1. Continuous Regional Travel Behaviour Survey
Presented to:
16th TRB National Transportation Applications Conference
May, 2017

2. Background Main Database for studying travel behaviour
Relatively large (~2%) regional household travel diaries done about once every 5 years since 1985
Focus on a ‘typical day’ – fall, weekday
Gaps in understanding regional travel behaviour
Weekday vs. weekend
Seasonality
Weather effects independent from time of year

3. Research Design Main Survey (cross-sectional) Panel Survey Car loggers
Two-day trip diary
Survey over 15 months—Fall 2013 to Fall 2014—except Stat Holidays
Random sample of households over 5 time periods (waves)
Target of 5000 Households, 1000 per Wave
Panel Survey
Recruitment from Waves 1 and 2 of cross-sectional survey
About 500 panel households
Car loggers
Loggers for up to two household vehicles
Same two days of survey

4. Results How Weekend Trips are Different?
Trip rates are lower
Extended ‘peak period’ from late morning to late afternoon
Saturday trip rates are higher than Sunday, but trip characteristics are similar
Except – auto driver trips are substantially higher on Saturday
What are the seasonality effects?
Trip rates are highest in the fall and lowest in the summer
Proportion of travel-to-work trips is consistent throughout the year
School and pick-up/drop-off trips decline substantially in the summer
Shopping, social/recreation and dining increase in the summer
Mode shares are relatively consistent yearlong
Exceptions are in the summer, Auto Driver – decrease, Bike - increase

5. Lessons Learned Would we have done it again?
Yes, need some idea about travel behaviour outside of the regular travel survey
Unclear how this factors into planning decisions
What we would have done differently?
Would have narrowed the scope of the study
Cross-sectional vs. Panel – unclear if panel provides additional information
Loggers – technical issues (e.g. cold starts, signal drops) that made it unusable

6. Next Steps Econometric modelling
Account for socio-demographic, employment, prices, weather
Analyze travel behaviour changes within households (panel)

7. Thank you!