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Practice Activity - Category Analysis Model (a) Model Estimation This is a simple example to let you see how category analysis works. A survey of 25 households in the city of Utopolis yielded the information which is shown in Table 1. For each household, the number of home-based person-trips was recorded, and these data were broken down by mode and by trip purpose. In addition, certain items of information on household size and structure and car-ownership were obtained. You are required to estimate a category analysis model of home-based car trips (note that the number of car trips is equal to the number of person trips by car drivers). It is suggested that you use 3 “household structures” classes and 3 “car-ownership” classes, making a total of 9 categories altogether (3 x 3 = 9). Suggested household structure classes: Households with only one adult person (aged 18+) Households with two adult persons Households with three or more adult persons Suggested car-ownership classes: Households with no car Households with one car Households with two or more cars. For each of the 9 categories, indicate the generation rate for car trips (give the range of observed values, and estimate the mean). You will find that Table 1 contains considerably more data than you will need for this problem. (b) Prediction A developer is planning to build a new housing estate on the outskirts of Utopolis. The subdivision will comprise 400 dwellings. The developer cannot be sure as to who the various home buyers will be, but has some ideas of the kinds of people who would be interested, because records have been kept of who visited display homes. These records show that: 10% were young married couples with no car; 30% were young married couples with one car; 10% were young married couples with two cars; 5% were single parents with young children, and with no car; 15% were single parents with young children with one car; 20% were large families including grown-up children with several cars; 10% were couples who were seeking houses with room for in-laws to live with them, and who had only one car among them. Use this information and the category analysis which you developed in part (a) estimate the number of car trips likely to be generated by the housing estate per day. Trip Production Modelling Practice Activity In this exercise, you will be practicing with a small sample of survey data to estimate trip generation models using the three techniques demonstrated in class; 1) Regression, 2) Cross-Classification, and 3) MCA. The dataset is available on Blackboard as Pilot_Survey_Data_Set, which you should download and save. 1) Run a correlation for total trips against the independent variables. What are the major insights you can draw? 2) Build a regression model to predict total trips using i) household size, ii) household size & vehicles, and iii) household size, vehicles & workers. Interpret the results. 3) Build a cross-classification model using household size (1-6) by vehicles owned (0-4) using the pivot table wizard. Interpret the results. 4) Repeat part 3) using MCA. Trip Attraction Modelling Practice Activity A developer has approached the local Council with a proposal to expand a shopping centre located in the Council’s planning zone 4. There is currently 15000 m2 of retail floorspace in zone 4 and this would be expanded to 22000 m2 if the development is approved. Y