Key Technologies For Autonomous Cars: Path Planning, Car Navigation, Control, And Perception

Background

Autonomous Driving could be defined as the disruptive form of innovation within the recent years. Though the technology based on vehicle driving could be assembled within premium cars on a larger scale, hence the concept of these self-driven cars could be a serious concept that could be discussed within newspapers reports and articles (Chen et al., 2015). In general terms, the self-driven cars could also be defined as a wheeled mobile robot and an intelligent vehicle. These vehicles would have the possibility of arriving at a destination based on the gained information from different inbuilt sensors. These sensors would include the perception of the environment of paths, information of car control and route. The primary characteristic of the self-driven cars would be to transport people to a pre-defined target without the purpose of humans to drive the cars (Wei et al., 2013). The different forms of technologies that are integrated within the self-driven cars include architecture, automatic control, AI, computer vision and various other forms of advanced technologies.

The statement of the problem would be mainly involved based on the protection and controls over the automotive vehicles. These automotive vehicles are designed to fit the needs of the user. However, there could be many issues based on the maintaining the movement and proper guidance of such kind of cars. Hence the assessment and management of the different risks would be a major form of concern based on the particular research.

The primary aim of the research would be based on the different operations based on the commercial and successful use of automotive cars, which would thus make human lives easier.

The objectives of the research are:

• To provide essential information about the decision about the control of the car
• To assess the different forms of strategies that could address the issues
• Assess the different risks that could affect the operations of automotive cars.

Will the small and large scale commercial usage of autonomous cars would prove to be a major help for the society?

There are different kinds of advanced technologies that are primarily integrated within the autonomous cars. These forms of technologies would include technologies based on computer science, intelligent control technology and pattern recognition. The kind of technology that are embedded within the autonomous cars would represent a higher level of scientific research (Zhang et al., 2016). They would also be able to represent the scientific advances of the concerned country. Different papers have thus reviewed the process of technology that have been used within the cars due to a higher level of complexity based on the design process used within the cars (Seif & Hu, 2016).

Problem Statement

(Fig 1: Classification of the Primary Technology of Autonomous Cars)

As compared to the manual methods of driving, the primary characteristic of autonomous cars would be based on an automation equipment for the purpose of replacing the human driver. The core technology embedded within the autonomous cars could be classified into four categories. These are known as path planning, car navigation systems, car control and environment perception (Anderson et al., 2014).

Based on the different kinds of sensors that would be embedded within the cars, these intelligent cars would be able to perform the planning of the paths and the various kinds of shortest routes that would be able to make the car top reach till their destination (Broggi et al., 2013).

There are two major issues that could be affecting the driving of the autonomous cars. These would include the current location and the ways of driving from the location up to the predetermined destination. However, in the cases of self-driving cars, the car should be able to intelligently locate their position and thus be able to perform the planning of the paths to reach till the destination (Litman, 2017).

(Fig 2: On-Board Navigation System of Autonomous Cars)

There should be a proper form of control based on the driving activity of the cars. Based on the impact of different kinds of sensors, the car would be able to locate their personal position. In the navigation systems of these cars, the global positioning systems (GPS) and geographic information system would be embedded for the purpose of receiving the information of the location. Hence the controlling systems within these cars would be able to control themselves. These cars are equipped with automatic braking systems, advanced steering options and various other control mechanisms. These different forms of mechanisms would be able to control the different functionalities of the car (Lee et al., 2013).

This form of perception could be defined as one of the module based on the autonomous cars. In order to gain sufficient information based on the decision of the control of the car, the car would be required to perceive the surrounding environment. The major forms of methods based on perception include visual navigation, radar navigation and laser navigation (Ziegler et al., 2014). In this form of perception the different kinds of embedded sensors would be deployed for sensing the various kinds of information of the environment and thus react according to the needs of the environment.

Research Aim and Objectives

In the present times, the autonomous cars would be able to configure different forms of sensors that would be non-existent within the traditional cars. The vision and laser sensors would be mainly be used for environmental perception based on typical key sensors (Fagnant & Kockelman, 2014). The different kinds of sensors that are mainly embedded within these autonomous cars are highly expensive. They have higher forms of requirement based on their condition. The installation and use of these sensors within the cars would include different forms of risks that need to be avoided. The service lifetime of these kind of high-powered sensors would reduce after a prolonged period of use (Yaghoubi et al., 2013). Hence, these sensors should be highly efficient in order to fit according to the needs of movement of the cars.

