Research of technologies of autonomous vehicles for use in Smart City networks

DOI: 10.31673/2412-9070.2021.055459

Abstract

The article presents the prerequisites for the use of autonomous cars. The goals that try to achieve their use and the problems that hinder this concept are also identified. The analysis of potentially used communication technologies in autonomous vehicles is carried out. The following technologies were investigated in the analysis: 5G, LTE, eSIM, WiFi, DSRC, Bluetooth and ZigBee. The very concept of autonomous transport has become a reality thanks to the fifth generation (5G) standard, which provides low latency and high data rates. Specialized equipment used by an autonomous vehicle moving on highways is indicated: artificial intelligence, cameras, radar, leader. The analysis of new technologies was also carried out, which included: peripheral computing, cloud computing for vehicles (VCC), SDN, NFV and named data networks (NDN). With the advancement of edge computing, autonomous vehicles have been able to efficiently process data and find patterns over time, moving sensor data closer to the automotive network, leading to faster decision making. With interoperability, autonomous vehicles can mitigate risks using SDN. VCC has a big impact on autonomous vehicles through traffic management and road safety by leveraging vehicle resources such as computers, storage and the Internet to generate solutions. NFV provides the ability to distribute network functions with an emphasis on processing power so that they can be used efficiently. NFV enables 5G-enabled autonomous vehicles to focus on the services and locations that matter most. Autonomous vehicles make it easier for human drivers to perform intelligent operations such as collision avoidance, lane departure warning and traffic sign detection. At the same time, autonomous vehicles strive to reduce fuel consumption and the number of accidents, as well as improve the mobility of people with reduced mobility and the elderly. Autonomous transport can reduce the large number of accidents that occur due to unsteady driving, bad weather or pedestrian disruptions, as well as speeding and human error. By successfully completing the development of an autonomous vehicle, accidents can be prevented by 90%.

Keywords: autonomous vehicles; vehicular networks; self-driving cars; intelligent transportation systems; Internet of vehicles.

References
1. Hussain R., Zeadally S. Autonomous cars: Research results, issues, and future challenges // IEEE Communications Surveys & Tutorials. 2018. Vol. 21, no. 2. P. 1275–1313.
2. Wang J., Liu J., Kato N. Networking and communications in autonomous driving: A survey // IEEE Communications Surveys & Tutorials. 2018. Vol. 21, no. 2. P. 1243–1274.
3. Wang Z., Chen Y., Li C. Corman: A novel cooperative opportunistic routing scheme in mobile ad hoc networks // IEEE Journal on Selected Areas in Communications. 2012. Vol. 30, no. 2. P. 289–296.
4. Altun M., Celenk M. Road scene content analysis for driver assistance and autonomous driving // IEEE Transactions on Intelligent Transportation Systems. 2017. Vol. 18, no. 12. P. 3398–3407.
5. Named data networking in vehicular ad hoc networks: State-of-the-art and challenges / H. Khelifi, S. Luo, B. Nour [et al.] // IEEE Communications Surveys & Tutorials. In Press, 2019.