Real-time estimation of road traffic speeds from cell-based vehicle trajectories

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Abstract

This paper presents a novel approach for urban road networks to estimate traffic speeds using vehicle trajectories captured by detectors on transportation cells. By scanning and analyzing dynamic traffic streams of passing-vehicles, we calculate the real-time traffic speed of road segment separated by adjacent detectors, which are further synthesized to present the traffic speed of whole road. Compared to driving routes data with limited coverage or floating GPS data with occasional missing that are both frequently utilized for traditional road speed estimation, our approach utilizes the full coverage detector data and is proved to have more accurate and reliable results in its application for two large cities of China. An analysis and visualization system was hence developed, whose successful operation in several transportation departments indicated the efficiency of our approach. It helps to guide travelers the optimal driving routes, which greatly relieves the huge traffic stress of city road.

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Sun, X., Yu, D., Liao, S., Li, W., & Zhou, C. (2019). Real-time estimation of road traffic speeds from cell-based vehicle trajectories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11434 LNCS, pp. 220–228). Springer Verlag. https://doi.org/10.1007/978-3-030-17642-6_19

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