出版社：The International Institute for Science, Technology and Education (IISTE)
摘要：In modeling travel demand and analyzing travel behavior, it is important to know the behavior of a large number of individuals. How the individuals choose an alternative among others given in the choice set, and how they assess and consider the different alternatives, must be a function of several factors including their need, task, socio-economic, environmental and the level of service offered by the various alternatives. A qualitative analysis of travel behavior was done with a number of individuals as the samples. To provide the required data, a field survey as direct home interview survey and travel time survey were conducted and given a number of 233 households and 871 respondents obtained as the samples. Meanwhile, the socio-economic data were obtained directly from the institution concerned. . The collected data were analyzed by using the Statistical Package for Social Science (SPSS) Software.The results of the analysis show that people with higher income and more automobile availability make more travel than people with low income and less automobile availability. The home-based trips take the largest percentage (50%) of people in the study area. The result also indicates that the shopping trips (15%) contribute higher among different trip purpose. The results also show that about 57% of individuals are between 20-50 years. The number of trips generated from each zone is strongly related to the amount of households, population, active workers and students of that zone. By considering a significant level of 5% four trip generation models have been developed. By using these models future trip generation from each zone can be determined. By applying the Gravity Model and the Fratar Method, the trip distribution models have been developed. Three basic models have been introduced by using travel time, road distance and straight distance as the resistance index. From these models the future travel pattern of Khulna Metropolitan city, Bangladesh can be predicted.
其他摘要：In modeling travel demand and analyzing travel behavior, it is important to know the behavior of a large number of individuals. How the individuals choose an alternative among others given in the choice set, and how they assess and consider the different alternatives, must be a function of several factors including their need, task, socio-economic, environmental and the level of service offered by the various alternatives. A qualitative analysis of travel behavior was done with a number of individuals as the samples. To provide the required data, a field survey as direct home interview survey and travel time survey were conducted and given a number of 233 households and 871 respondents obtained as the samples. Meanwhile, the socio-economic data were obtained directly from the institution concerned. . The collected data were analyzed by using the Statistical Package for Social Science (SPSS) Software.The results of the analysis show that people with higher income and more automobile availability make more travel than people with low income and less automobile availability. The home-based trips take the largest percentage (50%) of people in the study area. The result also indicates that the shopping trips (15%) contribute higher among different trip purpose. The results also show that about 57% of individuals are between 20-50 years. The number of trips generated from each zone is strongly related to the amount of households, population, active workers and students of that zone. By considering a significant level of 5% four trip generation models have been developed. By using these models future trip generation from each zone can be determined. By applying the Gravity Model and the Fratar Method, the trip distribution models have been developed. Three basic models have been introduced by using travel time, road distance and straight distance as the resistance index. From these models the future travel pattern of Khulna Metropolitan city, Bangladesh can be predicted. Keywords: Khulna Metropolitan City, Household survey, Travel behavior, Trip Distribution Models, Trip Generation Models.
