Assignment – 4 Understanding Campus Pedestrian Flow

Yangbin Lu on 15|12|2013
Filled under: Assignment4



In this assignment I focus on the routes which were chosen by students between typical places in university campus. The more data I have, the more accurate my research will be.

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PART1. Import XML dataset

After getting map data from OpenStreetMap, all useful nodes were picked and drawn on the screen as roads net and buildings, it will take minutes for the first run, then it will save as an PNG file to load more quickly. With the same screen width 1000, height can be automatically configured by the XML map file which was exported.

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PART2. Walking density study

If tick the checkbox, it will draw  all the CSV tracking data points as translucent small circles. A specific place where it is showing more deep blue color means that more people had walked through this place in the research period. In this case, IC and university tram stop were widely used.

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PART3. Single track study

When click on the second listbox at the top left of the screen, it will list every single track file and show the track process as an interesting animation, the speed is 30 times fast than normal. In this study it is quite clear to see the activity of each person: where he stops or runs.

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PART4. Campus building highlights

The first list box can be used to show the specific building in our campus, data read from a CSV file which was manually typed in.

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PART5. Calculate the distance

Original idea about this function is to find the shortest way from mouse position to listed campus building, but given up due to the complex of this approach. Now it can calculate the whole distance through the way where the cursor was clicked. Right click to show the final result of amount of positions selected.

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PART6. Comparison

This sketch gives possibility of functions combination. With the mixture use, we can more visually see whether the options students chose are shortest or not, and consider why those routes were chosen, or why it could become a high intensive place. We can benefit from this study to find the way refining the transport in our campus and reducing negative influence to the public transport.

Sketch file:

Yangbin Lu


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