Research Article
Reliability Evaluation Method of Intelligent Transportation System Based on Deep Learning
@INPROCEEDINGS{10.1007/978-3-031-50577-5_21, author={Xiaomei Yang}, title={Reliability Evaluation Method of Intelligent Transportation System Based on Deep Learning}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part III}, proceedings_a={ICMTEL PART 3}, year={2024}, month={2}, keywords={Deep Learning Intelligent Transportation System Evaluation Index Ahp Method Factor Analysis Method Reliability Evaluation}, doi={10.1007/978-3-031-50577-5_21} }- Xiaomei Yang
Year: 2024
Reliability Evaluation Method of Intelligent Transportation System Based on Deep Learning
ICMTEL PART 3
Springer
DOI: 10.1007/978-3-031-50577-5_21
Abstract
Urban road reliability analysis is an important part of traffic condition analysis and research in recent years. The research on road network reliability can provide strong information support for the control, induction, optimization and planning of intelligent transportation systems. In this context, a reliability evaluation method of intelligent transportation system based on deep learning is proposed. Use the Delphi method to select evaluation indicators and build an evaluation index system. The AHP method and factor analysis method were used to calculate the comprehensive weight of the indicators. Based on the deep belief network in deep learning, an evaluation model is constructed, the reliability index is calculated, and the degree of reliability is judged. The test results show that the intelligent transportation system is applied in 9 different administrative regions, and the obtained reliability indexes are all above 1.0, indicating that the reliability of the intelligent transportation system is high.
