Comprehensive Evaluation of Regional Road Transport Safety Service Level

Authors

  • Xiaoxu Dang Institute of Management,Xi’an University of Science and Technology,Xi’an,710054, China
  • Guoyu Wang Institute of Management, Xi'an University of Science and Technology,Xi’an,710054, China
  • Xiaodong Zhou Shaanxi Provincial Department of Transportation, Xi'an, 710075, China
  • Shihui Wang Institute of Management, Xi'an University of Science and Technology,Xi’an,710054, China

DOI:

https://doi.org/10.12694/scpe.v25i4.2999

Keywords:

road safety, transport system, intelligent transportation, deep convolutional neural network

Abstract

Ensuring road transport safety is a critical imperative for regional development and public welfare. This abstract outline a comprehensive evaluation framework designed to assess the service level of regional road transport safety. The proposed methodology integrates diverse parameters, encompassing infrastructure, technology, policy, and human factors, to provide a holistic understanding of the safety landscape. Using real-time data integration and powerful analytics, the assessment system combines quantitative and qualitative indicators. Technology aspects of infrastructure evaluations centre on the effectiveness of automated transportation systems and their influence on accident reduction; architecture evaluations also cover the layout of roads, advertising, and maintenance requirements. Policy evaluation is examining current laws and the ways in which they are enforced while considering how they affect the behaviour of drivers and public safety. The proposed method uses DCNN method for intelligent road transport safety. Using DCNN algorithms to monitor and regulate traffic congestion in smart  cities represents a significant leap in the use of deep learning in traffic management.

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Published

2024-06-16

Issue

Section

Special Issue - Evolutionary Computing for AI-Driven Security and Privacy: Advancing the state-of-the-art applications