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RESEARCH PRODUCT
Forecasting Adverse Weather Situations in the Road Network
Juan José MartínezJavier MartínezMarta Pla–castellsVicente R. Tomássubject
Operations researchComputer sciencemedia_common.quotation_subjectTransport per carreteraexpert systems02 engineering and technologyInvestigació0502 economics and business0202 electrical engineering electronic engineering information engineeringRoad Weather Information SystemQuality (business)MeteorologiaSet (psychology)Intelligent transportation systemDownstream (networking)media_commonintelligent transport systems (ITS)050210 logistics & transportationAdverse weatherSeguretat viàriaMechanical Engineeringmultiagent system05 social sciencesTraffic flowComputer Science ApplicationsAutomotive EngineeringAccidents Prevenció020201 artificial intelligence & image processingAutonomous system (mathematics)description
Weather is an important factor that affects traffic flow and road safety. Adverse weather situations affect the driving conditions directly; hence, drivers must be informed about the weather conditions downstream to adapt their driving. In the framework of intelligent transport systems, several systems have been developed to know the weather situations and inform drivers. However, these systems do not forecast weather in advance, and they need the support of road operators to inform drivers. This paper presents a new autonomous system to forecast weather conditions in a short time and to give users the information obtained. The system uses a set of algorithms and rules to determine the weather and to forecast dangerous situations on the road network. It has been implemented using a multiagent approach and tested with real data. Results are very promising. The system is able to forecast adverse situations with a high degree of quality. This quality makes it possible to trust in the system and to avoid the supervision of operators.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-08-01 |