A Real-Time Urban Traffic Detection Algorithm Based on Spatio-Temporal OD Matrix in Vehicular Sensor Network

Ke Zhang, Guangtao Xue

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DOI: 10.4236/wsn.2010.29080                

Abstract

Currently, there are kinds of algorithms in order to detect real-time urban traffic condition. Most of these approaches consider speed of vehicles as a main metric to describe traffic situation. In this paper, we find out two important observations through several experiments. (1) In urban city, the speed of vehicles is influenced significantly by some factors such as traffic lights delay and road condition. The actual situation rarely satisfy hypothesis required for these solutions. Therefore, these traditional algorithms do not work well in practical environment. (2) Traffic volume on a road segment shows strong pattern and changes smoothly at adjacent time. This feature of traffic volume inspires us to define a metric: traffic-rate, which is used to detect traffic condition in real time. In our solution, we develop a novel traffic-detection algorithm based on original- destination (OD) matrix. We illustrate our approach and measure its performance in real environment. The performance evaluations confirm the effectiveness of our algorithm.

Keywords

KNN; Linear Least Square; OD Matrix; Traffic Status Detection

Conflicts of Interest

The authors declare no conflicts of interest.

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