A Traffic Information Detection Method at Single Intersection Based on Wi-Fi Data
Source abstract
Abstract
Traffic information analysis plays an essential role in urban signalized intersection control. Wi-Fi technology can be used in multiple scenarios. It is effective to use a Wi-Fi data acquisition device to detect traffic information. This paper aims to study a traffic information detection method at a single intersection based on Wi-Fi data, determine the architecture design of the Wi-Fi data acquisition system, design the Wi-Fi data processing process, and then realize the acquisition of Wi-Fi data at a single intersection. K-means clustering algorithms and the LSTM neural network prediction model are used to obtain the space mean speed and vehicle steering ratio of the intersection sections. This method can be used to obtain and forecast various types of traffic information at intersections. The traffic information of an intersection in Xi’an is detected and predicted by using Wi-Fi technology. The experimental results show that the proposed method has high prediction accuracy.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Network Security and Intrusion Detection · Internet Traffic Analysis and Secure E-voting · Human Mobility and Location-Based Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Railway Transport, Shaanxi Railway Institute, Weinan 714000, China
School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China
Funding
National Key Research and Development Program of China · Shaanxi Provincial Natural Science Foundation of China · Detection and evaluation technology for asphalt pavement smoothness and damage based on smartphone cloud services · Identification and evaluation technology for asphalt pavement damage based on smartphone cloud services
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