In literature there are several approaches to eliminate shock waves on freeways by means of dynamic speed limits. Most of them incorporate control systems that have a high computational complexity or that contain parameters without direct physical interpretation, which may make the application in real life difficult. Here we present an approach called SPECIALIST that is based on shock wave theory, and that has parameters with clear physical meaning. The clear interpretation of the parameters leads to an intuitive and insightful formulation of the tuning guidelines. One of the most important features related to the parameter tuning is that the stability of the traffic flow can be ensured by selecting a proper maximum density that is allowed to occur in the speed-controlled area. In addition, other parameters can be tuned for more robust behavior of the algorithm. We first present the theory of shock wave resolution, and next we develop a practical control algorithm based on this theory. A unique feature of the algorithm is that it first judges the solvability of a shock wave and only starts controlling the speed limits if the shock wave is classified as solvable. The algorithm is demonstrated with a simulation example, and it is shown that its performance is similar to existing approaches.

In origin–destination (O-D) estimation methods, the relationship between the link flows and the O-D flows is typically approximated by a linear function described by the assignment matrix that corresponds with the current estimate of the O-D flows. However, this relationship implicitly assumes the link flows to be separable; this assumption leads to biased results in congested networks. The use of a different linear approximation of the relationship between O-D flows and link flows has been suggested to take into account link flows being nonseparable. However, deriving this relationship is cumbersome in terms of computation time. In this paper, the use of marginal computation (MaC) is proposed. MaC is a computationally efficient method that performs a perturbation analysis, with the use of kinematic wave theory principles, to derive this relationship. The use of MaC for dynamic O-D estimation was tested on a study network and on a real network. In both cases the proposed methodology performed better than traditional O-D estimation approaches, and thereby showed its merit.