Assessing the Impact of Transit and Personal Characteristics on Mode Choice of TOD Users Ms Deepti Muley, Dr Jonathan Bunker and Prof Luis Ferreira Queensland University of Technology, Brisbane In this presentation Introduction Need for this study Case study TOD Overview of data collection Mode shares of TOD users Mode share comparisons Travel demand of TOD users Conclusions Need for this study Comparison required to understand transport benefits of TODs Mode shares of TOD users need to be understood
Accurate travel demand models for TODs are needed Past Studies Concentrate principally on residents data No significant previous Australian case studies Kelvin Grove Urban Village (KGUV) 3km (1.8mi) from Brisbanes Central Business District Development underway Size: 16.57 Ha (approx. 41 acre) Mixed land uses Education oriented development Next to existing QUT Kelvin Grove campus (12,000 students) Close to many recreational KGUV @ 2008 facilities
Details of transit service 800m e s PT f yo ra e Ov o ll g o e c i
rv lit a u 400m q d 0.5km TOD user groups for KGUV Residents Non-student residents, Student residents Students Y8-12 High School students, University students Employees Retail employees, Professional employees
Shoppers Overview of data collection TOD user group Survey instrument Sample size Response rate Residents Mail back & intercept 76 10%
Professional employees Internet based 125 10% Retail shop employees Personal interviews 39 31% University students Internet based 89 15%
High school students Mail back 28 20% Shoppers Personal interviews 117 68% Mode share for employees at KGUV 46% Mode share for students at KGUV
85% Mode share for shoppers at KGUV 71% Mode share for residents at KGUV 78% Mode share comparison for work trips Mode of transport Greater Brisbane1 Brisbane inner northern suburbs KGUV Car
81.4% 57.6% 53% Public transport 10.2% 25.6% 26% Walk only 6.2% 14.5% 13%
Bicycle 1.2% 1.5% 7% Taxi 0.3% 0.6% 0% Other 0.6% 0.2% 1%
1. Population approx 1.8M, average annual household income approx USD$44,000 Mode share comparison for education trips Mode of transport Greater Brisbane1 Brisbane inner northern suburbs KGUV Car 58.4% 40.0% 15%
Public transport 24.9% 49.5% 78% Walk only 13.8% 9.5% 7% Bicycle 2.9% 0.0% 0%
Taxi 0.1% 0.0% 0% 0% 1.1% 0% Other 1. Population approx 1.8M, average annual household income approx USD$44,000 Mode share comparison for shopping trips Mode of transport
Greater Brisbane1 Brisbane inner northern suburbs KGUV Car 84.2% 54.7% 27% Public transport 4.7% 12.5% 23%
Walk only 9.4% 29.7% 44% Bicycle 0.6% 0.0% 4% Taxi 0.2% 0.4%
0% Other 0.9% 2.6% 2% 1. Population approx 1.8M, average annual household income approx USD$44,000 Mode share comparison for residents (Considering first trip of the day) Mode of transport Greater Brisbane1 Brisbane inner northern suburbs
KGUV Car 81.6% 87% 22% Public transport 7.8% 4.7% 43% Walk only 8.5% 6.2%
35% Bicycle 1.1% 1.6% 0% Taxi 0.3% 0.2% 0% Other 0.7%
0.4% 0% 1. Population approx 1.8M, average annual household income approx USD$44,000 Travel demand analysis Mode choice Personal characteristics Transit characteristics Logistic regression analysis Coefficients of Logistic regression analysis Variable Employees Students LOS Trip length 0.049
-0.016 -0.011 -0.029 0.155 0.042 0.295 -0.494 Travel time difference 0.015 0.023 0.069 0.052 Frequency
NA NA 0.353 NA Age group -0.837 -0.200 -1.122 -1.298 Employment status -0.463 1.516a
-0.104 -0.967 Gender 0.477 0.579 NA -1.860 NA -1.964 NA NA
1.734 2.440 1.168 5.170 164 117 117 72 Nagelkerkes R2 0.202 0.211 0.354
0.535 % correctly predicted 66% 86.4% 79.8% 86.1% Licence availability Constant No of cases Shoppers Residents Sensitivity of an employees sustainable mode choice, p(1), with age group
Sensitivity of a students sustainable mode choice, p(1), with age group Sensitivity of a shoppers sustainable mode choice, p(1), with age group Sensitivity of a residents sustainable mode choice, p(1), with age group Conclusions KGUV highly attractive to young adults More walk, cycle and public transport trips compared to Greater Brisbane and Inner Northern Brisbane users Mode shares principally dependant on age group , LOS and employment status Scope of future research & future applications Detailed comparison with other suburbs
Travel demand modelling for TODs Planning future TODs Contact author: Deepti Muley [email protected]
