Shaded Route Planning Using Active Segmentation and Identification of Satellite Images
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Abstract (arXiv)
Heatwaves pose significant health risks, particularly due to prolonged exposure to high summer temperatures. Vulnerable groups, especially pedestrians and cyclists on sun-exposed sidewalks, motivate the development of a route planning method that incorporates somatosensory temperature effects through shade ratio consideration. This paper is the first to introduce a pipeline that utilizes segmentation foundation models to extract shaded areas from high-resolution satellite images. These areas are then integrated into a multi-layered road map, enabling users to customize routes based on a balance between distance and shade exposure, thereby enhancing comfort and health during outdoor activities. Specifically, we construct a graph-based representation of the road map, where links indicate connectivity and are updated with shade ratio data for dynamic route planning. This system is already implemented online, with a video demonstration, and will be specifically adapted to assist travelers during the 2024 Olympic Games in Paris.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 25 references that are in the map. First posted on arXiv 18 Jul 2024.
Builds on
6 of 25 references.
References · 6
- 2023Segment Anythingcited by 8,234
- 2023Segment Anything in Non-Euclidean Domains: Challenges and Opportunitiescited by 16
- 2023Reinforcement Learning Approaches for Traffic Signal Control under Missing Datacited by 13
- 2021Learning to Simulate on Sparse Trajectory Datacited by 6
- 2023Uncertainty-aware Traffic Prediction under Missing Datacited by 5
- 2024MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Datacited by 3
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.