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(civl261)[2009](s)quiz8a~PPSpider^_10072.pdf
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CIVL 261 Traffic and Transportation Engineering
Tutorial 8A Quiz
Name: Student ID: Week 9, 3 April 2009
Question 1:
Consider the following trip attraction models estimated using a standard computing package.
The t values are given in parentheses (assume that all the t values are larger then the critical value 1.645 for a 95% significant level on a one-tailed test, i.e. all the three equations pass the t-test)







are work trips attracted to the zone

is the total employment in the zone

is industrial employment in the zone

is the commercial employment in the zone

is service employment
Choose the most appropriate model, explaining clearly why, considering all its pros and cons

Discussions
1.
Good explanatory power of base year travel behavior should be achieved by the equation, i.e. the explanatory variables must be highly correlated with the dependent variable. Actually, the R2 of all the three equations are more than 0.9 with a good explanatory power (goodness of fit)


2.
The parameters of the trip generation equation should be stable over time, and the explanatory variables should be reliably predicted for the horizon year. In general, employment is certainly a good measure, while the more the employment in a zone, the more the work trips attracted to the zone, and the relationship (coefficients) is expected to remain constant.


3.
The independent variables should not be highly correlated between themselves. As a result, equation 3 should be simply rejected in spite of its highest explanatory power. Because X1 already contains X2 (they are highly correlated to each other). This also explains why t-value associated with the coefficient X4 becomes negative, which is not realistic.


4.
Equation1 use only one explanatory variable with good explanatory power and also being statistically significant (pass t-test), so it is acceptable. But the value of the intercept (constant, i.e. 123.2) is too large compared with the coefficient, i.e. 0.89. Imagine that if some zone only have less than 100 employments, how many work trips will attracted to that zone according to equation 1? Is that realistic?


5.
Equation 2 also has good explanatory power and being statistically significant. It use three independent variables instead of one. This is desirable, since typically some zones in a region are characterized by different categories of employment which may have quite different rates of work trips attraction. Indeed, as shown in equation 2, the coefficients associated with X1 X2 and X3 are quite different. So it is has better explanatory power, . Besides the constant (40.1) is relatively acceptable.




Summarizing the above discussion, Equation 2 is the most appropriate model.