In the past decades, traffic congestion on the Dutch motorway network has developed into a serious problem. The extension of the infrastructure supply has not kept up with the growth in traffic demand. Consequently, the network is very heavily loaded now, resulting in a lot of traffic congestion. Besides recurrent congestion, non-recurrent congestion takes an important part in this as well. As a result of its heavier loading, the network has become more vulnerable to disturbances (like incidents, bad weather conditions, and road works).
The traffic congestion results in the road users experiencing substantial delays. Furthermore, they are faced with large uncertainty with respect to their travel times. Because of the high societal costs attached to this delay and uncertainty, the Dutch government strives for a reduction of the amount of traffic congestion. To this end, three strategies are combined: using the existing infrastructure more efficiently, extending the infrastructure, and road pricing.
When considering measures to alleviate daily traffic congestion (like changes to the infrastructure, or dynamic traffic management measures), the inherent variability of this traffic congestion typically is not taken into account systematically. Rather, often a kind of ‘representative’ situation is analyzed (a deterministic approach). This project aims to illustrate which additional or revised insights may be obtained when this inherent variability is explicitly taken into account (a probabilistic approach).
The research is divided in four parts. First of all, it is analyzed which criterion(s), taking into account the inherent variability in traffic congestion, should be used when assessing the traffic system’s performance. Subsequently, a method should be found to evaluate the traffic system’s performance with respect to these criterion(s). This problem is split up into two parts. First of all, the (probabilistic) mechanisms governing traffic congestion will be examined. Next, attention will be focused on finding an actual quantification method. This will be the most challenging part of the project. Finally, this method will be employed in analyses related to the main research objective.