Fundamentals of Transportation/Trip Generation/Additional Problems

Additional Problems
$$Trips = B_1 Off + B_2 Ind + B_3 Ret$$
 * 1) Are number of destinations always less than origins?
 * 2) Pose 5 hypotheses about factors that affect work, non-work trips? How do these factors affect accuracy, and thus normalization?
 * 3) What is the acceptable level of error?
 * 4) Describe one variable used in trip generation and how it affects the model.
 * 5) What is the basic equation for normalization?
 * 6) Which of these models (home-end, work-end) are assumed to be more accurate? Why is it important to normalize trip generation models
 * 7) What are the different trip purposes/types trip generation?
 * 8) Why is it difficult to know who is traveling when?
 * 9) What share of trips during peak afternoon peak periods are work to home (>50%, <50%?), why?
 * 10) What does ORIO abbreviate?
 * 11) What types of employees (ORIO) are more likely to travel from work to home in the evening peak
 * 12) What does the trip rate tell us about various parts of the population?
 * 13) What does the “T-statistic” value tell us about the trip rate estimation?
 * 14) Why might afternoon work to home trips be more or less than morning home to work trips? Why might the percent of trips be different?
 * 15) Define frequency.
 * 16) Why do individuals > 65 years of age make fewer work to home trips?
 * 17) Solve the following problem. You have the following trip generation model:

And you are given the following coefficients derived from a regression model.

B_1 = 0.61 B_2 = 0.15 B_3 = 0.123

If there are 600 office employees, 300 industrial employees, and 200 retail employees, how many trips are going from work to home?

/Additional Problems