#Train maze software

Design of the installation will be based on the interior of surveillance rooms. Execution depending on exhibition space and available budget. The installation is an extension of the online interface, with each interface element on a seperate screen and/or audio monitor. However, we don’t have access to your webcam. Take note: all activity on this website is logged.

Relevant data and portraits of all passengers on board this train, based on travel card data and other sources.

A transcript of the story as told by one of the passengers, running on top of the video.

A video recording (with sound) from the inside of the train at this section.

The current section, showing the position of the train that we are following, based on live public transport data feeds freely available on the web.

A small map of the Maze, which can be enlarged.

One web page showing the entire project, with: In this video, the trajectory of the Maze runs through Amsterdam, New York, San Francisco and Shenzen. The homeless Bob Tagge maundering about the New York subway Video version of the Maze New York: 4 Lexington Avenue Express from Bowling Green to 125 St San Francisco: BART trains running between Daly City and EmbarcaderoĪ man on his way to a enigmatic meeting following a curious messageĪmsterdam: line 51 from Central Station to Station ZuidĪ woman working as security guard, returning home after a long shift The Metropolitan Maze will have an online interface but can also take the form of an installation.

In a future version we might want to use the surveillance cameras on board of each train. The video footage is shot on these specific lines and usually includes station calls and security messages. Every time the train leaves a station on the line, the passenger data are updated. In this project we show a sample of what is possible, without actually tapping these sources live. These data can of course be linked to tax and health insurance data, social media accounts, cloud based email services and so on. The passenger data that we show are derived from actual travel card and cell phone data that are available to the transport corporation, phone companies, the government and others. Though living their everyday routine in different cities there seems to be some relationship between the four, by ties from the past or the deceit of the imagination.īesides the four stories and the information on where the train is at a certain moment, all kind of information on the other passengers that are on board the train is given. They feel excluded, not valued and – as it goes in this respect – the alienation to which they prey is reinforced by their lack of willpower, their inability to alter their lifes, their acceptance of the fate that has condemned them to themselves. The four storylines around which the Metropolitan Maze is structured have the form of monologues of four individuals who lost their connection with society and are leading a rather lonely life, with lousy jobs or even no job at all.

Presumely, a passenger on board this train, like we are eavesdropping on his thoughts or conversation. In between stations the section of the story that belongs to this specific segment is told by,

#Train maze software

The trajectory our software is taking through the Maze is determined by the simple rule to disembark at each crossing of lines and get on board the next train arriving at that station, a train that could well be in another city.ĭuring the ride a story is told, but after a crossing of two lines you might have been shifted to another story. You are in a train, but you disembark at each junction and wait for the next train to arrive at that station.

We know the location of the trains at each moment, we know where they are headed and we know who is inside. With four stories in which the visitor participates. The Maze is made out of four subway lines in four cities, The Metropolitan Maze Public Thought The Metropolitan Maze