Predicting Bicycle-Involved Crashes in the SCAG Region: A Machine Learning Analysis Using HSIS Data from California State-Reference-Cited by-同舟云学术

Predicting Bicycle-Involved Crashes in the SCAG Region: A Machine Learning Analysis Using HSIS Data from California State

Published:2024-06-13 Issue: Volume:51 Page:305-314
ISSN:
Container-title:International Conference on Transportation and Development 2024
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Author:

Javid Ramina¹²³⁴,Sadeghvaziri Eazaz¹²³⁴,Mokhtarimousavi Seyedmirsajad¹²³⁴,Omidi Hananeh¹²³⁴

Affiliation:

1. Ph.D. Candidate, Dept. of Transportation and Urban Infrastructure, Morgan State Univ.

2. Assistant Professor, Dept. of Environmental and Civil Engineering, School of Engineering, Mercer Univ., Macon, GA.

3. Postdoctoral Research Associate, Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL.

4. Ph.D. Student, Graduate Researcher, and Teaching Assistant, Dept. of Geography and Environmental Sustainability, Sarkeys Energy Center, Univ. of Oklahoma, Norman, OK.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485514.027

Reference26 articles.

1. A Speed Limit Compliance Model for Dynamic Speed Display Sign;Ardeshiri A.;Journal of Safety Research,2014

2. A Novel Deep Supervised Learning-Based Approach for Intrusion Detection in IoT Systems;Baniasadi S.;Sensors,2022

3. BayesFusion. 2022. Using GeNIe > Bayesian Networks > Sensitivity Analysis in Bayesian Networks. 2022. https://support.bayesfusion.com/docs/GeNIe/bn_sensitivitybn.html.

4. CDC. 2023. “Bicycle Safety | Transportation Safety | Injury Center | CDC.” 2023. https://www.cdc.gov/transportationsafety/bicycle/index.html.

5. Built Environment Factors in Explaining the Automobile-Involved Bicycle Crash Frequencies: A Spatial Statistic Approach;Chen P.;Safety Science,2015