Citation :

Srinivas Naveen Reddy, 2023. "The Role of Artificial Intelligence and Machine Learning in Autonomous Vehicle Diagnostics and Control" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 1, Issue 1: 72-81.

Abstract :

The economic and social costs of motor vehicle crashes and the strong media attention given to autonomous vehicle crashes are driving interest in solving the associated technical and policy-related issues. A key to alleviating these concerns is to enable autonomous vehicle control systems with advanced sensor technologies and data analytics. This work presents a machine learning and data analytics framework for driving assessment under partially observable Markov Decision Processes (MDPs). The machine learning framework, named Q-Stat, estimates distributions of future states and actions for look-ahead periods and evaluates the interaction, cooperation, and autonomous driving capabilities of agents. A prototype version of Q-Stat is engineered to be integrated into advanced driver assistance systems (ADAS) for driving and accident prediction. A full simulation and experimental validation are being coherently left for autonomous vehicle testing regulatory standards.

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Keywords :

Communication for the 2021 IEEE International Workshop on Communication, Computing, and Networking in Cyber-Physical Systems (CCNCPS 2021).