Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models
Joint Authors
Jin, Sheng
Xu, Cheng
Li, Qiangwei
Qu, Zhaowei
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-12
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk.
However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed.
The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN) models for the prediction of free flow speed and crash risk on the separated bicycle path.
Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics) were developed.
459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing.
The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models.
Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics.
The findings could contribute for evaluation, planning, and management of bicycle safety.
American Psychological Association (APA)
Xu, Cheng& Li, Qiangwei& Qu, Zhaowei& Jin, Sheng. 2015. Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073237
Modern Language Association (MLA)
Xu, Cheng…[et al.]. Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073237
American Medical Association (AMA)
Xu, Cheng& Li, Qiangwei& Qu, Zhaowei& Jin, Sheng. Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073237
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073237