenges arise as a result of the mixing of the autonomous vehicles with human driven vehicles. The adoption of autonomous vehicle technology may cause an increase in network congestion if poorly coordinated. If successful, autonomous vehicle technology would increase reliability and thereby minimizing security risks and vulnerabilities to cyber threats since the technology would be well secured.

Menon, N. (2017). Autonomous vehicles: An empirical assessment of consumers' perceptions, intended adoption, and impacts on household vehicle ownership (Order No. 10604282). Available from ProQuest Dissertations & Theses Global. (1937500864). Retrieved from:http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/1937500864?accountid=14580

Technological developments have given rise to revolutionary possibilities in how transportation industry would evolve. Technological giants and vehicle manufacturing industry have gone a further mile of testing the autonomous technology providing real life conditions. In a bid to prepare for the future transportation means, governments have started plans in ways they could design transportation infrastructure to suite the designs. This research presents the readiness of the adoption of technology in the market. The paper notes that from the past experiences evolving technologies have not been welcomed before by the public. Autonomous vehicle technology would probably face the market penetration challenges. The resistance in

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adoption could be mainly due to the high costs associated to the technology. The consumers’ perception towards this type of technology raises security issues due to risks and vulnerabilities involved. The acceptance of the technology would depend on the improvements in the cybersecurity issues affecting it. The fear that the attackers would exploit this technology contributes to the poor reception of the technology.

Munoz, A. (2020). Exploring strategies for adapting traditional vehicle design frameworks to autonomous vehicle design (Order No. 27735050). Available from ProQuest Dissertations & Theses Global. (2339173560). Retrieved from http://ezproxy.umgc.edu/login? url=https://www-proquest-com.ezproxy.umgc.edu/docview/2339173560? accountid=14580 Autonomous vehicles will, without a doubt, contribute to safety on the road as well as curb the climate change in many ways. However, for them to be adopted globally, they must overcome various standards set out by the government, which are meant to protect the consumers and the environment. As a result, various stakeholders mostly hardware and software developers who are spearheading the design of these crewless vehicles, are researching and putting in place various strategies to meet the regulation (Munoz, 2020). However, the paper notes that the adoption of some of the traditional design will significantly help them not only to save on time but also be compliant with existing laws. Important to note, this can used to meet the stakeholder requirements needs in the sense that the technology discussed implies the application of critical infrastructure aspects. Furthermore, it also to minimize and manage risks while in operation by being environmentally friendly. Autonomous vehicles will also help to combat aspects like terrorism and accidents because of their ability to detect the surrounding environment. most

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importantly, the technology used in these cars reduces their exposure to cybersecurity vulnerabilities and threats.

Ouyang, Z., Niu, J., Liu, Y., & Guizani, M. (2019). Deep CNN-based real-time traffic light detector for self-driving vehicles. IEEE transactions on Mobile Computing, 19(2), 300313.

The success of autonomous vehicles will significantly depend on the ability to detect traffic lights and obstacles such as people, cars, among other objects. For this reason, design engineers must use powerful cameras and other high computing devices that will lead to high vision. Unfortunately, the current heuristic algorithm offers low flexibility and vision capabilities. Also, the deep learning-based methods consuming high power, which will make them inefficient (Ouyang et al., 2019). Consequently, this paper proposes a model that uses a heuristic candidate selection region that will capture all traffic lights and classify those images using a convolution Neural Network and perform other simulation offline, thus increasing accuracy while reducing time. In relation to the needs of the executives and other stakeholders, this research indicates that the technology applied to autonomous vehicles help to minimize risks. This is because the vehicles can sense what is in the surrounding. Notably, the robotic nature of the vehicles plays a vital role in increasing resistance to threats and attacks. The technological components used in developing them have strong protective mechanism

Running head: TECHNOLOGY REVIEW #2 Park, J. (2016). A homotopy-based hierarchical framework for semi-Autonomous/Autonomous vehicle navigation (Order No. 10139101). Available from ProQuest Dissertations & Theses

Global.

(1803939406).

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from

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url=https://www-proquest-com.ezproxy.umgc.edu/docview/1803939406? accountid=14580 The popularity of Autonomous and semi-autonomous vehicles continues to increase by the day. This because the mentioned cars are hailed to be more effective than human-driven vehicles because they will be embedded with the technology that leads to the minimization of human error that is the number one cause of many accidents in our highways. Besides, these cars, by use of google maps among other navigation systems, will contribute to effortless and efficient navigation that will not only save on time but also lead to effective use of fuel. Incidentally, this paper suggests a hierarchical homotopy framework with several computational benefits and will result in a navigation decision that is compatible with humans (Park, 2016). The application of this framework will remove discontinuities that arise from the presence of obstacles that exist in feasible trajectory decisions, thus reducing complexity that exists in the present navigation algorithms. Also, the framework will reduce traffic jams as the model will give suggest the best routes for easy navigation leading to a smooth flow of cars. The best routes will save travel time and fuel, thus improving the efficiency of road transport. Also, feasible trajectories will minimize the possibility of car collisions that often emerge from poor selection trajectory movement decisions of vehicles.

Running head: TECHNOLOGY REVIEW #2

Xu, L., Liu, Y., Cheng, W., Guo, K., Zhou, G., Dai, Q., & Fang, L. (2017). Flycap: Markerless motion capture using multiple autonomous flying cameras. IEEE transactions on visualization and computer graphics, 24(8), 2284-2297.

