Multifunctional Intelligent Security Integrated System of Highway Level Crossing
Download PDF

Keywords

Traffic safety
Guarantee system
Deep learning
Signal control

DOI

10.26689/jera.v6i6.4719

Submitted : 2023-01-18
Accepted : 2023-02-02
Published : 2023-02-17

Abstract

In consideration of the safety of drivers, we designed a multifunctional intelligent seecurity guarantee integrated system for highway level crossing. Different from the existing intersection signs on the market, intelligent highway-level intersection indicators are based on the use of deep learning and computer vision technology to build a convolutional neural network model that can accurately recognize traffic accident images and traffic jams in a short period of time as well as obtain real-time road and highway meteorological environment information.

References

Zhang S, 2020, Self-Positioning of Monocular Visual Vehicles Based on Standard Road Signs, thesis, Shandong University.

Tao H, Zhang S, 2019, Intelligent Electronic Road Sign Design Based on NB-IoT. Information and Communication, 2019(02): 102–104.

Liang ZY, 2016, Intelligent Electronic Road Signs and Road Information Interaction System, thesis, South China University of Technology.

Chen J, Chen Z, Zheng H, et al., 2020, Black Sign Identification Model Based on PSO. Journal of Software, 31(09): 2785–2801.

Zhang X, 2020, Research on the Image Enhancement and Recognition Technology of Foggy Highway Road Signs, thesis, Changchun University of Science and Technology. https://doi.org/10.26977/d.cnki.gccgc.2020.000617

Lin F, Liu Y, Zhang D, et al., 2018, Design of Intelligent Road Sign Identification System Based on Deep Learning. Application of Electronic Technology, 44(06): 68–71.

Liang Z, 2017, Research on the Application Status and Development Trend of the Internet of Vehicles in Intelligent Transportation. Transportation World, 2017(22): 14–15.

Kong L, Wu X, 2016, Mobile Augmented Reality System Based on Road Sign Identification. Information Technology, 2016(03): 116–120.

Li W, 2016, Word Recognition of Street Signs Based on Deep Learning, thesis, South China University of Technology.

Ding K, 2013, Intelligent Detection and Weight Removal of Traffic Signs, dissertation, Wuhan University of Technology.

Ge J, 2011, Design and Implementation of Intelligent Urban Bus Dispatching System Based on GIS/GPS/GPRS, thesis, Xidian University.

Wang J, 2008, “Speak”: Please Detour.... Chengdu Daily, December 20,2008, A09.

Qi T, 2022, Research on Traffic Flow Prediction Algorithm Based on Graph Convolution and Deep Learning, thesis, Jiangnan University.

Ren N, 2021, Short-Time Passenger Flow Prediction of Urban Rail Transit by the Deep Learning Algorithm. System Simulation Technology, 17(04): 259–264.

Cheng H, 2020, Research on Traffic Accident Risk Prediction Algorithm in Vehicle Connected Edge Network, thesis, Nanjing University of Posts and Telecommunications.