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teaching:mfe:is [2019/07/09 17:56] msakr |
teaching:mfe:is [2019/07/09 17:58] msakr [Scalable Map-Matching] |
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| =====Scalable Map-Matching===== | =====Scalable Map-Matching===== | ||
| - | GPS trajectories originate in the form of a series of absolute lat/lon coordinates. Map-matching is the method of locating the GPS observations onto a road network. It trasforms the lat/lon pairs into pairs of a road identfier and a fraction representing the relative position on the road. This preprocessing is essential to trajectory data analysis. It contributes to cleaning the data, as well as preparing it for network-related analysis. There are two modes of map-matching: (1) offline, where al the observations of the trajectory exist before starting hte map-matching, and (2) online, where the observation arrive to the map-matcher one by one in a streaming fashion. Map-matching is known to be an expensive pre-processing, in terms of processing time. The gorwing amount of trajectory data (e.g., autonmous cars) call for map-matching methods that can scale-out. This thesis is about proposing such a solution. It shall survey the existing Algorithms, benchmark them, and propose a scale out architecture. | + | GPS trajectories originate in the form of a series of absolute lat/lon coordinates. Map-matching is the method of locating the GPS observations onto a road network. It transforms the lat/lon pairs into pairs of a road identifier and a fraction representing the relative position on the road. This preprocessing is essential to trajectory data analysis. It contributes to cleaning the data, as well as preparing it for network-related analysis. There are two modes of map-matching: (1) offline, where all the observations of the trajectory exist before starting the map-matching, and (2) online, where the observation arrive to the map-matcher one by one in a streaming fashion. Map-matching is known to be an expensive pre-processing, in terms of processing time. The growing amount of trajectory data (e.g., autonomous cars) call for map-matching methods that can scale-out. This thesis is about proposing such a solution. It shall survey the existing Algorithms, benchmark them, and propose a scale out architecture. |
| MobilityDB has types for lat/lon trajectories, as well as map-matched trajectories. the implementation of this thesis shall be integrated with MobilityDB. | MobilityDB has types for lat/lon trajectories, as well as map-matched trajectories. the implementation of this thesis shall be integrated with MobilityDB. | ||