In practice, speed limits on road networks are often determined pragmatically, which can give suboptimal solutions for traffic performance and unfair results for the underlying user classes. This study presents an elegant approach to determine optimal speed limits on a traffic network with asymmetric user classes under congested conditions, that minimizes individual user travel time and does justice to differences in economic importance. Existing prescriptive approaches typically lack one or more of these features, cannot guarantee optimality or are difficult to solve. We formulate a new prescriptive method using mixed-integer quadratic programming. The model can be solved with well-established operation research approaches and commercial solvers such as Cplex or Gurobi. To demonstrate the approach, we apply it to a regional network in the Netherlands. The result shows a reduction of travel time of passenger cars by 6% and of trucks by 13%, with mild changes in speed limits compared to the base situation, of between −20% and +10%. The speed limit changes and impacts are in line with the relatively high economic importance of freight traffic. Also we find in this case that the speed limit changes are ordered by major routes through the network, which makes implementation relatively straightforward.

The interest in tradable mobility credits (TMC) is growing steadily. Compared to existing instruments, its cap-and-trade design for the demand side ensures that a limited quantity, e.g., traffic and related emissions, can by design not be exceeded. However, most TMC schemes are market-based financial instruments that can only be successful, if the market ensures the most efficient allocation of resources and if one can rely on the price. Hence, TMC schemes require trading activity and a liquid market that only emerges when participants are able and willing to trade. In this paper, we systematically review the TMC literature for aspects of trading activity and market liquidity, summarize the literature streams, and discuss determinants of participants’ ability and willingness to trade TMCs. During the literature review we separate those into demand-side, supply-side, and market regulation factors. This first coherent discussion of creating liquid TMC markets with substantial trading activity challenges the instrument and allows us to draw valuable conceptual implications for the TMC scheme design, but also implications for stakeholders beyond concept. Generating trading activity and liquid markets is thoroughly possible, but robustly achieving it can be challenging.

We introduce an approach to formulate and solve the multi-class user equilibrium traffic assignment as a mixed-integer linear programming (MILP) problem. Compared to simulation approaches, the analytical MILP formulation makes the solution of network assignment problems more tractable. When applied in a multi-class context, it obviates the need to assume a symmetrical influence between classes and thereby allows richer traffic behavior to be taken into account. Also, it integrates naturally in optimization problems such as maintenance planning and traffic management. We develop the model and apply it for the Sioux Falls network, showing that it outperforms the traditional Beckmann-based and MSA approaches in smaller-scale problems. Further research opportunities lie in developing extensions of MILP-based assignment, with different variants of user equilibrium or dynamic assignment, and in improving the model and solution algorithms to allow large-scale application.

This paper investigates at an aggregated (macroscopic) scale the effects of route patterns on a road network. Four main variables are considered: the production, the mean speed, the outflow and the mean travel distance. First, a simple network with heterogeneous travel distances between origins and destinationsis studied by simulation. It appears that the mean travel distance is not only very sensitive to the changes in the origin-destination (OD) matrix but also to the internal traffic conditions within the network. When this distance is assumed constant as usual in the literature, significant errorsmayappearwhen estimating the outflow at the network perimeter. The OD matrix also modifies the shape of the macroscopic fundamental diagram (MFD) to a lesser extend. Second, a new modelling framework is proposed to account for multiple macroscopic routes within reservoirs (spatial aggregates of road network) in the context of MFD simulation. In contrast to existing works, partial accumulations are defined per route and traffic waves are tracked at this level. This leads to a better representation of wave propagation between the reservoir frontiers. A Godunov scheme is combined to a HLL Riemannapproximate solver in order to derive the model numerical solutions. The accuracy of theresulting scheme is assessed for several simple cases. The new framework is similar to some multiclass models that have been elaborated in the context of link traffic dynamics.