Abstract
Abstract. Pole-shaped objects (PSOs) located along a road play key role in road safety and planning. Automation is required for calculating the numbers of trees need to be removed and utility poles need to be relocated during rural road widening. Road-side poles are among the most frequently struck road-side objects during road-side accidents. An automatic method is therefore proposed for detecting PSOs using LiDAR point cloud captured along the roadway using Mobile LiDAR system. The proposed method is tested on the point cloud data of rural road environment in India. Dataset of study area having text file size of 1.22 GB is processed in 13 minutes resulting in completeness of 88.63 % and correctness of 95.12 % in identifying PSOs within 10m of the road boundary. In data of across road coverage of 5m of the road boundary, the completeness of 93.10 % and correctness of 100% are achieved. Poles attached with other objects, tilted poles and the poles occluded by tree branches and shrubs are detected by the proposed method.
Highlights
Mobile LiDAR system (MLS) is becoming a popular choice among the government and private agencies, working in the field of roadway planning, designing and its management
Grid size is selected less than the selected threshold value, non-pole-shaped objects (NPSOs), i.e., building columns are falsely classified as PSOs
An automatic method is proposed for extraction of PSOs from MLS data
Summary
Mobile LiDAR system (MLS) is becoming a popular choice among the government and private agencies, working in the field of roadway planning, designing and its management. Width of formation or roadway width of 7.5m suggested by Indian Road Congress is used in the rural roadway planning and its management (Mathew and Rao, 2006) This coverage includes planar and linear non-ground objects, most commonly road-side buildings, low and high vegetation, utility poles, other pole-shaped objects and boundary walls. The pole-shaped objects (PSOs) mainly utility poles and road side planted trees are located nearby road boundary in the rural road environment. They are responsible for most of the roadside accidents and categorized as two major fatal roadside hazards. A total of 10.7% of rural pole accidents resulted in severe to fatal injuries versus only 5.4% for urban pole accidents
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