The U-Turn information collecting method using vehicle GNSS trajectory data

doi:10.11947/j.AGCS.2023.20220063

Abstract

Abstract: With the rapid development of intelligent transportation and refined navigation technology, the requirements of coverage, accuracy, richness and freshness for road maps are becoming higher and higher. As a significant element in connectivity of urban road network, U-Turn has become an important part of road data renewal. It is high-cost and long-term to update by existing professional surveying and mapping models, resulting in poor reality of U-Turn data. In this paper, using vehicle GNSS trajectory big data, an automatic U-Turn information collecting approach is proposed. The turning round point pairs and turning round behaviors are first extracted through trajectory tracking. Then, DBSCAN algorithm is used to extract turning round clusters. Next, a support vector machine model is built based on traffic flow proportion to eliminate illegal turning round behaviors. Finally, U-Turn positions and spatial structures are identified according to distribution characteristics of U-Turn clusters. Taking vehicle GNSS trajectory data of DiDi in Wuhan as an example, the experiment detects 183 road sections in Jianghan District. The recognition recall rate of U-Turn structures was 88.3%, and the precision rate was 87.6%. At the same time, the horizontal and vertical position accuracy of U-turn positions are 3.40 m and 5.90 m, respectively. Results show that the proposed method can effectively collect the position and structural category of U-Turn from vehicle GNSS trajectory big data, and can provide a promising solution for short-term and low-cost collection of U-Turn data.

Key words: vehicle GNSS trajectory data, U-Turn information, trajectory tracking, urban road network

CLC Number:

P227

WANG Zihao, TANG Luliang, YANG Xue, DAI Ling, LI Chaokui. The U-Turn information collecting method using vehicle GNSS trajectory data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(8): 1330-1341.

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