Environmental Change Detection During Route-Clearance Operation via Autonomous Vehicle (AV): A Proposed AI-Based Approach

Autonomous Vehicles (AV) are capable of performing tasks without human intervention and assistance. They serve prominently in tasks that pose a significant risk to humans, especially in outdoor environment exploration. It's essential to save humans‘ lives and prevent them from outdoor roads dangerous factors such as mines, explosives, and ammunition. However, there is a need to design a system that can identify objects ahead of and detect them continuously in a real-time setting during AV driving in a route-clearance operation in urban cities. This assists the AV in identifying danger factors early through the environmental change detection process. Since the change in the dynamic scenes of the environment is still of interest to scientists, therefore, this paper proposes an idea of a practical approach based on Artificial Intelligence (AI) techniques for environmental change detection and avoidance of dangerous factors by AV during a route-clearance operation. The suggested approach aims to develop a comprehensive real-time change detection system ensuring the AV's immediate avoidance of danger factors in the explored environment. Where an operator inside the AV classifies the detected changes and assesses whether they pose a threat. This proposal presents a potentially vital solution for detecting change and danger factors by AVs, highlighting the immediate need to understand and respond to the changes in our environment in real-time settings under multiple road patterns, weather conditions, and illuminations.