The most important issue of sociological research is based on social habits. With the increase in the level of self-driven cars, it has been seen that the technologies would have a major form of impact on the life of transportation within the people. The use of self-driven cars would replace the existing vehicles and would make the people to become much more dependent on computing technologies for redefining the ways of technologies (Urry, 2016). The impact of self-driven cars would be able to promote a better form of life among the people.

The methodology of collection of different forms of data would be based on the secondary based collection of data. These data would be based on the works of different researchers who have performed extensive form of research within the concerned area. The research would also make the extensive form of research based on the gaining of vast knowledge that could be gathered from different journals, media sources and research articles. These previous works of different researchers would be properly reviewed and thus this would be helpful in understanding the different gaps within the research area. Based on the different kinds of previous works of research, further form of investigation could be developed based on successful development of improved ideas based on self-driven cars.

	Task Description	Duration	Strat Date	End Date
1	Selection of Topic	6	01 August 2018	07 August 2018
2	Gathering information from secondary sources	14	08 August 2018	22 August 2018
3	Finalizing the layout	11	23 August 2018	03 September 2018
4	Review of Literature	22	04 September 2018	26 September 2018
5	Develop Research Plan	14	27 September 2018	11 October 2018
6	Selection of Proper Technique	7	12 October 2018	19 October 2018
7	Collection of Secondary Data	21	20 October 2018	10 November 2018
8	Data  Interpretation and Analysis	12	11 November 2018	23 November 2018
9	Drawing of Conclusion	7	24 November 2018	01 December 2018
10	Preparation of Rough Draft	9	02 December 2018	11 December 2018
11	Completion of Final Work	19	12 December 2018	31 December 2018

(Fig 3: Proposed Project Description)

(Fig 4: Proposed Budget of the Project)

(Fig 4: Proposed Timeline of the Project)

Conclusion

Based on the discussion from the research proposal, it could be stated the different forms of risks within the operations of autonomous cars. The research is conducted based on the discussion of the various kinds of operations that are performed within the functioning of autonomous cars. Based on the discussion from the various works of different researchers, it could be discussed that the self-driving cars makes the configuration of different kinds of sensors. These sensors would not be present in the traditional cars. The discussion also focuses on the risks that could be incurred within the use of sensor technology. These self-driven cars makes use of AI based technologies. They should be able to mitigate the different forms of risks that could be incurred within the systems. The mitigation of these form of incurred risks would be able to improve the ways in which the self-driven cars would leave a major form of impact on the people.

References

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Broggi, A., Buzzoni, M., Debattisti, S., Grisleri, P., Laghi, M. C., Medici, P., & Versari, P. (2013). Extensive tests of autonomous driving technologies. IEEE Transactions on Intelligent Transportation Systems, 14(3), 1403-1415.

Chen, C., Seff, A., Kornhauser, A., & Xiao, J. (2015). Deepdriving: Learning affordance for direct perception in autonomous driving. In Proceedings of the IEEE International Conference on Computer Vision (pp. 2722-2730).

Fagnant, D. J., & Kockelman, K. M. (2014). The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C: Emerging Technologies, 40, 1-13.

Lee, J., Park, B. B., Malakorn, K., & So, J. J. (2013). Sustainability assessments of cooperative vehicle intersection control at an urban corridor. Transportation Research Part C: Emerging Technologies, 32, 193-206.

Litman, T. (2017). Autonomous vehicle implementation predictions. Victoria, Canada: Victoria Transport Policy Institute.

Seif, H. G., & Hu, X. (2016). Autonomous driving in the iCity—HD maps as a key challenge of the automotive industry. Engineering, 2(2), 159-162.

Urry, J. (2016). Mobilities: new perspectives on transport and society. Routledge.

Wei, J., Snider, J. M., Kim, J., Dolan, J. M., Rajkumar, R., & Litkouhi, B. (2013, June). Towards a viable autonomous driving research platform. In Intelligent Vehicles Symposium (IV), 2013 IEEE (pp. 763-770). IEEE.

Yaghoubi, S., Akbarzadeh, N. A., Bazargani, S. S., Bazargani, S. S., Bamizan, M., & Asl, M. I. (2013). Autonomous robots for agricultural tasks and farm assignment and future trends in agro robots. International Journal of Mechanical and Mechatronics Engineering, 13(3), 1-6.

Zhang, X., Gao, H., Guo, M., Li, G., Liu, Y., & Li, D. (2016). A study on key technologies of unmanned driving. CAAI Transactions on Intelligence Technology, 1(1), 4-13.

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