This paper proposes and simulates a speed limit controller for recurrent traffic jams (SPERT). SPERT is a simple yet efficient variable speed limit (VSL) control strategy based on the behavior of the optimal controller without any need for online optimization. The online implementation of SPERT is a simple rule-based controller that activates and deactivates the corresponding variable speed limit when the densities of the dominant bottlenecks (which are found offline) reach predefined thresholds. These thresholds are defined in order to activate and deactivate the speed limits at the same bottleneck density at which they would be activated or deactivated in the nominal case. The simulation results show that SPERT is able to approach the optimal behavior while eliminating online computational cost, increasing robustness, and outperforming previously proposed easy-to-implement VSL control algorithms.

The goals of this paper are to analyze the effects of Variable Speed Limits (VSLs) on freeway traffic flow, to propose a new macroscopic model for VSL, and to compare, calibrate and validate the most well known macroscopic models for VSL using real data from a stretch of the A12 freeway in The Netherlands. Firstly, a new macroscopic model for VSLs is presented, combining characteristics of previously proposed models, in order to have the capability of modeling different capacities, critical densities, and levels of compliance for segments affected by speed limits. Subsequently, the effects of VSLs on the fundamental diagram of traffic flow are studied concluding that, at least for the considered stretch of the A12 freeway, the capacity of the freeway segment is decreased (and the critical density is increased) when the speed limit is reduced from 120 to 90 km/h. Furthermore, analyzing a wider range of VSLs, it is shown that the VSL-induced fundamental diagram is not triangular and that the speed limit compliance can be very low if enforcement measures are not applied. Finally, the proposed model is compared analytically, numerically, and graphically with the two most well-known macroscopic models for VSLs. The analysis and the simulation results show that the proposed model delivers more accurate predictions in cases where the compliance is low and/or the capacity is reduced by the use of VSLs.

This paper proposes a new ramp metering control algorithm, Feed-Foward ALINEA (FF-ALINEA), for bottlenecks located both nearby on an on-ramp and further away from it (i.e., more than just a few hundred meters). The formulation of the controller is based on a feed-forward modification of the well-known control algorithm for ramp metering, ALINEA. The feed-forward structure allows anticipating the future evolution of the bottleneck density in order to avoid or reduce traffic breakdowns. The proposed controller is tested, using the macroscopic traffic flow model METANET, for nine scenarios, and the results are compared with the ones obtained with ALINEA, PI-ALINEA, and with the optimal solution. The simulations show that the FF-ALINEA is able to approach the optimal behavior, thereby outperforming ALINEA and PI-ALINEA. Moreover, results indicate that the FF-ALINEA is quite robust in cases where different demands are considered, there are a limited number of available detectors, or there are errors in the estimation of the capacity and/or the critical density of the bottleneck.

This paper proposes a new macroscopic model for Variable Speed Limits (VSLs), combining characteristics of previously proposed models, in order to have the capability of modeling different capacities, critical densities, and levels of compliance for links affected by speed limits. Moreover, the effects of VSLs on the fundamental diagram of traffic flow are studied concluding that, at least for the considered stretch of the A12 freeway in The Netherlands, the capacity of a freeway link is decreased (and the critical density is increased) by reducing the value of the corresponding speed limit. Finally, it is shown that the VSL-induced fundamental diagram is not triangular and that the speed limit compliance can be very low if enforcement measures are not applied.

This paper proposes a logic-based control algorithm for Variable Speed Limits (VSLs) in order to reduce or avoid traffic jams created at bottlenecks. The proposed controller estimates, for each controller time step, the number of vehicles that have to be held back or released by the VSLs in order to maximize the outflow of the bottleneck (avoiding the capacity drop). Afterward, based on the estimated number of vehicles, the VSLs are increased or decreased sequentially. The proposed controller uses a feed-forward structure that allows to anticipate the future evolution of the bottleneck density in order to avoid or reduce traffic breakdowns. As a result, although the implementation of the controller is quite easy with an almost instantaneous computation time, the performance of the controller is effective in reducing Total Time Spent (TTS). The proposed controller is tested, using the macroscopic traffic flow model METANET, for 10 scenarios and the results are compared with the ones obtained with the Mainstream Traffic Flow Control (MTFC) algorithm, and with the optimal solution. The simulations show that the proposed controller is able to approach the optimal behavior and that its behavior is quite robust (especially comparing with MTFC) in cases where different demands are considered.