Analyzing the Real Time Factors: Which Causing the Traffic Congestions and Proposing the Solution for Pakistani City

Vehicle ownerships are an integral part of modern life, and traffic congestion is an unavoidable inconvenience. The Western countries have a far better control on the pace of number of vehicles on a road matched with supporting infrastructure. In contrast, cash strapped underdeveloped countries have a poorly built and scarce number of main roads with problems compounded by soft car loans, leases and other discounts. As a result several developing countries have been inundated with peripheral complications such as pollution and congestion undermining their economy with enormous energy bills negatively impacting respective economy. Case in point is Pakistan, where dilapidated infrastructure or absence outright thereof and ever more number of vehicles on the road presents a unique and highly complicated problem. One can term traffic in Sub-Continent as controlled chaos and the authors plan to develop an organized solution from the chaos. This presents a unique challenge in traffic management. They have developed a smart phone application when the phone is placed in vehicles, provides data for the origin and destination routes. Taking 6 parameters, which they believe mostly impacts the destination arrival time for the driver in Pakistan, they propose to develop a model supported by empirical data that will enable driver to select whether they are interested in economy of fuel or economy of time in reaching their destination. The authors propose to plot time it takes to reach destination versus the 6 factors that determines destination arrival time. The curve will be generated for each route and from the graph median time, standard deviation as well as confidence interval will be computed. Large data will be collected and statistical analysis will be performed to verify the integrity of the model.


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  • Accession Number: 01536555
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 30 2014 3:14PM