Evaluation of a Wi-Fi Signal Based System for Freeway Traffic States Monitoring: An Exploratory Field Test.

Fan Ding,Zhen Zhang,Shanglu He,Yang Zhou,Guangming Shou,Xiaoxuan Chen

doi:10.3390/s19020409

Abstract

Monitoring traffic states from the road is arousing increasing concern from traffic management authorities. To complete the picture of real-time traffic states, novel data sources have been introduced and studied in the transportation community for decades. This paper explores a supplementary and novel data source, Wi-Fi signal data, to extract traffic information through a well-designed system. An IoT (Internet of Things)-based Wi-Fi signal detector consisting of a solar power module, high capacity module, and IoT functioning module was constructed to collect Wi-Fi signal data. On this basis, a filtration and mining algorithm was developed to extract traffic state information (i.e., travel time, traffic volume, and speed). In addition, to evaluate the performance of the proposed system, a practical field test was conducted through the use of the system to monitor traffic states of a major corridor in China. The comparison results with loop data indicated that traffic speed obtained from the system was consistent with that collected from loop detectors. The mean absolute percentage error reached 3.55% in the best case. Furthermore, the preliminary analysis proved the existence of the highly correlated relationship between volumes obtained from the system and from loop detectors. The evaluation confirmed the feasibility of applying Wi-Fi signal data to acquisition of traffic information, indicating that Wi-Fi signal data could be used as a supplementary data source for monitoring real-time traffic states.

Highlights

Traffic state monitoring is accepted as an extremely important topic, especially when the whole transportation community is studying automated travel and finding solutions for smart cities.Developed and conventional devices such as loop detectors [1], microwave radars [2], and cameras [3,4]have been widely deployed
This paper mainly focuses on extraction of traffic speeds and discussion of the possibility of using Wi-Fi volumes to estimate traffic volumes
Was performed on all state based on the loess (STL) decomposition procedure [36] was performed on all state data data for for both both outputs of the proposed system, and aggregated loop data over two directions

Summary

Introduction

Traffic state monitoring is accepted as an extremely important topic, especially when the whole transportation community is studying automated travel and finding solutions for smart cities.Developed and conventional devices such as loop detectors [1], microwave radars [2], and cameras [3,4]have been widely deployed. Monitoring functions and accuracy of these devices are mainly subject to the direct impacts of individual equipment. Installation of these devices requires coordination with roadside power lines, increasing the costs of installation and maintenance [5]. Data sources such as GPS data [5,6,7], cellular data [8,9,10,11], Bluetooth data [12,13,14,15,16], and Wi-Fi signal data [17,18,19] have gained attention from the community for traffic state monitoring.

Methods

Results

Discussion

Conclusion