Edinburgh Napier University

  Traffic congestion today is a major problem in almost all of the metropolitan areas of
the world. An increasing level of congestion results in negative impacts on the urban
environment. These include environmental pollution, energy problems and traffic
accidents. The analysis of these problems and the predictions of the impacts of any
transport policies that could be devised to deal with them are very critical to their
success. Traffic problems are almost the same in most modern cities either in
developed countries or less economically developed countries.
The driving cycle for a vehicle is the representation of a speed–time sequenced
profile, which is developed for a specific area or city. It is an important requirement in
the evaluation of the driver’s behaviour and the performance of vehicles for a number
of applications, mainly in the area of environmental studies. For example, fuel
consumption and emissions’ predictions need information input on the characteristics
of driving patterns of traffic. The applications of driving cycle analysis can be
extended however, to many more other areas. The motivation for this research is to
investigate the detailed impacts of travel demand management (TDM) measures, that
are already in application. This is to improve the network performance, using driving
cycle analysis. It is important to explicitly assess these measures using a micro-level
detailed approach in order to comprehend overall results in terms of emissions and
network performance. These understandings will benefit government agencies and
policy makers in their planning and appraisals. It will also benefit public transport
providers to improve their service in attracting and retaining their customers.
The developments of the real world driving cycles in Edinburgh and Abu Dhabi have
been presented in this research. The analysis of real world data, which has been
obtained from monitoring traffic conditions in both cities using the GPS tracking of
traffic, is presented. This data was collected from trips which have been carried out on
a number of traffic corridors in both cities. The assessment of various parameters of
traffic (i.e. speed, time percentage spent on acceleration, deceleration, idling, cruising
and cycle duration) and their statistical validity, produced a real world driving cycle
for the buses as well as the private cars. Two TDM measures have been considered; bus lanes and traffic calming measures. At each corridor, a handheld GPS device was
used to record speed, acceleration, deceleration and distances driven. This data
enabled the analysis of driving cycles for the buses and for the private cars. The
driving cycle analysis and investigations have further been investigated using
regression analysis techniques. The results suggest that the approach shows potential
but further research is needed with more data available.
The results suggest that the driving cycle analysis approach would be very useful to
have a better understanding of driving behaviour and also the detailed impacts of the
transport policies on traffic. In terms of bus lanes and traffic calming measures, the
results show some positive impacts of these policies, while there are evidences of
some negative impacts as well. These findings would be very valuable for the policy
decision makers. It is recommended from this research that the driving cycle analysis
could be utilised effectively in the assessment of TDM measures. Further
investigations and analysis of driving cycle is urgently recommended in a number of
research directions. Combined GIS and GPS data could also enhance the
development in this research.