Big Data Management in Advanced Driver Assistance Systems: Challenges and Opportunities

EasyChair Preprint 15048

Abstract

The growing complexity of Advanced Driver Assistance Systems (ADAS) is leading to an unprecedented amount of data generated from multiple sources such as cameras, radar, LIDAR, and vehicle sensors. Managing this vast data effectively is critical to ensuring the real-time decision-making and overall efficiency of ADAS. This paper explores the role of Big Data management in ADAS, focusing on the challenges associated with processing, storing, and retrieving large volumes of data. Key challenges include data integration from disparate sources, real-time processing demands, data security, and the need for scalable storage solutions. Additionally, the paper examines opportunities for enhancing ADAS performance through advanced database management systems, including the adoption of cloud-based architectures, distributed databases, and machine learning algorithms. The potential of these solutions to improve data accuracy, system reliability, and decision-making speed will be critically analyzed, highlighting their importance in the future development of fully autonomous vehicles.

Keyphrases: Advanced Driver Assistance Systems (ADAS), Big Data, Database Management Systems (DBMS), data management, real-time processing, sensor data fusion

@booklet{EasyChair:15048,
  author    = {Adeoye Ibrahim},
  title     = {Big Data Management in Advanced Driver Assistance Systems: Challenges and Opportunities},
  howpublished = {EasyChair Preprint 15048},
  year      = {EasyChair, 2024}}