For ages, cameras have played a significant role in capturing images that have shaped our country in many ways. Also, advancement in technology has led to the invention of drones and other crewless vehicles used by the military for surveillance, which has led to increased security and technology development in different fields. However, since drones and other crewless vehicles move while taking images, the blur, among other effects, continues to be a challenge (Xu et al., 2017). Thus, to avoid such outcomes, the paper proposes a technique that will lead to automatic, convenient, non-intrusive capturing of surface objects. This technology will be integral in many sectors such as agriculture, where it can be deployed to take clear images of plants, which will be analyzed by experts to determine whether the crops are healthy or not so that appropriate action can be taken to minimize loss of pest and diseases. Also, the technology is a keystone is improving surveillance, thus minimizing terrorist attacks and theft. Furthermore, with the possibility of drones being used for delivering lightweight items, this technology will enhance their vision and ensure they make deliveries effectively.

Running head: TECHNOLOGY REVIEW #2 Yoon, S., & Qiao, C. (2010). Cooperative search and survey using autonomous underwater vehicles (AUVs). IEEE Transactions on Parallel and Distributed Systems, 22(3), 364379. In recent decades, Underwater Autonomous Vehicles have been deeply explored. Importantly, some of these vehicles have been used both in research and for commercial purposes. In research, they have deployed in lakes, seas, and oceans to measure various compounds in water. Also, these particular vehicles have played a vital role in the oil and gas industry, where they have been used to give a detailed map of the ocean floor before construction of subsea infrastructure, enabling the installation of equipment in a manner that does not disrupt the environment (Yoon & Qiao, 2010). However, this AUV provided the condition they operate in experience challenges that may make them fail to disseminate signals or completely malfunction. Therefore, to prevent such eventualities and make the AUV more effective, the paper reveals that the application of X Synchronization (XS) will enable them to coordinate data aggregation, detect the possibility of their failure and finally control signal dissemination. Thus, making them more effective by minimizing the likelihood of the technology to fail and by simplifying data sharing. The proper functioning of this equipment is efficient is safeguarding aquatic life because it will ensure that oil wells are well constructed to avoid accidents, thus minimize the risk of spillage, which will eventuality ensure sea animals thrive well. In return, fishing will thrive, thus ensuring millions of households that depend on this activity have a source of livelihood. Moreover, as a nation, we will be food sufficient.

Running head: TECHNOLOGY REVIEW #2 References Baron, B., Spathis, P., Rivano, H., & de Amorim, M. D. (2016). Offloading massive data onto passenger vehicles: Topology simplification and traffic assignment. IEEE/ACM Transactions on Networking, 24(6), 3248-3261. Burgei, D. (2017). Autonomous edge cities: Revitalizing suburban commercial centers with autonomous vehicle technology and new (sub)urbanist principles (Order No. 10801028). Available from ProQuest Dissertations & Theses Global. (2026698535). Retrieved from http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/2026698535?accountid=14580 Gao, G., Xiao, M., Wu, J., Huang, L., & Hu, C. (2018). Truthful incentive mechanism for nondeterministic crowdsensing with vehicles. IEEE Transactions on Mobile Computing, 17(12), 2982-2997. Liu, Z. (2020). Strategic infrastructure planning for autonomous vehicles (Order No. 28092332). Available from ProQuest Dissertations & Theses Global. (2439464388). Retrieved from http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/2439464388?accountid=14580 Menon, N. (2017). Autonomous vehicles: An empirical assessment of consumers' perceptions, intended adoption, and impacts on household vehicle ownership (Order No. 10604282). Available from ProQuest Dissertations & Theses Global. (1937500864). Retrieved from http://ezproxy.umgc.edu/login?url=https://www-proquestcom.ezproxy.umgc.edu/docview/1937500864?accountid=14580

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Munoz, A. (2020). Exploring strategies for adapting traditional vehicle design frameworks to autonomous vehicle design (Order No. 27735050). Available from ProQuest Dissertations & Theses Global. (2339173560). Retrieved from http://ezproxy.umgc.edu/login? url=https://www-proquest-com.ezproxy.umgc.edu/docview/2339173560? accountid=14580 Ouyang, Z., Niu, J., Liu, Y., & Guizani, M. (2019). Deep CNN-based real-time traffic light detector for self-driving vehicles. IEEE transactions on Mobile Computing, 19(2), 300313. Park, J. (2016). A homotopy-based hierarchical framework for semi-Autonomous/Autonomous vehicle navigation (Order No. 10139101). Available from ProQuest Dissertations & Theses

Global.

(1803939406).

Retrieved

from

http://ezproxy.umgc.edu/login?

url=https://www-proquest-com.ezproxy.umgc.edu/docview/1803939406? accountid=14580 Xu, L., Liu, Y., Cheng, W., Guo, K., Zhou, G., Dai, Q., & Fang, L. (2017). Flycap: Markerless motion capture using multiple autonomous flying cameras. IEEE transactions on visualization and computer graphics, 24(8), 2284-2297. Yoon, S., & Qiao, C. (2010). Cooperative search and survey using autonomous underwater vehicles (AUVs). IEEE Transactions on Parallel and Distributed Systems, 22(3), 364379....