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Energy consumption;pollutant emissions;vehicle ownership and usage
|Issue Date: ||2013-05-13T02:40:51Z
abstract:In this study, an integrated model that correlates vehicle usage with energy consumption and pollutant emissions will be developed to evaluate and forecast the effects of vehicle ownership and/or usage control strategies on the reduction of energy consumption and pollutant emissions. To achieve this goal, the study will employ data mining techniques, mainly based on the official database of aperiodic and periodic motor vehicle inspections, to extract key explanatory variables affecting emissions and to cluster similar vehicle emission types so as to properly set the pollutant parameters. According to the chosen explanatory variables and clustered vehicle types, proper questionnaires will be designed and a large-scale repeated household survey will be conducted to collect panel data with individual’s preferences, behaviors and potential responses of car and motorcycle ownership, transaction, and usage to the vehicle control strategies. This data will then be used to calibrate dynamic car and motorcycle ownership, transaction, and usage disaggregate models, using appropriate methods such as Logit modeling and Markov Chain. Aggregate models of car and motorcycle ownership and usage at national and regional levels will also be developed, using simultaneous logistic regression method, to correlate energy consumption and pollutant emissions with vehicle usage. In order to seek for optimal vehicle control strategies, a bi-level mathematic programming that incorporates all of these aggregate and disaggregate models will be formulated, solved and validated. At last, to facilitate the decision makers to examine the effects of energy and emissions reduction via the proposed integrated model, a decision support system with user-friendly interface will be developed.
|Appears in Collections:||[河海工程學系] 研究計畫|
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