How can we avoid traffic jams? Design of on-demand traffic guidance systems II

With the increasing occurrence of traffic congestions, there is a growing need for traffic guidance systems that can accurately predict future traffic flows and guide users to take the optimal route. In this thesis, we primarily analyse a traffic data set obtained from LTA Singapore that contains sp...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ramamoorthy, Gautham
مؤلفون آخرون: Justin Dauwels
التنسيق: Final Year Project
اللغة:English
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10356/54497
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:With the increasing occurrence of traffic congestions, there is a growing need for traffic guidance systems that can accurately predict future traffic flows and guide users to take the optimal route. In this thesis, we primarily analyse a traffic data set obtained from LTA Singapore that contains speed values, to understand and exploit internal trends; which can then be applied to build practical transportation algorithms for the required traffic guidance system. To reduce the complexity of the analysis, popular term reduction techniques such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are applied to the traffic data and their compression performances are compared. A new term reduction technique employing both PCA & ICA is postulated and its compression performance is measured. The report provides the theoretical background behind the different reduction techniques and presents step by step the method used for performing them through MATLAB.