Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning

التفاصيل البيبلوغرافية
العنوان: Enhancement of High-definition Map Update Service Through Coverage-aware and Reinforcement Learning
المؤلفون: Redondo, Jeffrey, Yuan, Zhenhui, Aslam, Nauman
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
الوصف: High-definition (HD) Map systems will play a pivotal role in advancing autonomous driving to a higher level, thanks to the significant improvement over traditional two-dimensional (2D) maps. Creating an HD Map requires a huge amount of on-road and off-road data. Typically, these raw datasets are collected and uploaded to cloud-based HD map service providers through vehicular networks. Nevertheless, there are challenges in transmitting the raw data over vehicular wireless channels due to the dynamic topology. As the number of vehicles increases, there is a detrimental impact on service quality, which acts as a barrier to a real-time HD Map system for collaborative driving in Autonomous Vehicles (AV). In this paper, to overcome network congestion, a Q-learning coverage-time-awareness algorithm is presented to optimize the quality of service for vehicular networks and HD map updates. The algorithm is evaluated in an environment that imitates a dynamic scenario where vehicles enter and leave. Results showed an improvement in latency for HD map data of $75\%$, $73\%$, and $10\%$ compared with IEEE802.11p without Quality of Service (QoS), IEEE802.11 with QoS, and IEEE802.11p with new access category (AC) for HD map, respectively.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2402.14582
رقم الأكسشن: edsarx.2402.14582
قاعدة البيانات: arXiv