Dataset of Jordanian Road Traffic Accidents Reports

The dataset utilized for this research consists of data on traffic accidents in Jordan, sourced from the JO-Traffic-Accidents-Dataset (JO-TAD). This dataset was procured from the Central Traffic Department, Public Security Directorate, Amman-Jordan. JO-TAD contains 73,095 accident reports recorded i...

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1. Verfasser: Mustafa, Dheya
Format: Dataset
Sprache:eng
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Zusammenfassung:The dataset utilized for this research consists of data on traffic accidents in Jordan, sourced from the JO-Traffic-Accidents-Dataset (JO-TAD). This dataset was procured from the Central Traffic Department, Public Security Directorate, Amman-Jordan. JO-TAD contains 73,095 accident reports recorded in 2018, specifically focusing on incidents transpiring in January, June, and September. These months correspond to three distinct seasons: winter, summer, and fall, respectively. The Jordanian Road Traffic Accidents reports Dataset is publicly available as an Excel file (JO_traffic_accidents_dataset.xlsx) and a CSV file (Accident_raw_data_En.csv) . The JO_traffic_accidents_dataset.xlsx file includes several individual Excel sheets that contain: (1) the raw primary data for traffic accident reports, (2) the encoded dataset, and (3) the associated features encoding key. As per the JO-Traffic-Accidents-Dataset (JO-TAD), it exclusively encompasses records pertaining to drivers and lacks any details regarding passengers involved in the accidents. The raw dataset comprises various labels, providing information about the accidents. This includes accident type, date, injury severity (ranging from simple to medium, severe, and fatal), road lanes, road surface description, road type, road properties, driver license type, travel speed, light condition, weather condition, driver errors, city, vehicle type, vehicle country of origin, number of cars involved, driver age, and driver sex. This extensive dataset can be used by researchers and policymakers to explore accident mortality patterns at various geographical and time scales, as well as to assess the success of measures aimed at reducing road fatalities.
DOI:10.17632/r6db558376.1