Visual analytics for movement behavior in traffic and transportation


Understanding movement of vehicles, people, merchandise, or any sort of object is vital for creating knowledgeable decisions concerning public transportation planning. However, movement could be a complicated and dynamic phenomenon, and until recently, movement knowledge was difficult to exploit for such planning purposes. The widespread adoption of location-aware devices such as International Positioning System (GPS) sensors in public transportation systems and also the adoption of open information principles have set the stage for brand new strategies and tools for data collection and analysis of movement patterns. This paper illustrates the worth and benefit of applying visual analytics techniques to movement information to form valuable insight for public transportation planning using vehicle-mounted devices on buses and trams. The contribution of the paper is 3 distinct visual analytics solutions that we developed employing a real-world open knowledge feed revealed by the Helsinki Public Transport Authority. This work addresses encounters between objects, stops that interrupt movement, and flow dynamics of a large variety of moving objects. We have a tendency to instantiated the described strategies by showing that our findings will be applied in real-world use cases.

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