traffic generation rates for high density residential developments - understanding the issues
TRANSCRIPT
Traffic Generation Rates for High Density Residential Developments
- Understanding the issues
Josh Milston
• Context
• The current process
• Study approach & site selection
• Data analysis & key findings
• Recommended next steps
Today
Josh Milston
Context• Cities are growing…..upwards
• Urban infill near public transport nodes
• Traffic assessments have significant implications for the feasibility of new development
• Adopting an appropriate traffic generation rate therefore critical!
Josh Milston
• Context
• The current process
• Study approach & site selection
• Data analysis & key findings
• Recommended next steps
Josh Milston
• ‘Standard rate’ using RMS guidelines
• Based entirely on quantum of dwellings
• 0.19 vehicles / dwelling (AM peak hour)
• 0.15 vehicles / dwelling (PM peak hour)
• Determined via surveys at eight high density residential developments across Sydney
Josh Milston
As it now stands…..
Limitations….• Rate based on a
single factor (# dwellings)
• Determined by surveys at only eight sites
• High variability
• Non-weighted average used to determine the ‘standard’ rate
Josh Milston
A more robust approach to forecasting traffic generation from high density residential developments is required.
• Context
• The current process
• Study approach & site selection
• Data analysis & key findings
• Recommended next steps
Josh Milston
Peak hour Dwellings Parking
Recommend approach to forecasting traffic generation
Multi-linear regression
Josh Milston
Data collection
Location
Influencing factors
Review of existing data
Site selection
Existing database
• 8 sites
• 770 dwellings
• 1,010 parking spaces
Josh Milston
Expanded database
• 19 sites
• 2,250 dwellings
• 2,700 parking spaces
Josh Milston
• Context
• The current process
• Study approach & site selection
• Data analysis & key findings
• Recommended next steps
Josh Milston
Influence of peak hour
• ‘Paired-t’ test
• Tests wether there is a statistical distinction between trips generated in the AM / PM peaks
• Analysis returned p-value of 0.98
AM peak hour: 482 tripsPM peak hour: 483 trips
No statistical distinction between AM/PM peak hour traffic generation rates
Josh Milston
Influence of dwelling and parking spaces
Trips / Dwelling Trips / parking space
Influence of dwelling and parking spaces
• Both quantum of parking and dwellings display strong relationship to generated traffic
• Difficult to use both variables in a single trip generation formula
• Rate of parking investigated as influencing factor
Josh Milston
1: Journey to work car mode share
2: Car/PT travel time to Sydney CBD
3: Accessibility to public transport score (PTAL)
4: Walking distance to the nearest railway station and bus stop
5: Employment and population density
Influence of location
?Josh Milston
JTW Travel time PTAL Walk distance Emp/Pop density0
0.2
0.4
0.6
0.8
1Dwellings only Inc parking rate Inc location
Influence of locationR
2 val
ue
Josh Milston
Key Findings
Traffic generation formula:
Ln(Total trips) = -0.95+ 0.01*totaldwellings+ 1.34*parksperdwelling + 1.67*JTWcarmodeshare
• Clear relationship between traffic generation and the following factors:• Number of dwellings• Rate of parking in development• Various accessibility factors
Predicted vs actual tripsRMS rates (per dwelling)
Per dwelling
Per dwelling, parking space & accessibility
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%82%
58%
42%
31%
Per dwelling & parking space
• Context
• The current process
• Study approach & site selection
• Data analysis & key findings
• Recommended next steps
Josh Milston
• Collect more data to increase sample size
• Gather data at a wider geographical spread of sites
• Gather data at sites with greater variability in public transport accessibility
• Determine appropriate measure to assess how location of a site influences the rate at which traffic is generated
Next Steps
Josh Milston
• Forecasting traffic generation is complex, but important!
• Dependent on a number of factors
• Using a rate based on a single variable is simplistic
• Surveying similar sites in nearby areas should be undertaken
Summing it up