Vision-Based Collision Warning Systems with Deep Learning: A Systematic Review.

ABSTRACT: Timely prediction of collisions enables advanced driver assistance systems to issue warnings and initiate emergency maneuvers as needed to avoid collisions. With recent developments in computer vision and deep learning, collision warning systems that use vision as the only sensory input have emerged. They are less expensive than those that use multiple sensors, but their effectiveness must be thoroughly assessed. We systematically searched academic literature for studies proposing ego-centric, vision-based collision warning systems that use deep learning techniques. Thirty-one studies among the search results satisfied our inclusion criteria. Risk of bias was assessed with PROBAST. We reviewed the selected studies and answer three primary questions: What are the (1) deep learning technique

SUBMITTER: Chitraranjan C 

PROVIDER: S-EPMC11856197 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature