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    A traffic congestion level monitoring system in crowded developing world cities

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    Degree of Masters of Science in Computer science (1.838Mb)
    Date
    2014-07
    Author
    Ssenyange, Joseph
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    Abstract
    Many cities in developing countries like Kampala do not have modern intelligent traffic monitoring and management systems (ITS) like those deployed in developed countries because of the differences in financial and traffic conditions. Most of the cities in developed countries have good roads with clear lanes, relatively simple and orderly traffic flow patterns, homogeneous mix of vehicles, cars installed with special devices to work with ITS and are financially well to purchase and deploy such expensive systems. Contrary, cities in developing countries like Kampala have poor roads which are bumpy, potholed and sometimes non-laned with disorderly and chaotic complex traffic conditions characterized by a lot of braking and sometimes honking. Most of these roads are narrow, poorly planned and constructed and are non-laned or with only two lanes. Traffic congestion on these roads is caused by a heterogeneous mix of objects ranging from large carriers, small vehicles, motor bikes, pedestrians, hawkers and sometimes animals. With lack of real time information on traffic flows, traffic police officers fail to redirect traffic in order to avoid traffic jams, and travellers can not plan their journeys in advance in real time to avoid congested routes. The project developed a low cost solution which is able to avail real time information on traffic flow to travellers via web interface that is accessible via portable devices like mobile phones with an internet connection. The main drawback of the monitoring solution is that it performs poorly in significant weather changes like heavy rain and night time. To improve functionality of the system, future work should extend the system to make use of historical information to predict the traffic state based on day of the week and time period when there is no available fresh data from the traffic data input sources.
    URI
    http://hdl.handle.net/10570/6569
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    • East African School of Library and Information Science (EASLIS) Collection

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