Scalable and Robust Mobility Prediction with Traffic Management Strategy for Connected and Autonomous Vehicles.

Autor: Najim, Ali Hamzah
Předmět:
Zdroj: International Journal of Computational & Electronic Aspects in Engineering (IJCEAE); Oct-Dec2023, Vol. 4 Issue 4, p90-99, 10p
Abstrakt: Vehicular Ad-hoc Network (VANET) is a highly trending communication technology and it is developed mainly to handle complicated futuristic environment in the intelligent transportation system (ITS) based applications. In the vehicular network the communication is performed by transmitting the control messages through the roadside units (RSUs) and that leads to increase the communication capacities of the vehicles. In an urban environment recent times the development of vehicles are huge and that leads to the increase of lack of connectivity and other traffic issues among the vehicles which directly affects the communication quality. For that purpose in this article Scalable and robust Mobility Prediction with Traffic Management Strategy in VANETs (SRMPT-VANETs) are developed. This method perform two operation namely effective predictive information gathering and traffic management strategy that helps to control the traffic and to predict the high speed mobility in an effective manner. As the results the communication quality of the urban environment can be improvised. The implementation of this method is done in OMNET++ and as well the matrices which are in use for the performance analysis are The essential metrics to consider are energy efficiency, delay, routing overhead, and packet delivery ratio. In the final step of the study, results are compared to those obtained using reference methods such as the ICFDB-VANET and the RSUCI-VANETs. The results show that the proposed method improves upon the state-of-the-art by 17% in terms of packet delivery ratio and 20% in terms of energy efficiency. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index