Short-Term Traffic Flow Prediction of Expressway Considering Spatial Influences-Reference-Cited by-同舟云学术

Short-Term Traffic Flow Prediction of Expressway Considering Spatial Influences

Published:2022-06 Issue:6 Volume:148 Page:
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Shuai Chunyan¹^ORCID,Wang WenCong²,Xu Geng³,He Min⁴,Lee Jaeyoung⁵

Affiliation:

1. Professor, Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Kunming, Yunnan 650041, China. ORCID: .

2. Master’s Student, Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Kunming, Yunnan 650041, China.

3. Assistant Engineer, Kunming Urban Planning & Design Institute Co., Ltd., Kunming, Yunnan 650041, China (corresponding author).

4. Professor, School of Traffic and Transportation Engineering, Central South Univ., Changsha, Hunan 410075, China.

5. Professor, Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Kunming, Yunnan 650050, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000660

Reference35 articles.

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2. SVRGSA: a hybrid learning based model for short‐term traffic flow forecasting

3. Short-term traffic forecasting: An adaptive ST-KNN model that considers spatial heterogeneity

4. Short-Term Traffic Flow Prediction Method for Urban Road Sections Based on Space–Time Analysis and GRU

5. Ding, Q. Y., X. F. Wang, X. Y. Zhang, and Z. Q. Sun. 2011. “Forecasting traffic volume with space-time ARIMA model.” In Advanced materials research, 979–983. Freienbach, Switzerland: Trans Tech Publication.

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