Spatiotemporal Comparative Analysis of Pre/Post Covid-19 Pedestrian Crash Incidences in Chicago

Introduction: Despite major transformational effects observed in vehicle traffic crashes due to COVID-19, there is little comprehensive research studying the shifts in trends of pedestrian crashes after COVID-19. This study aims at determining changes in spatiotemporal trends of pedestrian crashes taking two time periods: 2017 to 2020 (pre-COVID-19) and 2020 to 2023 (post-COVID-19). Method: The dataset for this study is taken from the City of Chicago data portal. The temporal analysis is conducted using pedestrian crash frequencies of data such as year, month, day, and severity of the incident, from the dataset. Hotspot analysis using the Getis Ord Gi* statistic is used for the spatial analysis of the pedestrian crashes to determine concentrated spatial clusters on ArcGIS after assigning weights based on a defined Severity Index to the pedestrian crashes. Some intersections from the hotspot TAZs obtained were then visited to determine pedestrian facility faults at the intersections. Results: The temporal analysis showed that overall pedestrian crashes increased from 2017 to 2020, suddenly dropped after the COVID-19 lockdown, and resumed growing from 2020 to 2023 after the initial plunge. Despite the decrease in overall pedestrian crashes, fatal crashes increased from 78 to 114 after COVID-19. The spatial analysis showed that hotspots in the Loop and Near North Side disappeared in the year after the lockdown, whereas hotspots in the West Side and South Side increased. Discussion: This study shows the severe effects of COVID-19 on pedestrian crash trends and pedestrian behavior, along with effects of declining pedestrian facility conditions in low income neighborhoods, mainly consisting of Black and Hispanic communities. This study may benefit further research in the field, and also encourage transportation engineers and policymakers to address disparities in transportation planning for better and more sensitive planning to reduce overall pedestrian crashes.