Abstract
Dynamic traffic management measures are potentially powerful measures to not only improve
network efficiency but also to reduce externalities of traffic (i.e. emissions of substances and
noise and safety). In current practice the deployment of these measures (i.e. strategies)
focuses on improving efficiency on a local level in which behavioral responses are not taken
into account in the assessment and mainly concerns the evaluation of a few predefined
strategies. However, these strategies should be based on their network performance, because
of spatial correlations, considering all possible strategies, which can be done by optimizing
the objectives on network level. Previously no research has been done on how these
objectives relate and what strategies can be effective, taking traffic dynamics and route choice
behavior into account.
For this purpose the optimization problem is formulated as a multi-objective network design
problem. A framework is developed, connecting the Streamline dynamic traffic assignment
model with externality models for emissions (ARTEMIS), noise (RMV and AR-INTERIMCM)
and an accident risk based model for safety. To solve the optimization problem, various
solution approaches are developed and compared, incorporating response surface methods
within genetic algorithms to accelerate the solution approach. Applications shows that the
objectives efficiency, air quality (NOx emissions) and climate (greenhouse gas emissions) are
aligned, and are opposed to traffic safety and noise. Because the objectives are conflicting,
there is not one single solution that optimizes all objectives simultaneously, an optimization
results in finding Pareto optimal solutions. To choose the best compromise solution, a
compensation principle is needed. Pruning and ranking methods have been applied, which
may be useful to circumvent the possible difficulties in analyzing the large Pareto optimal set
in the decision making process. Using cost benefit analysis shows that efficiency is the
dominant objective. Other multi criteria decision making methods are potentially more useful
as a basis for an interactive decision support tool. Analyzing the Pareto optimal solutions
further shows that metering of traffic on smart locations can be an effective strategy to reduce
externalities and that lowering the speed limit not necessarily reduces externalities.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 27 Sept 2012 |
Place of Publication | Enschede |
Publisher | |
Print ISBNs | 9789055841554 |
DOIs | |
Publication status | Published - 27 Sept 2012 |