Risk aware Trust of Information for Improving Safety in Vehicular Networks

Author(s)
최종영
Advisor
고영배
Department
일반대학원 AI융합네트워크학과
Publisher
The Graduate School, Ajou University
Publication Year
2022-02
Language
eng
Keyword
AoIBSMRate adaptation논문아주대학교차량 네트워크
Abstract
차량 네트워크에서 BSM(Basic Safety Messages)을 기반으로 하는 안전 애플리케이션은 도로 안전을 크게 향상시킬 것이다. 차량이 주기적으로 broadcast하는 BSM은 차량의 위치, 속도 및 방향과 같은 정보가 포함된다. BSM이 오래되거나 잘못되었다면 충돌로 이어질 수 있다. 따라서 신선하고 정확한 BSM을 전달하는 데에 BSM rate adaptation은 필요하다. 최근 많은 연구에서 Age of Information (AoI) 개념을 BSM rate adaptation에 적용하였다. 이 논문에서는 AoI를 "있는 그대로" 적용하는 것이 최적이 아닌 이유를 조사하고 AoI 최소화를 위해 특정 차량을 선택하는 것의 중요성을 보여준다. 또한 BSM의 중요성 측면에서 신뢰성을 정량화하는 데 적용할 수 있는 새로운 Trust of Information (ToI) 개념을 제안한다. 시뮬레이션을 통해 ToI 기반 BSM rate adaptation 알고리즘을 최근의 BSM rate adaptation과 비교하여 ToI 알고리즘이 안전 측면에서 더 우수함을 보여준다.
Alternative Abstract
In vehicular networks, safety applications based on Basic Safety Messages(BSMs) promise to improve the road safety significantly. BSMs broadcast by a vehicle contain current information on its kinematics namely its position, speed, and heading. An outdated or incorrect BSM can lead to collision; therefore, BSM rate adaptation is necessary to communicate fresh and accurate information. Many recent studies have applied the Age of Information (AoI) concept to BSM rate adaptation. In this dissertation, I investigate why applying AoI "as is" is not optimal, and demonstrate the importance of selecting specific vehicles for AoI minimization. I also propose the novel Trust of Information (ToI) concept, which can be applied to quantify the reliability of BSMs in terms of their importance. Through simulations, a ToI-based BSM rate adaptation algorithm is compared with recent BSM rate adaptation schemes, demonstrating that the ToI algorithm outperforms the scheme in terms of safety assurance.
URI
https://dspace.ajou.ac.kr/handle/2018.oak/20687
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Graduate School of Ajou University > Department of Artificial Intelligence Convergence Network > 3. Theses(Master)
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