Empirical and Synthetic Datasets for Estimating Vehicular Stopped Delay at Isolated Signalized Intersections in Amman, Jordan
Description
This dataset contains information on vehicular stopped delay at signalized intersections collected from eight isolated intersections in Amman, Jordan. The dataset includes 322 data points, each representing measurements taken during 15-45 minute intervals on weekdays outside of peak hours. Additionally, the dataset also includes ten synthetic datasets generated based on the original data providing additional data for training and evaluation purposes. The dataset can be used for developing and evaluating machine learning models or other analytical techniques for estimating stopped delay at signalized intersections, a critical parameter for assessing intersection performance and level of service. Citation: Alatoom YI, Al-Hamdan AB. A comparative study between different machine learning algorithms for estimating the vehicular delay at signalized intersections. J Soft Comput Civ Eng 2025;9(1):123–158. https://doi.org/10.22115/scce.2024.418800.1725 Paper URL: https://www.jsoftcivil.com/article_196451.html
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Institutions
- Al-Balqa Applied UniversityBalqa, Salt