The paper presents the NaviExpert’s Community Traffic technology, an interactive, community–based car navigation system. Using data collected from its users, Community Traffic offers services unattainable to earlier systems. On the one hand, the current traffic data are used to recommend the best routes in the navigation phase, during which many potentially unpredictable traffic-delaying and traffic-jamming events, like unexpected roadworks, road accidents, or diversions, can be taken into account and thereby successfully avoided. On the other hand, a number of istinctive features, like immediate location of various traffic dangers, are offered. Using exclusively real-life data, provided by NaviExpert, the paper presents two illustrative case studies concerned with experimental evaluation of solutions to computational problems related to the community-based services offered by the system.
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In an on-line car satellite navigation system users may communicate with the system's operator and send them information about some objects in a road network, e.g. dangerous places or safety cameras. The operator of such a system may publish this information for the benefit of other users, but firstly has to assess the credibility of the submitted information. The paper presents a probabilistic model of such a scenario- It investigates the possibility of estimating probabilities of objects' existence and users' credibilities based only on data provided by the users. This estimation is performed by the Expectation Maximization algorithm. The proposed approach is compared to a voting method in a simulation study, which is the first step required by an industrial partner toward a commercial application.
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