Fine-grained analysis of traffic congestions at the turning level using GPS traces

doi:10.11947/j.AGCS.2019.20170448

Abstract

Abstract:

For the issue that existing approaches on studying traffic conditions using GPS traces lack of detailed analysis of traffic congestion, this paper puts forward an approach for detecting traffic congestion events based on taxis' GPS traces at turning level. Firstly, this approach analyzed taxis' operating patterns and filtered valid traces. Then this approach detected traffic congestion traces of three different intensities:mild congestion, moderate congestion and serious congestion, based on analyzing traffic conditions from the filtered valid trace segments. Finally, traffic flow speed, congestion time and congestion distance of each turning direction at an intersection were explored at a fine-grained level. The experimental results show that the proposed approach is able to detect congestions of different intensities and analyze congestion events at turning level.

Key words: traffic congestions, turning-level, space time analysis, GPS trace, big data

CLC Number:

P208

TANG Luliang, KAN Zihan, REN Chang, ZHANG Xia, LI Qingquan. Fine-grained analysis of traffic congestions at the turning level using GPS traces[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(1): 75-85.

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