|Table of Contents|

[1] Cheng Juan, Chen Xianhua,. Travel time prediction model of freewaybased on gradient boosting decision tree [J]. Journal of Southeast University (English Edition), 2019, 35 (3): 393-398. [doi:10.3969/j.issn.1003-7985.2019.03.017]
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Travel time prediction model of freewaybased on gradient boosting decision tree()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
35
Issue:
2019 3
Page:
393-398
Research Field:
Traffic and Transportation Engineering
Publishing date:
2019-09-30

Info

Title:
Travel time prediction model of freewaybased on gradient boosting decision tree
Author(s):
Cheng Juan;  Chen Xianhua
School of Transportation, Southeast University, Nanjing 211189, China
Keywords:
gradient boosting decision tree(GBDT);  travel time prediction;  freeway;  traffic state parameter
PACS:
U491.2
DOI:
10.3969/j.issn.1003-7985.2019.03.017
Abstract:
To investigate the travel time prediction method of the freeway, a model based on the gradient boosting decision tree(GBDT)is proposed. Eleven variables(namely, travel time in current period Ti, traffic flow in current period Qi, speed in current period Vi, density in current period Ki, the number of vehicles in current period Ni, occupancy in current period Ri, traffic state parameter in current period Xi, travel time in previous time period Ti-1, etc.)are selected to predict the travel time for 10 min ahead in the proposed model. Data obtained from VISSIM simulation is used to train and test the model. The results demonstrate that the prediction error of the GBDT model is smaller than those of the back propagation(BP)neural network model and the support vector machine(SVM)model. Travel time in current period Ti is the most important variable among all variables in the GBDT model. The GBDT model can produce more accurate prediction results and mine the hidden nonlinear relationships deeply between variables and the predicted travel time.

References:

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Memo

Memo:
Biographies: Cheng Juan(1983—), female, Ph.D. candidate; Chen Xianhua(corresponding author), male, doctor, professor, chenxh@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.51478114, 51778136).
Citation: Cheng Juan, Chen Xianhua. Travel time prediction model of freeway based on gradient boosting decision tree[J].Journal of Southeast University(English Edition), 2019, 35(3):393-398.DOI:10.3969/j.issn.1003-7985.2019.03.017.
Last Update: 2019-09-20