Ontology Based Road Traffic Management

Bermejo, A. J.; Villadangos, J.; Astráin, José Javier; Córdoba, Alberto

doi:10.1007/978-3-642-32524-3_14

Cited by 22 publications

(12 citation statements)

References 4 publications

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“…Regarding the use of ontologies with sensors information, we can mention the work in [6]. In this work, the authors propose an ontology for traffic management that combines both traffic concepts and general sensor ontology A3ME [7].…”

Section: Related Workmentioning

confidence: 99%

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Fernández

Ito

2017

IEICE Trans. Inf. & Syst.

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SUMMARYIntelligent transportation systems (ITS) are a set of technological solutions used to improve the performance and safety of road transportation. Since one of the most important information sources on ITS are sensors, the integration and sharing the sensor data become a big challenging problem in the application of sensor networks to these systems. In order to make full use of the sensor data, is crucial to convert the sensor data into semantic data, which can be understood by computers. In this work, we propose to use the SSN ontology to manage the sensor information in an intelligent transportation architecture. The system was tested in a traffic light settings application, allowing to predict and avoid traffic accidents, and also for the routing optimization.

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Section: Related Workmentioning

confidence: 99%

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Fernández

Ito

2017

IEICE Trans. Inf. & Syst.

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“…In [ 34 ], the authors propose an ontology for traffic management that combines both traffic concepts and general sensor ontology A3ME [ 35 ]. The added concepts are specializations of position, distance and acceleration sensor classes, and the different actions that take place in the car motions.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

Fernández

Hadfi

Ito

et al. 2016

Sensors

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Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

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“…where is the wedge angle, , , and ∓ are defined in [13], and 0, are the reflection coefficients for the appropriate polarization for the 0 face or face, respectively. The complete approach has been explained in detail in [15], and it has been used successfully in different complex indoor environments [16][17][18][19][20][21][22].…”

Section: D Raymentioning

confidence: 99%

Performance Analysis of ZigBee Wireless Networks for AAL through Hybrid Ray Launching and Collaborative Filtering

et al. 2016

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This paper presents a novel hybrid simulation method based on the combination of an in-house developed 3D ray launching algorithm and a collaborative filtering (CF) technique, which will be used to analyze the performance of ZigBee-based wireless sensor networks (WSNs) to enable ambient assisted living (AAL). The combination of Low Definition results obtained by means of a deterministic ray launching method and the application of a CF technique leads to a drastic reduction of the time and computational cost required to obtain accurate simulation results. The paper also reports that this kind of AAL indoor complex scenario with multiple wireless devices needs a thorough and personalized radioplanning analysis as radiopropagation has a strong dependence on the network topology and the specific morphology of the scenario. The wireless channel analysis performed by our hybrid method provides valuable insight into network design phases of complex wireless systems, typical in AAL-oriented environments. Thus, it results in optimizing network deployment, reducing overall interference levels, and increasing the overall system performance in terms of cost reduction, transmission rates, and energy efficiency.

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Ontology Based Road Traffic Management

Cited by 22 publications

References 4 publications

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Semantic Integration of Sensor Data with SSN Ontology in a Multi-Agent Architecture for Intelligent Transportation Systems

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

Performance Analysis of ZigBee Wireless Networks for AAL through Hybrid Ray Launching and Collaborative Filtering

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