2026-06-28T20:10:12Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/1123212025-08-06T15:44:31Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Barreno, Felipe
author
Romana, Manuel
author
Santos Peñas, Matilde
2024-12-10T12:30:46Z
2024-12-10T12:30:46Z
2022
Barreno, F., Romana, M. G., & Santos, M. (2022). Fuzzy expert system for road type identification and risk assessment of conventional two‐lane roads. Expert Systems, 39(9), e12837.
10.1111/exsy.12837
https://hdl.handle.net/20.500.14352/112321
https://doi.org/10.1111/exsy.12837
This paper first presents a fuzzy expert system to identify and classify conventional two-lane roads based on geometric characteristics. Both fuzzy and neuro-fuzzy techniques have been used. Fuzzy logic has proved suitable to address this problem, since in this case, there is a variability of input information, and classical rules are not suitable to be used due to the uncertainty introduced by some combinations of the variables. Each road's geometric features were measured by sensors in an equipped vehicle, and are subsequently used to classify the roads according to their real condition. The conventional two-lane roads used for this research are located in the Madrid Region, in Spain. This intelligent system may be used to update the road database regarding the assigned type to each conventional road, according to their present features and state. Also, a risk identification system has been developed to assess whether a vehicle is driving on a two-lane road with an inappropriate speed, combining variables such as the former identification model, vehicle type, road longitudinal gradient, the angle covered by each horizontal curve, and the existence or not of an additional traffic lane. A fuzzy risk index is proposed for this approach. This fuzzy model may be useful to detect road sections where safety must be enhanced by revising the speed limit, since less safe situations may arise from travelling at unappropriated speeds.
eng
Attribution-NonCommercial-NoDerivatives 4.0 International
Fuzzy expert system for road type identification and risk assessment of conventional two-lane roads
journal article
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URL
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File
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69acce78462e2933089d4ddf53072097
2381178
application/pdf
Fuzzy_expert_system.pdf