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Part 6: AlgorithmsInternational audienceComputational performance of route planning algorithms has become increasingly important in recent real navigation applications with many simultaneous route requests. Navigation applications should recommend routes as quickly as possible and preferably with some added value. This paper presents a performance evaluation of the main part of probabilistic time-dependent route planning algorithm. The main part of the algorithm computes the full probability distribution of travel time on routes with Monte Carlo simulation. Experiments show the performance of the algorithm and suggest real possibilities of use in modern navigation applications

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Part 2: AlgorithmsInternational audienceThis paper presents an algorithm for dynamic travel time computation along Czech Republic highways. The dynamism is represented by speed profiles used for computation of travel times at specified time. These speed profiles have not only the information about an optimal speed, but also a probability of this optimal speed and the probability of the speed which represents the possibility of traffic incident occurrence. Thus, the paper is focused on the analysis of paths with the uncertainty created by traffic incidents. The result of the algorithm is the probability distribution of travel times on a selected path. Based on these results, it is possible to plan a departure time with the best mean travel time for routes along the Czech Republic highways for a specified maximal acceptable travel time. This method will be a part of a larger algorithm for dynamic traffic routing

Abstract. Gauging and analyzing the ever-growing strain on todays roadways is an issue that needs to be adressed with urgency. The rate at which technology is developing and the amount of vehicles now equipped with GPS systems are factors that ensure the potential for creating statistics to gauge this strain. When processing data gathered from monitored vehicles, it is necessary to implement procedures that identify specific roadways upon which a given vehicles movement is recorded. With respects to the volume of this data, a method for indexing these data files becomes a critical issue. Within the following text, we will present a process of collecting and processing data in the FLOREON+ Traffic system and spacial indexing using a raster index that processes queries at a much greater speed than standard indexing.