assessing the impact of transit and personal characteristics on mode choice of tod users ms deepti...
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![Page 1: 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](https://reader036.vdocument.in/reader036/viewer/2022081519/56649d9c5503460f94a85bcf/html5/thumbnails/1.jpg)
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
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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
In this presentation…
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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
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KGUV @ 2008
3km (1.8mi) from Brisbane’s 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
facilities
Kelvin Grove Urban Village (KGUV)
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Details of transit service
Overall good quality
of PT se
rvice
0.5km
400m
800m
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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
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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%
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46%
Mode share for employees at KGUV
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85%
Mode share for students at KGUV
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Mode share for shoppers at KGUV
71%
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Mode share for residents at KGUV
78%
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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
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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%
Other 0% 1.1% 0%
1. Population approx 1.8M, average annual household income approx USD$44,000
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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
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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
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Travel demand analysis Mode choice Personal characteristics Transit characteristics Logistic regression analysis
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Coefficients of Logistic regression analysisVariable Employees Students Shoppers ResidentsLOS 0.049 -0.011 0.155 0.295Trip length -0.016 -0.029 0.042 -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
Licence availability NA -1.964 NA NA
Constant 1.734 2.440 1.168 5.170
No of cases 164 117 117 72
Nagelkerke’s R2 0.202 0.211 0.354 0.535
% correctly predicted 66% 86.4% 79.8% 86.1%
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Sensitivity of an employee’s sustainable mode choice, p(1), with age group
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Sensitivity of a student’s sustainable mode choice, p(1), with age group
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Sensitivity of a shopper’s sustainable mode choice, p(1), with age group
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Sensitivity of a resident’s sustainable mode choice, p(1), with age group
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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
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Scope of future research & future applications
Detailed comparison with other suburbs Travel demand modelling for TODs Planning future TODs