Short-Term Traffic Flow Prediction and Signal Timing Optimization Based on Deep Learning

Hao Qin,Weishi Zhang,Xin Ning

doi:10.1155/2022/8926445

Abstract

The rapid development of traffic industry has caused traffic congestion and environmental pollution and other problems. Traffic flow prediction and signal timing optimization under different road environments can improve the current traffic environment. In this paper, based on historical traffic data and BP neural network, according to the characteristics of different deep learning modes, SVM neural network is integrated to achieve accurate prediction of traffic flow, fully analyze the characteristics of traffic flow in different traffic environments, and accurately estimate the current traffic capacity. Meanwhile, on the basis of traffic flow prediction data and fuzzy control method, the signal timing optimization of three-phase intersections is realized to ensure the maximum capacity and the lowest average delay time of intersections. Simulation experiments show that the accuracy of the traffic flow prediction method designed in this paper is about 19.5% higher than that of the traditional mean prediction method, and fusion neural network model is more accurate than single neural network model. The optimized signal timing method can accurately control the traffic process with different phases and has obvious improvement in traffic capacity and average delay time compared with the traditional method.

Highlights

With the development of economy and the continuous improvement of transportation demand, transportation industry has become an important pillar of national social development and economic development [1]. e development of intelligent transportation system and transportation industry has caused a certain degree of pressure on the environment and road construction
Erefore, this paper takes this as an opportunity to study short-term traffic flow prediction method and signal timing optimization strategy to improve the traffic environment. e second part of the paper describes the relevant research situation and summarizes the current research status at home and abroad. e third part designs short-time traffic flow prediction method based on deep learning. e fourth part optimizes the signal lamp timing method based on short-term traffic flow prediction and fuzzy control. e fifth part designs the experiment to carry on the experiment and the test to the short-time traffic flow prediction and the signal lamp timing optimization method
The research on signal timing is mainly based on the actual intersection situation and the length of the fleet, without integrating the predicted traffic flow data, which lacks real-time performance and predictability. is paper takes this as an opportunity to study the multifactor traffic flow prediction method and integrates the traffic flow prediction results into the signal timing method to improve traffic communication ability and reduce the average delay time

Summary

Introduction

With the development of economy and the continuous improvement of transportation demand, transportation industry has become an important pillar of national social development and economic development [1]. e development of intelligent transportation system and transportation industry has caused a certain degree of pressure on the environment and road construction. The existing signal lamp collocation is mostly fixed collocation based on expert experience, that is, according to the hour section This method can maintain traffic lights at a relatively low cost, it cannot realize the real-time matching of traffic lights with the actual traffic flow, resulting in the waste of people and material resources, and the effect is not satisfactory. Erefore, this paper takes this as an opportunity to study short-term traffic flow prediction method and signal timing optimization strategy to improve the traffic environment. E fifth part designs the experiment to carry on the experiment and the test to the short-time traffic flow prediction and the signal lamp timing optimization method

Related Work

Design of Short-Term Traffic Flow Prediction Method Based on Deep Learning

Simulation and Test

F LF N LM M TM

Findings

Conclusion