A Micro-Scale Walkability Metric for Pleasant Pedestrian Route Planning

Engineering notes

Key topics: autonomous driving, route planning, perception, planning. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Abstract. This paper proposes a micro-scale walkability metric based on harmonised indicators that supports pedestrian route planning, which prioritises pleasant environments alongside distance efficiency. The employed method quantifies street segments and crossings using geospatial indicators, including pavement width, slope, shade, adjacency to traffic, park context, and crossing type and width. Indicator values are transformed into percentile ranks to harmonise heterogeneous inputs and aggregated into a single edge-level walkability score on a 0-1 scale. The score is integrated into a routing cost function that reduces edge costs with higher walkability, favouring calmer, greener, and wider links while bounding detours relative to the shortest path. The method also accommodates the incorporation of street-level perceptions through a structured survey instrument and a confidence-weighted fusion scheme. The results show various spatial patterns. Central areas and park-adjacent segments exhibit higher scores, while steep, narrow, and traffic-exposed links score lower, and several suburban and foothill districts display reduced walkability. The comparison with a distance-only baseline shows selection of quieter alignments with modest length increases, indicating potential gains in perceived pleasantness.

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