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February 5, 2026Journal of Ambient Intelligence and Humanized Computing

Pedestrian trajectory and intention prediction: a comprehensive review of models, datasets, and challenges

Mahmoud Taha Ahmed B. Zaky H. Yamaguchi Ahmed Fares

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Key Points

Pedestrian intention recognition models show promise in enhancing safety measures and urban planning.
Key findings indicate a significant reliance on machine learning algorithms across varied datasets.
Observational analysis covers various approaches, identifying gaps in model evaluation and real-world applications.
Challenges in integrating different datasets underscore the need for standardized metrics and robust methodologies.

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Implication

Comprehensive review highlights challenges in pedestrian trajectory and intention prediction for improved safety.

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Cite This Study

Taha et al. (2026) studied this question.

synapsesocial.com/papers/69a767e8badf0bb9e87e2db1 https://doi.org/10.1007/s12652-026-05042-1

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