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

Sai Sneha Channamallu, Deema Almaskati, Sharareh Kermanshachi, Apurva Pamidimukkala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Safety is the predominant concern in the advancement of automated vehicles (AVs); therefore, extensive real-world testing is underway to ensure their secure operation. Despite the widespread belief that they will decrease the frequency of accidents, there remains uncertainty about their impact on the severity of crashes in which they are involved. The primary objective of this study is to use the bagging classifier technique to predict the likelihood of injuries in accidents involving AVs. This was accomplished by conducting an in-depth examination of a wide range of independent variables and an analysis of injuries sustained in crash incidents involving AVs from 2014 to July 2023. The bagging classifier model showed notable effectiveness, achieving a balanced accuracy of 0.59, along with high precision and recall values of 0.94 and 0.97, respectively. These metrics indicate the model’s strong capability for accurately identifying severe crash outcomes and minimizing false positives. The precision-recall curve and a modified F1 score of 2.39 further endorse the model’s performance, particularly highlighting its efficiency in handling the class imbalance present in the dataset. The validation and learning curves underscore the model’s optimal complexity, displaying its proficiency in identifying essential patterns without succumbing to overfitting. Collectively, these metrics underscore the model’s success in predicting injury outcomes in AV crashes with a high level of accuracy. This study contributes to the literature on AV safety by providing valuable insights for manufacturers and policymakers that will enable them to develop effective safety features and strategies, thereby enhancing traffic safety.

Original languageEnglish (US)
Title of host publicationInternational Conference on Transportation and Development 2024
Subtitle of host publicationTransportation Safety and Emerging Technologies - Selected Papers from the International Conference on Transportation and Development 2024
EditorsHeng Wei
PublisherAmerican Society of Civil Engineers (ASCE)
Pages538-549
Number of pages12
ISBN (Electronic)9780784485514
StatePublished - 2024
EventInternational Conference on Transportation and Development 2024: Transportation Safety and Emerging Technologies, ICTD 2024 - Atlanta, United States
Duration: Jun 15 2024Jun 18 2024

Publication series

NameInternational Conference on Transportation and Development 2024: Transportation Safety and Emerging Technologies - Selected Papers from the International Conference on Transportation and Development 2024

Conference

ConferenceInternational Conference on Transportation and Development 2024: Transportation Safety and Emerging Technologies, ICTD 2024
Country/TerritoryUnited States
CityAtlanta
Period6/15/246/18/24

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanics of Materials
  • Safety, Risk, Reliability and Quality
  • Geography, Planning and Development
  • Transportation

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