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All Journal Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Forum Geografi Journal of Civil Engineering Jurnal Aplikasi Teknik Sipil G-Tech : Jurnal Teknologi Terapan
Aji, Pujo
Institut Teknologi Sepuluh Nopember
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

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YOLO-Based Pedestrian Trajectory Analysis for Zebra Crossing Safety and Suitability Evaluation Using UAV Data Herjuna, Arde Dewantara; Kartika, Anak Agung Gde; Aji, Pujo
G-Tech: Jurnal Teknologi Terapan Vol 10 No 1 (2026): G-Tech, Vol. 10 No. 1 January 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i1.8852

Abstract

Pedestrian crossing facilities in urban areas are often positioned without adequate consideration of actual movement patterns, leading to low utilization rates, widespread informal crossings, and increased pedestrian-vehicle conflict risks. Traditional manual observation methods for assessing crossing behavior are time-consuming, subjective, and unable to capture continuous spatial-temporal movement dynamics at scale. This study aims to develop and evaluate an automated framework for extracting pedestrian trajectories and assessing the alignment between pedestrian desire lines and existing zebra crossing infrastructure. The methodology integrates YOLO11 fine-tuned object detection with ByteTrack multi-object tracking to process unmanned aerial vehicle (UAV) video data collected at an urban intersection in Surabaya, Indonesia. Pedestrian-vehicle conflict severity was quantified using Time-to-Collision (TTC)-based surrogate safety indicators, including Time Exposed to Time-to-Collision (TET) and Time Integrated Time-to-Collision (TIT). The results reveal substantial heterogeneity in crossing behavior, with distinct spatial clustering of informal crossing hotspots located away from the designated zebra crossing. Asymmetric yet bidirectional pedestrian demand patterns were observed across the study area. Based on trajectory-derived evidence, the study recommends strategic relocation of the zebra crossing approximately 135 meters south to better accommodate natural pedestrian flow and reduce vehicular traffic exposure. These findings demonstrate that deep learning-based trajectory analysis offers a practical, objective, and scalable approach for evidence-based pedestrian infrastructure planning, particularly applicable to rapidly urbanizing contexts in developing countries where conventional assessment resources are limited.
Co-Authors . Faimun AA Sudharmawan, AA Alrasyid, Harun Amalia, Rizky Angga Bayu Christianto Bambang Piscesa Bangun Muljo Sukojo, Bangun Muljo Budi, Firman Endah Wahyuni Herjuna, Arde Dewantara Irawan, Candra Jaelani, Lalu Muhamad Januarti Jaya Ekaputri Julio Cezar Haryantho Muhammad Taufik Muhsi Nikmatus Solikha Rofiq, Muhammad Suluch, Munarus Teddy Yustiono Triwulan Triwulan Yeni Rochsianawati Yu Chen-Ou Yusronia Putri