Lauren Walker & Tony Fransos

1. Beyond Level of Service –
Towards a Relative
Measurement of Congestion
in Planning Transport
Lauren Walker and Tony Fransos
Veitch Lister Consulting

2. What is level of service?
A way of translating quantitative traffic performance measures
into a quality of service.
Aims to provide qualitative descriptions of:
• Traffic flow stability
• Ability of drivers to select desired speeds and to easily manoeuvre
• Incidence of queuing
Adopted by the Highway Capacity Manual and by Austroads

3. What is level of service?
Level of service is a useful performance measure:
• Widely accepted
• Simply distils complicated engineering analysis with a highly
recognisable measurement scale (A, B, C etc.)
• Uses quantitative performance measures (such as volume-capacity
ratios) that are readily available from strategic models as inputs

4. Drivers perceive and value aspects of congestion in
different ways
Problems with level of service
Weinstein (2006)
Congestion is subjective, not objective.
Perceptions vary from person to person, cultural context to cultural context.
Arizona DOTTS 4273 Virginia DOT

5. Drivers perceive and value aspects of congestion in
different ways
Problems with level of service
Papadimitriou et al (2010)
Field survey indicated a significant variation in tolerance to various VC ratios
from driver to driver
Hostovsky et al (2004)
Focus group found that different types of road users valued different aspects
of service quality:
•Urban commuters value travel time reliability
•Rural commuters value manoeuvrability and presence of HCVs
•Commercial vehicle drivers value consistent trip times and ability to
maintain constant speeds

6. Takes a simplistic view of congestion as a universal sign of
network failure
Problems with level of service
Source: Strongtowns.orgSource: The Age
High Street, Northcote King Street, Newtown
Source: SMH
Taylor (2002)
‘Long queues at restaurants…are seen as signs of success’
‘Traffic congestion is an inevitable by-product of vibrant, successful cities.’

7. Doesn’t allow for ‘prioritisation’ of congestion
• Primary freeway function is to carry large volumes of traffic at high
speeds for longer distances – minimal interaction with surrounding
land uses
• Established inner city areas support other important functions
(retail, commercial activity, active/public transport users) as well as
conveying traffic
Problems with level of service

8. Problems with level of service in
traffic forecasting
Strategic models do not handle delay at intersections well
Link-based VC ratios only account for a small component of
variation in travel speeds
Skabardonis (2008)
Found that VC ratios account for ~30% of variations in travel speeds on
arterial roads – single timing offsets were almost equally as impactful

9. Problems with level of service in
traffic forecasting
Difficulties in specifying ‘capacity’ in strategic models
Minderhoud et al (1997)
Three types of road capacity :
•Design capacity: the maximum volume ‘that may pass a cross section of
a road with a certain probability under predefined road and weather
conditions’
•Strategic capacity: ‘the maximum traffic volumes a road section can
handle’
•Operational capacity: ‘the actual maximum flow rate’

10. Problems with level of service in
traffic forecasting
Speed-flow curves tend to overestimate traffic volumes
under congested conditions

11. Problems with level of service in
traffic forecasting
Tolerance to congestion will likely grow into the future
Cameron (1996)
Level of service measures have not kept pace with changing travel patterns
since their initial development in the 1960s. As the public now expects higher
levels of congestion, this higher tolerance should be reflected in level of
service measures.
Clark (2008)
Drivers in larger cities, such as in inner-Sydney, have a much higher tolerance
to traffic delays than drivers in regional environments. Also, a maximum
category of level of service is probably not ‘as bad as it gets’ – a new level of
service measures ‘beyond F’ should be considered.

12. Methodology
Two-fold approach:
1. Identify a VC ratio at which poor level of service is almost certainly due
to excess demand rather than misspecification of capacity
2. Develop simple indices to weight the importance of VC ratio in the
evaluation of link performance

13. ResultsIdentify a VC ratio at which poor level of service is almost certainly due to excess demand
rather than misspecification of capacity

14. Results

15. Develop simple indices to weight the importance of VC ratio in the
evaluation of link performance
Methodology
Index Justification Calculation
Strategic
importance
Simple measure of the importance of a link in a city's
network
Count of appearances of a link in the free flow
minimum time paths
Density of
human activity
Indication of the number of residents/workers
potentially impacted by traffic on each link
Association each link with the average of the
population and employment per length of road
within an area (SA2)
Amenity Traffic noise generated is a pragmatic proxy for amenity:
- higher volumes of traffic reduce ambient quality
- higher speeds increase safety issues
- higher numbers of heavy vehicles produce more noise
and emissions
- links without crossings and large lanes numbers
decrease the permeability of the surrounding area
Based on approach from Tripathi, Mittal and
Ruwali (2012), which is proportional to traffic
volume, speed and %HCVs
Modal
compatibility
The diversity of speeds and modes that use a link Shannon's diversity index for speed and volume
separately, combined with Shannon’s diversity
index range of modes

16. Results
Less Important
More Important

17. Results
Better amenity
Worse amenity

18. Results
Less Dense
More Dense

19. Results
Fewer modes/
travel speeds
More modes/
speeds

20. Develop simple indices to weight the importance of VC ratio in the
evaluation of link performance
Methodology
Density of
human activity
index

21. Results

22. • The measure allows transport planners to more easily isolate
the relative importance of poor traffic level of service in the
context of an entire network, based on key-weighting factors.
Conclusions