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ISPRS Int. J. Geo-Inf. 2019, 8(2), 69; https://doi.org/10.3390/ijgi8020069

Estimating the Available Sight Distance in the Urban Environment by GIS and Numerical Computing Codes

Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering (DIATI), 24, corso Duca degli Abruzzi, 10129 Torino, Italy
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Received: 13 December 2018 / Revised: 9 January 2019 / Accepted: 27 January 2019 / Published: 30 January 2019
(This article belongs to the Special Issue GIS for Safety & Security Management)
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Abstract

The available sight distance (ASD) is that part of the roadway ahead which is visible to the driver, and should be of sufficient length to allow a vehicle traveling at the designated speed to stop before reaching a stationary object in its path. It is fundamental in assessing road safety of a project or on an existing road section. Unfortunately, an accurate estimation of the available sight distance is still an issue on existing roads, above all due to the lack of information regarding the as-built condition of the infrastructure. Today, the geomatics field already offers different solutions for collecting 3D information about environments at different scales, integrating multiple sensors, but the main issue regarding existing mobile mapping systems (MMSs) is their high cost. The first part of this research focused on the use of a low-cost MMS as an alternative for obtaining 3D information about infrastructure. The obtained model can be exploited as input data of specific algorithms, both on a GIS platform and in a numerical computing environment to estimate ASD on a typical urban road. The aim of the investigation was to compare the performances of the two approaches used to evaluate the ASD, capturing the complex morphology of the urban environment. View Full-Text
Keywords: road safety assessment; available sight distance; urban roads; mobile mapping system (MMS); low cost MMS; digital surface model; 3D model; GIS road safety assessment; available sight distance; urban roads; mobile mapping system (MMS); low cost MMS; digital surface model; 3D model; GIS
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Bassani, M.; Grasso, N.; Piras, M.; Catani, L. Estimating the Available Sight Distance in the Urban Environment by GIS and Numerical Computing Codes. ISPRS Int. J. Geo-Inf. 2019, 8, 69.

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