University of Twente Student Theses


Multimodal Map Matching with smartphone data : a shortest path approach.

Neeft, J.M. (2017) Multimodal Map Matching with smartphone data : a shortest path approach.

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Abstract:Smart phones can be used for automatic trip and mode detection and have become a popular tool in studying mobility patterns and transportation network performance. The map matching problem is to allocate a sequence of sensed location measurements onto a infrastructural map, determining the path that has been travelled. Many algorithms have been developed for high frequency data, however, the level of performance for smartphone data may be insufficient. We propose an enhanced algorithmic shortest path approach to solve the map matching problem, called the MultiModal Map Matching (4M) algorithm. The main algorithmic contribution is the extension from a unimodal framework to a multimodal framework. The 4M algorithm exploits various type of data and combines both topological and probabilistic elements of existing algorithms. The developed 4M algorithm is tested using big sized real-world datasets and compared with a benchmark algorithm. Quality indicators are introduced to evaluate the performance of our algorithm. Results suggest an improvement in both quality and computational speed compared to the current state of the art.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 55 traffic technology, transport technology, 74 (human) geography, cartography, town and country planning, demography
Programme:Applied Mathematics MSc (60348)
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