Abstract
Abstract. Maintaining high visibility of traffic signs is very important for traffic safety. Manual inspection and removal of occlusion in front of traffic signs is one of the daily tasks of the traffic management department. This paper presents a method that can automatically detect the occlusion and continuously quantitative estimate the visibility of traffic sign cover all the road surface based on Mobile Laser Scanning (MLS) systems. The concept of traffic sign’s visibility field is proposed in this paper. One of important innovation of this paper is that we use retinal imaging area to evaluate the visibility of a traffic sign. And this makes our method is in line with human vision. To validate the reasonable and accuracy of our method, we use the 2D and 3D registration technology to observe the consistence of the occlusion ratio in point clouds with it in photo. Experiment of implementation on large scale traffic environments show that our method is feasible and efficient.
Highlights
Traffic signs are often occluded by growing trees, road facilities, and buildings etc
We evaluate visibility of a traffic sign at a viewpoint in 3D point clouds according to human retinal imaging principle
We presented a traffic sign visibility evaluation model, proposed and automatic algorithm to detect occlusion and estimate visibility of a traffic sign, introduced a conception of visibility field
Summary
Traffic signs are often occluded by growing trees, road facilities, and buildings etc. As far as our best acknowledgment, there are not exist an automatic method to detect the occlusion and estimate the visibility of traffic sign cover all the road surface within a sight distance. How to detect the occlusion and evaluate the visibility of traffic signs accurately and efficiently in a large scale traffic environment is a challenging problem. (2) Traffic sign surroundings geometric factors, such as road facilities, buildings, etc. Simulator based methods (Lyu et al, 2017, Motamedi et al, 2017, Li , Zhang, 2017) evaluate the visibility or recognizability by observing the simulated traffic environment in the screen.
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