1. Transit Service Quality and Transit Use: TBOT, Task 5

2. “Did the relationship between transit service quality and transit use change between 2000 and 2010?”

3. Trip-Level Model Methods: Explain transit use in both years –Function of service, built environment, social characteristics –Probability an individual trip will include a transit leg. Test for structural breaks

4. YearTotal7-County Transit Served* Served, used transit In model In model, used transit 200056,81134,59323,43549420,321438 2010115,82194,64555,2031,80945,9401,541 Transit not an option everywhere. Focus on trips with origin and destination ≤ 0.5 mi from transit stop.

5. YearTotal7-County Transit Served* Served, used transit In model In model, used transit 200056,81134,59323,43549420,321438 2010115,82194,64555,2031,80945,9401,541 Transit not an option everywhere. Focus on trips with origin and destination ≤ 0.5 mi from transit stop.

6. Descriptive Analysis of Trips

8. 1% 2% 7% 10%

9. Trip Model Variables Personal/ Household Characteristics Age Trip Characteristics Origin Area Characteristics GenderDestination Area Characteristics Household CharacteristicsTrip Characteristics Economic CharacteristicsPurpose Vehicle AccessWeather

10. Trip Model Results (Person/Household Characteristics) Odds Ratio Variable (with unit)20002010 Age <18 yrs old (binary)0.3324*0.1087*** 40-64 yrs old (binary) 0.8520 1.0492 65+ years old (binary) 0.7097 0.6345*** Gender Female (binary) 1.1504 0.9723 Household Characteristics One-person household (binary) 1.2144 1.1439 Children in household (binary)0.5396*** 1.0722 Economic Characteristics Worker (binary) 1.5814 1.1825 Student (binary) 1.1006 1.5829*** Household income (1) 0.9549 0.9159*** Vehicle Access Licensed driver (binary)0.1822*** 0.2273 Household vehicles/household drivers (1)0.1436***0.2880*** Constant0.1572* 0.5566 legend: * p<.1; **p<.05; *** p<.01

11. Trip Model Results (Trip Characteristics) Odds Ratio Variable (with unit)20002010 Origin Area Characteristics Population density at origin (people/sq. kM) 1.0111 0.9905 Percent white residents at origin (people/sq. kM) 1.7468 0.9264 Retail area at origin (%)0.1925*6.8154*** Office/institutional area at origin (%) 1.8572 4.3505*** Origin stop distance (mi) 0.3360 0.2035*** 30-minute transit accessibility at origin (1K jobs)1.0068***1.0051*** Destination Area Characteristics Population density at destination (people/sq. kM)1.0448*** 0.9976 Percent white residents at destination (people/sq. kM) 2.0932 0.9605 Retail area at destination (%) 1.9482 5.3636*** Office/institutional area at destination (%) 0.4424 3.1296*** Destination stop distance (mi) 0.3453 0.3370*** 30-minute transit accessibility at destination (1K jobs)1.0041**1.0039*** Trip Characteristics Network distance <=0.5mi (binary)0.2271***0.0383*** Network distance >0.5mi, <=2mi (binary)0.3461***0.2672*** Mid-day departure (binary)0.3257***0.5027*** PM peak departure (binary)0.5992***0.7785*** Evening departure (binary)0.0815***0.3017*** Purpose School destination activity (binary) 0.8996 1.0456 Utilitarian personal destination activity (binary) 0.7950 0.4511*** Non-utilitarian personal destination activity (binary)0.3281***0.4474*** Home destination activity (binary) 1.2244 1.1822 Home-based trip (binary) 0.9549 1.4449*** Weather Average temperature on travel day (degrees F) 1.0104 0.9987 Rain (binary) 1.2278 0.9500 Snow (binary) 0.4961 1.1229 Constant0.1572* 0.5566 legend: * p<.1; **p<.05; *** p<.01

12. Trip Model Conclusions No change in relationship between transit service, transit use. Change in relationship of automobile access, transit use. Potential broadening of appeal for transit. Speaks to importance of promoting/enabling car-shedding.

13. Thank you. Andrew GuthrieYingling Fan guth0064@umn.eduyingling@umn.edu