Enhancing AV Safety: A Bagging Classifier Approach for Predicting Crash Outcomes-Reference-Cited by-同舟云学术

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Enhancing AV Safety: A Bagging Classifier Approach for Predicting Crash Outcomes

Published:2024-06-13 Issue: Volume:135 Page:538-549
ISSN:
Container-title:International Conference on Transportation and Development 2024
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Author:

Channamallu Sai Sneha¹¹²³,Almaskati Deema¹¹²³,Kermanshachi Sharareh¹¹²³,Pamidimukkala Apurva¹¹²³

Affiliation:

1. Ph.D. Student, Dept. of Civil Engineering, Univ. of Texas at Arlington, Arlington, TX.

2. Associate Vice Chancellor and Associate Dean of Research, Pennsylvania State Univ., State College, PA.

3. Assistant Professor of Research, Dept. of Civil Engineering, Univ. of Texas at Arlington, Arlington, TX.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485514.047

Reference30 articles.

1. Exploratory analysis of automated vehicle crashes in California: A text analytics & hierarchical Bayesian heterogeneity-based approach;Boggs A. M.;Accident Analysis & Prevention,2020

2. Impact of Autonomous Vehicles on Traffic Crashes in Comparison with Conventional Vehicles

3. Automated vehicle collisions in California: Applying Bayesian latent class model;Das S.;IATSS research,2020

4. Etminani-Ghasrodashti, R., Patel, R., Kermanshachi, S., Rosenberger, J., and Foss, A. 2022a. Exploring Factors Affecting Willingness to Ride Shared Autonomous Vehicles. In Proceedings of Transportation Research Board 101 Annual Conference.

5. Modeling Users’ Adoption of Shared Autonomous Vehicles Employing Actual Ridership Experiences

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