TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads

In Bangladesh, people sadly are not very much concerned about traffic rules. This study focuses on traffic flow patterns at four locations in Dhaka: Shapla Chattar, Arambag, Bashabo and Abul Hotel. Foot over bridges were used to collect video data, which captured single-lane and double-lane traffic conditions involving different types of vehicles and irregular pedestrian movement. The dataset comprises of 23,678 images extracted from the videos, taken at five different time periods on weekdays. These photos were later annotated using roboflow. This dataset provides a unique view on traffic situations in Dhaka, Bangladesh, by presenting unstructured traffic environments in different conditions at different road junctions. Monitoring vehicle fitness, examining pedestrian behaviour, and measuring vehicle flow in varying environmental contexts (e.g., day, dusk, night, rain) are all possible applications. Researchers can experiment with different machine learning techniques in such traffic environments.

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Publication Details

Journal
Data in Brief
Published
2025-02-18
DOI
https://doi.org/10.1016/j.dib.2025.111398
Citations
1
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
1.28
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article

TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads

Saleh Masum, Maheen Islam, Md. Shahjalal, Abdullahi Chowdhury et al.
1 citations
Data in Brief
Video Surveillance and Tracking Methods
1.28
article

TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads

Saleh Masum, Maheen Islam, Md. Shahjalal, Abdullahi Chowdhury, Mohammad Rifat Ahmmad Rashid, Md Sawkat Ali, Aritra Das, Kazi Ferdous Hasan, Mohammad Manzurul Islam, Md. Rakibul Hasan, Karib Shams
article en
1 citations

Abstract

In Bangladesh, people sadly are not very much concerned about traffic rules. This study focuses on traffic flow patterns at four locations in Dhaka: Shapla Chattar, Arambag, Bashabo and Abul Hotel. Foot over bridges were used to collect video data, which captured single-lane and double-lane traffic conditions involving different types of vehicles and irregular pedestrian movement. The dataset comprises of 23,678 images extracted from the videos, taken at five different time periods on weekdays. These photos were later annotated using roboflow. This dataset provides a unique view on traffic situations in Dhaka, Bangladesh, by presenting unstructured traffic environments in different conditions at different road junctions. Monitoring vehicle fitness, examining pedestrian behaviour, and measuring vehicle flow in varying environmental contexts (e.g., day, dusk, night, rain) are all possible applications. Researchers can experiment with different machine learning techniques in such traffic environments.

Data in BriefVol. 59
East West University (BD), University of Rajshahi (BD)
Sustainable cities and communities
Openalex Percentile: Top 23%
Video Surveillance and Tracking Methods
1.28
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TFP-BD: An image dataset for Traffic Flow and Pedestrian movement analysis on Bangladeshi urban roads — Saleh Masum, Maheen Islam, et al. · Data in Brief (2025) | TGRS Research Map | TGRS