Reconfiguring Vehicles for Drivers with Disability: A Knowledge-Based Decision Support System

Driving a car is pivotal to supporting Persons with Disabilities (PwDs) independence and quality of life. The problem of reconfiguring a vehicle to meet both the PwD’s needs and the (local or supranational) regulations is far from trivial since it requires the identification of the appropriate modifications and adaptations to be installed on the driver’s car. However, PwDs may not be acquainted with the mechanical modification, aids, and devices installed on their cars to allow them to drive, nor may they be aware of the possible configurations available. In the Italian context, this knowledge is strictly regulated by local and European regulations, which—according to the type(s) of impairments a driver has—indicate the possible configurations for the vehicles and the aids and mechanical modifications that need to be implemented. Therefore, to support PwDs in understanding the possible modification(s) their cars could undergo, a novel knowledge-based Decision Support System (DSS) was developed with the support of the Italian National Institute for Insurance against Accidents at Work (INAIL). The DSS exploits ontological engineering to formalize the relevant information on cars’ modifications, PwDs’ impairments, and a rule engine to match candidate drivers with the (sets of) car configurations that can be installed on their vehicles. Thus, the proposed DSS can enable the drivers to acquire more insights on the types and functionalities of the driving aids they will use. It also supports INAIL in administering the “special driving license”.

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Publication Details

Journal
Electronics
Published
2024-10-22
DOI
https://doi.org/10.3390/electronics13214147
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Reconfiguring Vehicles for Drivers with Disability: A Knowledge-Based Decision Support System

Daniele Spoladore, Angelo Davalli, Marco Sacco, Atieh Mahroo
Electronics
Semantic Web and Ontologies
article

Reconfiguring Vehicles for Drivers with Disability: A Knowledge-Based Decision Support System

Daniele Spoladore, Angelo Davalli, Marco Sacco, Atieh Mahroo
article en

Abstract

Driving a car is pivotal to supporting Persons with Disabilities (PwDs) independence and quality of life. The problem of reconfiguring a vehicle to meet both the PwD’s needs and the (local or supranational) regulations is far from trivial since it requires the identification of the appropriate modifications and adaptations to be installed on the driver’s car. However, PwDs may not be acquainted with the mechanical modification, aids, and devices installed on their cars to allow them to drive, nor may they be aware of the possible configurations available. In the Italian context, this knowledge is strictly regulated by local and European regulations, which—according to the type(s) of impairments a driver has—indicate the possible configurations for the vehicles and the aids and mechanical modifications that need to be implemented. Therefore, to support PwDs in understanding the possible modification(s) their cars could undergo, a novel knowledge-based Decision Support System (DSS) was developed with the support of the Italian National Institute for Insurance against Accidents at Work (INAIL). The DSS exploits ontological engineering to formalize the relevant information on cars’ modifications, PwDs’ impairments, and a rule engine to match candidate drivers with the (sets of) car configurations that can be installed on their vehicles. Thus, the proposed DSS can enable the drivers to acquire more insights on the types and functionalities of the driving aids they will use. It also supports INAIL in administering the “special driving license”.

ElectronicsVol. 13(21)
Istituto Nazionale per l'Assicurazione Contro gli Infortuni sul Lavoro (IT), National Research Council (IT), University of Milano-Bicocca (IT)
Istituto Nazionale per l'Assicurazione Contro Gli Infortuni sul Lavoro
Openalex Percentile: Top 84%
Semantic Web and Ontologies
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