1. Travel Demand and Traffic Forecasting
Dr. Attaullah Shah

2. Travel Demand & Traffic Forecasting
Necessary understand the where to invest in new facilities and what type of facilities to invest
Two interrelated elements need to be considered
Overall regional traffic growth/decline
Potential traffic diversions

3. Traveler Decisions
Four key traveler decisions need to be studied and modeled:
Temporal decisions – the decision to travel and when to travel
Destination decisions – where to travel (shopping centers, medical centers, etc.)
Modal decisions – how to travel (auto, transit, walking, biking, etc)
Route decisions – which route to travel (I-66 or Rt 50?)

6. Trip Generation
Objective of this step is to develop a model which can predict when a trip will be made
Typical input information
Aggregate decision making units – we study households not individual travelers typically
Segment trips by type – three types 1) work trips 2) shopping trips and 3) social/recreational trips
Aggregate temporal decisions – trips per hour or per day

8. Trip Generation Model Typically assume linear form
Typical variables which influence number of trips are
Household income
Household size
Number of non-working household members
Employment rates in the neighborhood
Etc.

9. Typical Trip Generation Model

10. Trip Generation Model Example Problem
Number of peak hour vehicle-based shopping trips per household = (household size) (annual household income in $1,000s) – 0.15 (employment in the household’s neighborhood in 100s) A household with 6 members; annual income of $50k; current neighborhood has 450 retail employees; new neighborhood has 150 retail employees.

11. Trip Generation with Count Data Models
Linear regression models can produce fractions of trips which are not realistic
Poisson regression can be used to estimate trip generation for a given trip type to address this problem

12. Poisson Regression Model

13. Estimating Poisson Parameter

14. Example 8.4
Given: BZi= (household size) + (0.004) annual household income in 1,000s – 0.10 (employment in household’s neighborhood in 100s) Household has 6 members; income of $50k; lives in neighborhood with 150 retail employment; what is expected no of peak hour shopping trips? What is prob household will not make peak hour shopping trip?