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Exit Survey
 
 
Age
 
20-29
 
30-39
 
40-49
 
50-59
 
60-65
 
65+
 
 
 
Education
 
BA or BS
 
MA or MS
 
PhD
 
PE or other license
 
 
 
Employer
 
Local government
 
State government
 
Federal government
 
University
 
Consultant
 
Think-tank
 
Other
 
 
 
 
Job
 
Policy/elected
 
Planning
 
Modeling
 
Analysis
 
Other
 
 
 
How ACCURATE* should forecasts of demand be, for decision-making in… (eg, +- 5%, +- 10%, etc)
A Base year (e.g in calibration)? A forecast 1 yr after opening? A forecast 10 yrs after opening? A forecast 20 yrs after opening?
New road, tolled
New road, un-tolled
Widening existing road , tolled (eg add HOT lane)
Widening existing road , un-tolled
Arterial improvement (no widening)
Intersection improvement
New fixed transit (CR, HR, LRT, streetcar)
Expanded existing transit service
 
 
 
What ISSUES will our demand models likely need to address within the next decade? (1= not likely, 2= likely, 3= very likely)
Demographic/living patterns
Communications/internet/social nets
Immigration
Energy
Vehicle technology/self-driving cars
System operation
System maintenance
System expansion
Vehicle sharing
Non-motorized travel
Other? _____________
Other? ______________
 
 
 
What key KNOWLEDGE is needed to address issues? (1=not needed, 2= somewhat needed, 3 = definitely needed)
Household activities and decision-making
Regional/zonal population/land use trends
Pricing and value of time
How cities evolve
Externalities (energy, recession, etc)
Government policies
Technology advances
Other ?
Other ?
 
 
How should we PROCEED?
a.Your preferred approach: (1= less preferred, 2 = neutral, 3= most preferred )
REDUCE focus on models , relax model requirements, admit uncertainty
FACILITATE incremental improvements, with R&D funding at current levels
EXPAND model research, funding and application over the next 20-30 years (big push for transformative changes in travel modeling)
 
 
 
b.Details for each approach, if adopted: (1=less preferred, 2=neutral, 3= most preferred)
REDUCE focus on models

Track/report model accuracy/performance
Recognize optimism bias and take model results with a grain of salt
Reduce non-local funding shares
Repeal/reduce regulatory requirements for model forecasts
Other
 
 
 
FACILITATE incremental improvements
Track/evaluate model performance
Modest increases in funding for R&D
Clarify modeling ethics
Develop standards for model performance
Coordinate research efforts
Educate officials on model assumptions and limitations
Other______________________________________________
 
*Accuracy is the degree to which an estimate of demand agrees with actual demand, in percent