Investigation of Young Pedestrian Crashes in School Districts of New Jersey Using Machine Learning Models

Md Arifuzzaman Nayeem, Ahmed Sajid Hasan, Mohammad Jalayer

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

1 Scopus citations


Approximately half of all traffic-related casualties across the globe involve vulnerable road users such as pedestrians, bikers, and bicyclists. The National Highway Traffic Safety Administration (NHTSA) reported that in the United States, crashes involving school buses resulted in a total of 111 fatalities in 2019. Specifically, almost one-sixth of the pedestrians involved in motor vehicle crashes in New Jersey over the last five years (2016-2020) were less than 18 years of age. Although various initiatives have been implemented to boost the safety of school children, crashes involving school children are still worrisome, leading to an emerging national issue. Finding unknown patterns in a complex, multivariate crash data set is often difficult for supervised algorithms, as they rely on a limited number of predetermined premises. Unlike supervised algorithms, unsupervised algorithms can find the relevant inherent trends between the variables and crash severity. Thus, to figure out the causes of these young pedestrian crashes, this study obtained and investigated five years of crash data sets (2014-2019) in New Jersey school districts using a multilayer artificial neural network. Shapley Additive Explanation of SHAP values of the top contributing factors is further performed to assess the impact of those factors on the crash severity. The analysis will help interpret the potential causes of the crashes, suggest countermeasures, and create awareness in combating pedestrian crashes in school districts.

Original languageEnglish (US)
Title of host publicationTransportation Planning, Operations, and Transit
EditorsHeng Wei
PublisherAmerican Society of Civil Engineers (ASCE)
Number of pages15
ISBN (Electronic)9780784484883
StatePublished - 2023
Externally publishedYes
EventInternational Conference on Transportation and Development 2023, ICTD 2023 - Austin, United States
Duration: Jun 14 2023Jun 17 2023

Publication series

NameInternational Conference on Transportation and Development 2023: Transportation Safety and Emerging Technologies - Selected Papers from the International Conference on Transportation and Development 2023


ConferenceInternational Conference on Transportation and Development 2023, ICTD 2023
Country/TerritoryUnited States

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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