Trip Planning Queries in Road Networks

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Mobility is a basic human characteristic. As a species we have always been moving about for a plethora of reasons. With today's abundance of mobile communication devices, data about mobility can be collected relatively easily, thus providing large amounts of spatio-temporal data. Using such data intelligently can enable people to move more efficiently in several aspects, e.g., consuming less fuel by sharing rides more effectively and efficiently, spending less time in traffic, etc., thus moving towards so-called smart cities. A large number of traffic monitoring applications, social networks, etc., can leverage such data sources and aggregate further value to it. Moreover, this data can become rather complex and richer by considering non-spatio-temporal data, e.g., public events, weather patterns and path-popularity. Given this overarching theme, the proposed research program will focus on the topic of trip planning queries in road networks. A trip planning query considers a road network, a starting and a destination point, and a set of points-of-interest a traveller (or group thereof) wants to visit. There can be several variations of trip planning queries: points-of-interest may belong to different categories-of-interest (which may be needed to be traversed in an arbitrary, full or partial order) or one may have to account for opening hours of points-of-interest along with traffic conditions or public transportation schedules, maximum distance between point-of-interest or from pre-determined paths to potential points-of-interest, etc. ******The proposed research program will contribute to advancing the state-of-the-art in the domain of trip planning queries in general by investigating three relevant aspects thereof: (a) Multi-modal transportation. Thus far in the literature, the vast majority of trip planning queries have considered a single mode of transportation. It is of practical importance to consider the possibility of travellers using more than one transportation mode in a single trip. (b) Enriched road networks. Road networks themselves are relatively simple and well understood. Nonetheless, there is a large amount of information that can be taken into account from their contextual environment as well as their historical use in order to enrich them and provide semantically more interesting answers. (c) Temporal dependency. Time is an intrinsic factor in planning, e.g., travel times vary during the day/year and travellers may need to consider a particular departure or arrival time. Those aspects have not been widely considered in the context of trip planning queries. Furthermore, given the general importance of those aspects, individually or in combination), furthering their understanding will contribute to the body of knowledge in spatio-temporal research broadly defined and enable the consideration of those aspects with respect to other queries as well.**