Andreas Paraskevopoulos

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We implement and experimentally evaluate landmark-based oracles for min-cost paths in two different types of road networks with time-dependent arc-cost functions, based on distinct real-world historic traffic data: the road network for the metropolitan area of Berlin, and the national road network of Germany. Our first contribution is a significant(More)
Urban road networks are represented as directed graphs, accompanied by a metric which assigns cost functions (rather than scalars) to the arcs, e.g. representing time-dependent arc-traversal-times. In this work, we present oracles for providing time-dependent min-cost route plans, and conduct their experimental evaluation on a real-world data set (city of(More)
We present a new dynamic graph structure specifically suited for large-scale transportation networks that provides simultaneously three unique features: compactness, agility and dynamicity. We demonstrate its practicality and superiority by conducting an experimental study for shortest route planning in large-scale European and US road networks with a few(More)
Many efforts have been done in the last years to model public transport timetables in order to find optimal routes. The proposed models can be classified into two types: those representing the timetable as an array, and those representing it as a graph. The array-based models have been shown to be very effective in terms of query time, while the graph-based(More)
A novel landmark-based oracle (CFLAT) is presented, which provides earliest-arrival-time route plans in time-dependent road networks. To our knowledge, this is the first oracle that preprocesses combinatorial structures (collections of time-stamped min-travel-time-path trees) rather than travel-time functions. The preprocessed data structure is exploited by(More)
We provide a cloud-based journey planner for public transport built upon an efficient core routing engine that updates efficiently timetable information in case of delays. We describe our mobile application along with a service that allows users to assess the suggested journeys offered by the application, built on top of an IoT/FIRE+ infrastructure. Our(More)
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