Uploaded on 2014-11-25 by OliviaKarulska

This picture was taken in front of the town hall of Kaiserslautern, Germany which is a central place in the town. Kaiserslautern is located in Rhineland-Palatinate functions as a cultural, educational and business center for a lot of small villages in its surrounding. This leads to a huge amount of commuters, which come to the town mainly by bus, car and by train, causing traffic jams and other problems like pollution, noise, overcrowded busses and waste of gas, time and money. The main visible information which you can take from this picture is the traffic. One of the town’s central bus stations is located right in front of the town hall and almost every existing bus line crosses this station. Then there are the cars taking the junction, leading them to the southern part of the city in which a lot of important facilities are located, for example the university and the central train station. The same junction is used by half of the busses. Another visible information in this picture are the people crossing the streets or waiting for the bus. The invisible information you can take from this picture is the pattern of travel behaviors. You could get information about the amount of commuters, the reason why they are heading to Kaiserslautern (school, university, work) by collecting statistics, for example via polls, census or installing a digital travelling pass. Based on this information you could make statistics about how people travel during different times of the day for different kind of activities. This could help to develop a better transportation system. A second invisible information you could get here is a visualization of interchange patterns, by collecting data about the redistribution of bus passengers. To gain this information statistics should be collected, as mentioned before. The statistics would help to show interchange volumes at junctions, the capacity of single busses or bus lines and the degree of capacity utilization during the day, which helps traffic planners to optimize and adjust their plans. The last example is a possible map of centrality. By collecting data about how many people are visiting or passing the area during the day and which activities they’re doing one could measure urban function of the city. [1]: https://edxuploads.s3.amazonaws.com/14169188885756952.jpg