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A Methodological Framework to Estimate GHG from Travel Pattern of Tyne & Wear of Newcastle, UK with Various Policy Options using Fuzzy Logic Modal Split Model

Lookup NU author(s): Professor Margaret Carol Bell CBE, Professor Pradip Sarkar, Dr Dilum Dissanayake, Dr Anil Namdeo


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An attempt has been made to study the existing travel pattern of Newcastle City with a small of data set, UK. This would form a basis of appreciating the travel pattern with respect to mode of transport used, purpose, cost, frequency and length of travel according the different categories of socio-economic groups. In this paper, the existing travel pattern by the various socio -economic categories of people were appreciated clearly in quantitative terms with the examination of the various transport related policy and strategy opt ions to ascertain the degree of public transport to be developed for creating a conducive environment of better public transport travel condition by developing Modal Split model using Fuzzy Logic. The primary aim of the study was to explore ways and means with the help of transport policy options to quantify and reduce the greenhouse gas emitted from the transport sector with the change modal split in favour of public transport. In order to demonstrate how to estimate the above gas from the travel pattern of Newcastle city, a small sample data of 248 commuters were collected in the year 2005 mostly traveling by car and public transport using bus and metro. Further an attempt has been made to study the travel characteristics for two types road users traveling by car and public transport. The approach demonstrated here would provide a basis for estimation of greenhouse gas from the data collected from the transportation study conducted in 2005, 2011 and 2021.

Publication metadata

Author(s): Bell M, Sarkar PK, Dissanayake D, Namdeo A

Publication type: Article

Publication status: Published

Journal: International Journal of Engineering Science Invention

Year: 2015

Volume: 4

Issue: 10

Pages: 1-12

Print publication date: 01/10/2015

Online publication date: 01/10/2015

Acceptance date: 01/01/1900

ISSN (print): 2319-6726

ISSN (electronic): 2319-6734