Real-time vehicular accident prevention system using deep learning architecture

作者：

Highlights：

• Real-time collision avoidance (RTCA) algorithm for moving vehicles is proposed.

• The RTCA algorithm is developed on MtobileNet Deep Learning Architecture.

• Single Shot Multibox Detection techniques are proposed using the RTCA algorithm.

• The results are analyzed with 3x3x9 repeated measure ANOVA.

• The RTCA algorithm predicts the possibility of accidents within 0.09 Sec.

摘要

•Real-time collision avoidance (RTCA) algorithm for moving vehicles is proposed.•The RTCA algorithm is developed on MtobileNet Deep Learning Architecture.•Single Shot Multibox Detection techniques are proposed using the RTCA algorithm.•The results are analyzed with 3x3x9 repeated measure ANOVA.•The RTCA algorithm predicts the possibility of accidents within 0.09 Sec.

论文关键词：Accident prevention,Deep learning architecture,Repeated measures ANOVA,Real-time object identification,Single Shot Multibox Detection

论文评审过程：Received 8 March 2022, Revised 22 May 2022, Accepted 8 June 2022, Available online 13 June 2022, Version of Record 17 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117837