Research on the influencing factors of elderly pedestrian traffic accidents considering the built environment-Reference-Cited by-同舟云学术

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Research on the influencing factors of elderly pedestrian traffic accidents considering the built environment

Published:2023-01-15 Issue:1 Volume:11 Page:44-63
ISSN:2187-3666
Container-title:International Review for Spatial Planning and Sustainable Development
language:en
Short-container-title:IRSPSD International

Author:

Chen Yanyan¹^ORCID,Yuan Rui²^ORCID,Wei Jiaomin¹^ORCID,Li Sichun¹^ORCID

Affiliation:

1. Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology

2. Transport planning and Research Institute, Ministry of Transport of the People's Republic of China

Publisher

International Community of Spatial Planning and Sustainable Development

Subject

Management, Monitoring, Policy and Law,Urban Studies,Geography, Planning and Development

Link

https://www.jstage.jst.go.jp/article/irspsd/11/1/11_4/_pdf

Reference31 articles.

1. Bowman, A. W. (1984). "An alternative method of cross-validation for the smoothing of density estimates". Biometrika, 71(2), 353–360. https://doi.org/https://doi.org/10.1093/biomet/71.2.353

2. Cai, Q., Abdel-Aty, M., et al. (2018). "Developing a grouped random parameters multivariate spatial model to explore zonal effects for segment and intersection crash modeling". Analytic Methods in Accident Research, 19, 1–15. https://doi.org/https://doi.org/10.1016/j.amar.2018.05.001

3. Chen, Y., Ma, J., et al. (2019). "Analyzing Pedestrian Fatality Risk in Accidents at Mid-Blocks". Journal of Transportation Technologies, 9(2), 171–192. https://doi.org/https://doi.org/10.4236/jtts.2019.92011

4. Chiou, Y.-C., Fu, C., et al. (2014). "Incorporating spatial dependence in simultaneously modeling crash frequency and severity". Analytic Methods in Accident Research, 2, 1–11. https://doi.org/https://doi.org/10.1016/j.amar.2013.12.001

5. Cleveland, W. S. (1979). "Robust Locally Weighted Regression and Smoothing Scatterplots. Journal of the American Statistical Association", 74(368), 829–836. https://doi.org/https://doi.org/10.1080/01621459.1979.10481038

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