Grid Mapping for Road Network Abstraction and Traffic Congestion Identification Based on Probe Vehicle Data

Author:

Wang Liwei1ORCID,Yan Xuedong2,Liu Yang3,Liu Xiaobing4,Chen Deqi4

Affiliation:

1. Ph.D. Candidate, Ministry of Transportation Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China. ORCID: .

2. Professor, Ministry of Transportation Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China (corresponding author).

3. Belt and Road Initiative Construction Promotion Center, National Development and Reform Commission, 38 Yuetan South St., Xicheng Dist., Beijing, PR China.

4. Ph.D. Candidate, Ministry of Transportation Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Reference51 articles.

1. A comparison and evaluation of map construction algorithms using vehicle tracking data;Ahmed M.;GeoInformatica,2015

2. Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks;Alshehhi R.;ISPRS J. Photogramm. Remote Sens.,2017

3. Dynamic Origin–Destination Matrix Estimation Using Probe Vehicle Data as A Priori Information

4. Level of service estimation based on low-frequency probe vehicle data;Axer S.;Transp. Res. Procedia,2014

5. Beijing Traffic Management Bureau. 2019. “Budget information of public security and traffic administration of Beijing public security bureau.” Accessed February 27 2019. http://jtgl.beijing.gov.cn/jgj/jgxx/95495/czyjs/598326/index.html.

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