An Overview on Automated Vehicles

Authors

  • Arvind Kumar SOEIT, Sanskriti University, Mathura, Uttar Pradesh, India Author
  • Ajay Agrawal SOEIT, Sanskriti University, Mathura, Uttar Pradesh, India Author

DOI:

https://doi.org/10.55524/

Keywords:

Autonomous, Architecture, Driverless, Machine, Navigation Technology

Abstract

A self-driving car is a machine that can  really hear and function without the need for human  intervention. A human rider is never needed to maintain  control of the vehicle or to be in the vehicle at the same  time. A self-employed vehicle should be able to do all of the  duties that a competent human driver can. A standard  vehicle should be capable of traveling to any place.  Thousands of hours have been recorded on US highways by  self-driving vehicles, such as Google's robotic vehicle  prototype, but they are not yet commercially accessible.  Self-sufficient vehicles use a range of technologies. It may  be developed to assist navigation using GPS sensor data.  Sensors and other equipment should be used to avoid  accidents. And also use a variety of technologies, such as  extended truth, in which a vehicle delivers data to drivers in  novel and innovative ways. Many people think that  substantial autonomous vehicle development will aggravate  current man-made car insurance and traffic regulations.  Extensive research on autonomous cars is taking place not  just in the United States, but also in Europe and other areas  of the world. According to industry analysts, it will only be a  matter of time until individuals are able to use a device on a  regular basis as a result of such advances. The construction  and device design of an autonomous vehicle, as well as the  control system module that enables the vehicle to travel  independently, are covered in this article. The CaRINA I  model was used to test and validate the team's autonomous  navigation and driver assistance technologies. Our  technology covers modifications to mechanical vehicles as  well as the creation and implementation of an integrated  computer architecture.

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References

Reina G, Johnson D, Underwood J. Radar sensing for intelligent vehicles in urban environments. Sensors (Switzerland). 2015;

Becker F, Axhausen KW. Literature review on surveys investigating the acceptance of automated vehicles. Transportation (Amst). 2017;

Paradarami TK, Bastian ND, Wightman JL. A hybrid recommender system using artificial neural networks. Expert Syst Appl. 2017;

Petit J, Shladover SE. Potential Cyberattacks on Automated Vehicles. IEEE Trans Intell Transp Syst. 2015;

Habibovic A, Lundgren VM, Andersson J, Klingegård M, Lagström T, Sirkka A, et al. Communicating intent of automated vehicles to pedestrians. Front Psychol. 2018;

González D, Pérez J, Milanés V, Nashashibi F. A Review of Motion Planning Techniques for Automated Vehicles. 2015;1–11.

Becker F. Literature review on surveys investigating the acceptance of automated vehicles. Transportation

(Amst). 2017;

Cavoli C, Phillips B, Cohen T, Jones P. Social and behavioural questions associated with Automated Vehicles A Literature Review. 2017;(January).

Soteropoulos A, Berger M, Ciari F. Impacts of automated vehicles on travel behaviour and land use : an international review of modelling studies. Transp

Rev. 2018;0(0):1–21.

Milakis D, Snelder M, Van Arem B, Van Wee B, De Almeida Correia GH. Development and transport implications of automated vehicles in the Netherlands: Scenarios for 2030 and 2050. Eur J Transp Infrastruct Res.2017;

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Published

2021-11-30

How to Cite

An Overview on Automated Vehicles . (2021). International Journal of Innovative Research in Computer Science & Technology, 9(6), 31–35. https://doi.org/10.55524/