Controlling User Groups in Traffic
J Vreeswijk, Peek Traffic bv; B Tutert, University of Twente; L Wismans, Goudappel Coffeng, NL
On the basis of policy-based target groups, we developed a prioritization strategy for traffic streams and applied it with the traffic network control system ImFlow. We conclude that policy making can become more rational, effective and efficient.
There is a growing awareness that traffic management and transport policy in general should deal with target groups instead of "undefined" traffic. With a target group approach, policy making can become more rational, effective and efficient. On the other hand, it might also lead to local traffic problems that can be rated as unacceptable.
The last decades, traffic network control systems have emerged that coordinate individual traffic lights at junctions in a network to arrive to optimum values for certain user defined criteria. One of these systems is ImFlow, which is comparable to SCOOT and UTOPIA. On the basis of target groups, we developed a prioritization strategy for traffic streams and applied it in an off-line version of ImFlow on the simulated network of the city of Helmond in the Netherlands. ImFlow provides the option to optimize a given situation for different target groups along chosen criteria reflected by a set of control variables. This opens up the possibility to link the system objectives to overall policy objectives and to close the plan-do-check-act loop, i.e. to able to evaluate the objectives and to refine them.
The first question is how to set up a prioritization strategy that matches policy and how to effectuate this prioritization with a system like ImFlow, SCOOT or UTOPIA. We start off with defining an overall objective for network management. In many cities in the Netherlands the main objective is to arrive to optimal accessibility in terms of travel times, within constraints regarding livability and traffic safety. We took a more integral objective, namely the development of a sustainable transport system that contributes to welfare and well-being in an optimal way. It follows that: (1) sustainability and the contribution to welfare and well-being need to be defined; (2) accessibility and traffic livability in urban environments need to be assessed simultaneously, and (3) local transport policy needs to acknowledge mobility aspects for different societal groups.
A major deviation from the sectorial approach in the last decades is the acknowledgement that local transport policy can be more effective and efficient if tailored to the desires and needs by different social groups with different spatial and temporal activity patterns. Indeed, new policies like accessibility planning are in line with this approach. The focus on network activity relations instead of traditional network performance might well lead to different solutions that can be considered more sustainable. With traffic control as with other measures in the realm of transport policy, certain groups can be defined, e.g. on the basis of their origin and their travel and activity pattern. In the final paper we will elaborate on possible target groups relevant for the overall objective. For the case of Helmond we used 6 different traffic streams on a city level as target groups: (1) daily commuters, (2) through traffic, (3) freight traffic, (4) internal traffic, (5) visitors, and (6) shoppers/recreationists. Their origins and destinations may be different with combination out of the following: (1) city center, (2) city boroughs, (3) rural areas, and (4) outside municipality. We then assessed their contribution to the overall objective, by scoring them on the different criteria. This result has led to a prioritization of the groups.
For the prioritization for traffic network control we took the following approach. First we defined a selected cordon origin-destination (OD) matrix relevant to the traffic network control system in Helmond. We then transferred the target groups with their different OD patterns to the OD?s of the selected cordon. This resulted in a fraction for each target group for each direction at a junction. From the fraction and the specific priorities per target group we derived the priorities per direction.
Our main aim was to gain understanding of the possibilities of a policy driven prioritization in an urban context. We conclude that linking the functioning of the traffic network control system to overall policy objectives can lead to a more clear and consistent contribution of the transport system to society, albeit local inefficiency could provoke considerable opposition in society. [At this moment in time we only have some preliminary results. Simulation activities and analysis of output data is ongoing. We will discuss them in detail in the final paper.
Association for European Transport