Vehicle Detection and Tracking Using Thermal Cameras in Adverse Visibility Conditions.

ABSTRACT: Level 5 autonomy, as defined by the Society of Automotive Engineers, requires the vehicle to function under all weather and visibility conditions. This sensing problem becomes significantly challenging in weather conditions that include events such as sudden changes in lighting, smoke, fog, snow, and rain. No standalone sensor currently in the market can reliably perceive the environment in all conditions. While regular cameras, lidars, and radars will suffice for typical driving conditions, they may fail in some edge cases. The goal of this paper is to demonstrate that the addition of Long Wave Infrared (LWIR)/thermal cameras to the sensor stack on a self-driving vehicle can help fill this sensory gap during adverse visibility conditions. In this paper, we trained a machine learning-based

SUBMITTER: Bhadoriya AS 

PROVIDER: S-EPMC9227869 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature