A warning system for assisting drivers during overtaking maneuvers is proposed. The system relies on Car-2-Car communication technologies and multi-agent systems. A protocol for safety overtaking is proposed based on ACL communicative acts. The mathematical model for safety overtaking used Kalman filter to minimize localization error.
Vehicular agents are empowered with domain knowledge and they can perform geospatial and temporal reasoning in @cite_10 . An ontology for the vehicular network domain has been developed for supporting agents reasoning in vanet-based cooperative applications @cite_10 . A different line of research @cite_14 is based on mobile agents and norm-aware agents. In this paper, we assume communication through vanet technologies, aiming to be consistent with the IEEE802.11p standard. A trust model in @cite_17 employs a penalty in case of misleading reports. Experiments with altruist selfish agents in vanets @cite_6 shown that average speed increased when the vehicular agents cooperate. A vanet-based emergency vehicle warning system has been developed in @cite_12 . In line with @cite_16 which argue on semantic exchange of mobility data and knowledge among moving objects, we will take a step towards formalizing vehicular-related knowledge and semantic interchange of events.
@cite_14 @cite_6 @cite_16 @cite_10 @cite_12 @cite_17
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Although drivers obtain road information through radio broadcasting or specific in-car equipment, there is still a wide gap between the synchronization of information and the actual conditions on the road. In the absence of adequate information, drivers often react to conditions with inefficient behaviors that do not contribute to their own driving goals, but increase traffic complication. Therefore, this study applies the features of information exchanged between ''Multi-Agents'' and mutual communication and collaboration mechanisms to intelligent transportation systems (ITS). If drivers could achieve distributed communication, share their driving information, and submit their own reasoned driving advice to others, many traffic situations will improve effectively. Additionally, the efficiency of the computing processes could have improved through distributed communication. At the same time, this paper proposes an architecture design, including vehicle components, OBU (On-Board Unit) devices and roadside device components (Roadside Unit) with hybrid architecture, which is intended to establish intelligent diversified road services to provide information support and applications. We review the state-of-the-art in the semantic representation of moving objects.We present the key research challenges for the semantic management of moving objects.We propose a scalable framework for the semantic management of moving objects.The framework supports a distributed storage and analysis of semantic mobility data. This position paper presents our vision for the semantic management of moving objects. We argue that exploiting semantic techniques in mobility data management can bring valuable benefits to many domains characterized by the mobility of users and moving objects in general, such as traffic management, urban dynamics analysis, ambient assisted living, emergency management, m-health, etc. We present the state-of-the-art in the domain of management of semantic locations and trajectories, and outline research challenges that need to be investigated to enable a full-fledged and intelligent semantic management of moving objects and location-based services that support smarter mobility. We propose a distributed framework for the semantic enrichment and management of mobility data and analyze the potential deployment and exploitation of such a framework. This paper deals with the integration of agent technology in the emerging field of vehicular networks. The agents are empowered with domain knowledge and they can perform geospatial and temporal reasoning. For the domain knowledge we developed a vehicular network ontology. The geospatial reasoning is performed with AllegroGraph, while event reasoning in RacerPro. The vehicle overtaking scenario is used to exemplify our solution. With the recent introduction of the eCall system, the cars involved in accidents exchange relevant information directly with the emergency healthcare services. For road safety, Vehicular Ad-hoc Networks can be used to exchange safety information between cars and ambulances, via vehicle-2-x communication. In this paper, we exploit recent advances in vehicle-2-x communication and the advantages of knowledge representation and reasoning in order to deploy cooperative communication for medical emergency services. The developed system continuously matches data retrieved from inter-vehicular communication with structured knowledge from vehicular ontologies and open street maps. In this paper we introduce a multi-faceted trust model of use for the application of ad-hoc vehicular networks (VANETs) – scenarios where agents representing drivers exchange information with other drivers regarding road and traffic conditions. We argue that there is a need to model trust in various dimensions and that combining these elements effectively can assist agents in making transportation decisions. We then introduce two new elements to our proposed model: i) distinguishing direct and indirect reports that are shared ii) employing a penalty for misleading reports, to promote honesty. We demonstrate how these two elements together serve to increase the value of the trust model, through a series of experiments of simulated traffic. In brief, we present a framework to facilitate the effective sharing of information in VANET environments between agents representing the vehicles.