On the Role of Thermal Imaging in Automotive Applications: A Critical Review

Abstract

For decades, the number of automobiles in urban areas around the world has been increasing. It causes serious challenges such as traffic congestion, accidents, and pollution, which have a social, economic, and environmental impact on widespread urban cities. To overcome these challenges, we need to explore smart AI-based perception systems for vehicular applications. Such types of systems can provide improved situational awareness to the driver and generate early alarm about upcoming obstacles and road incidents. In this study, we have presented the effective use of uncooled thermal IR sensors for designing smart thermal perception systems as an alternative to CMOS visible imaging by presenting state-of-the-art studies for in-cabin and out-cabin vehicular applications with potential long-term benefits for the automotive industry. The key rationale for selecting thermal IR sensors over conventional image sensors is that visible cameras are highly dependent on lighting conditions and performance is degraded significantly in low-lighting scenarios and harsh weather conditions. Contrary to this, thermal sensors remain largely unaffected by external lighting conditions or most environmental conditions, making them a perfect optical sensor choice for all-weather and harsh environmental conditions. This study presents a review of the current state of the art for automotive thermal imaging with a focus on the contributions and advances achieved by the EU-funded project ‘HELIAUS’ in the domain of AI-based thermal imaging pipelines for safer and reliable road journeys.

Keywords

• Thermal-infrared
• AI
• in-cabin
• out-cabin monitoring
• advanced driver-assistance system (ADAS)
• deep learning