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Updated: Sep 6, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Modeling infrastructure determinants, spatial patterns, and temporal trends of pedestrian fatalities along a
Mekuanint Getnet1, Girish Agrawal1, Geetam Tiwari1
1Transportation Research and Injury Prevention Centre (TRIP Centre), Indian Institute of Technology Delhi, New Delhi, India.
Objective:
Pedestrian fatality risks in low- and middle-income countries remain high due to mixed traffic conditions, roadside settlement activities, and inadequate pedestrian infrastructure. This study examines the associations between micro-level roadside infrastructure characteristics and pedestrian fatalities and identifies the spatial patterns and temporal trends of pedestrian fatalities along a high-speed multilane highway in India.
Methods:
This study analyzed 1,687 pedestrian fatalities recorded between 2017 and 2022 using police-reported crash data along National Highway 44 in Haryana, India. Temporal heatmaps were used to identify high-risk periods, while kernel density estimation (KDE) was used to visualize the spatial concentration of pedestrian fatalities. A negative binomial regression model was employed to examine the associations between roadside infrastructure, land-use characteristics, and pedestrian fatalities.
Results:
The model results indicated that the presence of earthen shoulders, service roads, and street lighting was associated with lower pedestrian fatalities, whereas junctions and bus stop locations were associated with higher fatalities. Higher concentrations of pedestrian fatalities were observed in commercial and mixed-use areas. Temporal analysis further showed that approximately 32% of pedestrian fatalities occurred during evening peak hours (18:00-21:00), with higher fatalities during weekends and nighttime periods.
Conclusions:
The findings highlight important associations between roadside infrastructure, land-use activity, and pedestrian fatality patterns along multilane highways. These results can support the identification of high-risk locations and guide targeted infrastructure improvements, including safer bus stop placement, improved lighting, pedestrian crossing facilities, and junction management. The findings can also assist planners and policymakers in developing effective strategies to improve pedestrian safety in India and similar low- and middle-income countries.
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