Citation

Sarkar SK, Shabab KR, Das PC, Zaki MH. Spat. Inf. Res. 2023; 31(1): 91-99.

Copyright

(Copyright © 2023, Korean Spatial Information Society, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s41324-022-00477-y

PMID

unavailable

Abstract

The objective of the study is to explore and characterize the spatial collision factors for bikeshare crashes using spatial and mathematical modeling. First, the nine most influential components behind the bikeshare crashes in Washington, D.C (179 census tracts) were selected as study variables (i.e., population density, number of bikeshare trips, etc.). Next, a spatial weight matrix was used to quantify the spatial relationships among the study variables with the bikeshare crashes. Finally, three models (i.e., Classic Regression, Spatial Lag, and Spatial Error) were used to investigate the essence of the interaction between these variables and bikeshare crashes. Finally, the spatial collision factors involved in bikeshare crashes were identified. According to model results, two causal factors (i.e., no. of cafe and no. of bikeshare points) significantly influence the bikeshare crashes in the Washington, D.C. area. The findings regarding spatial factors involved in bikeshare crashes can be useful in making optimum decisions regarding planning for bikeshare safety.

Language: en

Keywords

Bikeshare crashes; Safety; Spatial collision factors; Urban mobility