Enhancing Overtaking Safety with Mobile LiDAR Systems: Dynamic Analysis of Road Visibility

This study presents a methodology to automatically assess visibility distance on secondary roads using mobile LiDAR systems. The method evaluates both braking and overtaking visibility distances based on the 3D geometry of the road, applying a dynamic analysis through a series of parametrised quadrangular pyramids that simulate the driver’s field of view. Road segments are classified into three risk levels, low, medium, and high, according to the feasibility of stopping or overtaking safely. The methodology was validated on three secondary roads in Spain, achieving an average accuracy of 92.7% when compared to existing road signage. These results demonstrate the method’s potential to improve road safety through continuous, data-driven visibility monitoring. Its application supports advanced driver assistance systems and offers road authorities a reliable tool for proactive risk assessment and road infrastructure planning.

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Publication Details

Journal
Remote Sensing
Published
2025-08-25
DOI
https://doi.org/10.3390/rs17172948
Citations
2
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.60
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article

Enhancing Overtaking Safety with Mobile LiDAR Systems: Dynamic Analysis of Road Visibility

Mariano González-de-Soto, Susana Del Pozo, José Antonio Martín-Jiménez, Diego González‐Aguilera et al.
2 citations
Remote Sensing
Remote Sensing and LiDAR Applications
1.60
article

Enhancing Overtaking Safety with Mobile LiDAR Systems: Dynamic Analysis of Road Visibility

Mariano González-de-Soto, Susana Del Pozo, José Antonio Martín-Jiménez, Diego González‐Aguilera, Pablo Rodríguez‐Gonzálvez, Diego Guerrero
article en
2 citations

Abstract

This study presents a methodology to automatically assess visibility distance on secondary roads using mobile LiDAR systems. The method evaluates both braking and overtaking visibility distances based on the 3D geometry of the road, applying a dynamic analysis through a series of parametrised quadrangular pyramids that simulate the driver’s field of view. Road segments are classified into three risk levels, low, medium, and high, according to the feasibility of stopping or overtaking safely. The methodology was validated on three secondary roads in Spain, achieving an average accuracy of 92.7% when compared to existing road signage. These results demonstrate the method’s potential to improve road safety through continuous, data-driven visibility monitoring. Its application supports advanced driver assistance systems and offers road authorities a reliable tool for proactive risk assessment and road infrastructure planning.

Remote SensingVol. 17(17)
Universidad de Salamanca (ES), Catholic University of Ávila (ES), Universidad de León (ES)
Openalex Percentile: Top 16%
Remote Sensing and LiDAR Applications
1.60
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