Cecilia Pasquale

An Event-Triggered Receding-Horizon Scheme for Planning Rail Operations in Maritime Terminals

This paper proposes a planning approach to optimize railway operations in seaport terminals by adopting a queue-based discrete-time model of the considered system. First, a mixed-integer linear mathematical programming problem is defined in order to optimize the timing of import trains and the use of the handling resources devoted to rail port operations. Second, in order to deal with unexpected situations or uncertainty in estimating some data necessary to the planning, an event-triggered receding-horizon planning approach is proposed, in which the finite horizon optimization problem is solved whenever a critical event happens or the real values of some problem data significantly differ from the predicted ones. Both these planning approaches are tested on data referred to a real terminal and deeply discussed in this paper.

Ramp metering control for two vehicle classes to reduce traffic emissions in freeway systems

In the paper a two-class ramp metering control strategy is proposed in order to minimize the traffic emissions in a freeway system. Two vehicle categories, i.e. cars and trucks, are explicitly represented in the dynamic model and separate control actions are devised for the two classes. The traffic emissions of vehicles are represented according to an average-speed model, assuming that the emission factor for a given pollutant depends only on the average speed during a trip. The considered control strategy is PI-ALINEA, suitably adapted to the two-class case, in which the occupancy set-point is set in order to reduce both the traffic emissions and the congestion level. The simulation tests have been realized in order to evaluate, for the one-class and for the two-class cases, how the total emissions and the total time spent by vehicles in the freeway system vary depending on the occupancy set-point, in different traffic scenarios.

A New Emission Model Including On-ramps for Two-Class Freeway Traffic Control

The main objective of this paper is to propose a new two-class macroscopic emission model to describe the pollutant emissions produced by freeway traffic. The innovative aspect of the proposed model consists in considering the on-ramp emissions, which are explicitly modeled for different traffic scenarios. Next, a two-class local controller based on a ramp metering is reported with the aim of minimizing emissions and congestion in the freeway system. The relevance of the on-ramp emission model is in this way highlighted, since ramp metering may lead to creation of queues at the entering on-ramps and hence a concentration of pollutants on these on-ramps. Simulation results show the effectiveness of the proposed control strategy for a case of study.

Two-class emission traffic control for freeway systems

Abstract In the paper a traffic control strategy based on ramp metering is proposed in order to reduce traffic emissions in freeway stretches. Such strategy is devised to take into account that two vehicle classes are present in the freeway (cars and trucks) and that they are separately controlled. The simulation analysis developed in the paper shows, first of all, that the proposed control strategy is able not only to reduce traffic emissions in the freeway but also to reduce the congestion, by decreasing the total time spent by vehicles in the system. Moreover, the effectiveness of the two-class ramp metering control is shown on different traffic scenarios, that are deeply analysed and discussed in the paper.

Multi-class local ramp metering to reduce traffic emissions in freeway systems

Abstract In this paper a local ramp-metering strategy is proposed to minimize traffic emissions in a freeway; the control scheme is based on a two-class dynamic model in which two vehicle categories related to cars and trucks are explicitly represented. In fact, a major objective of the proposed approach is to devise separate ramp metering control actions for the two classes of vehicles, supposing that separate lanes at the on-ramps and separate traffic lights are present for fast vehicles and slow vehicles. In order to take explicitly into account the traffic emissions of vehicles, we adopt an average-speed model, according to which the emission factor for a given pollutant depends on the average speed during a trip. Considering such a model, a desired value of the traffic density for each class of vehicles is fixed and a properly adapted PI-ALINEA strategy is proposed. The experimental tests show the effectiveness of the proposed approach.

A two-class traffic control scheme for reducing congestion and improving safety in freeway systems

The definition of a new control scheme for freeway traffic systems is the objective of the present paper. The main innovative aspect of this work stands in the fact that, besides considering the reduction of traffic congestion, also safety-related aspects are explicitly taken into account in the formulation of the control problem. More specifically, two different performance indexes including a relation between the number of accidents and the traffic density in a freeway stretch are defined. The solution of the control problem is sought by applying a derivative-free procedure in which two phases are sequentially adopted: a global search carried out through a specific version of the Simulated Annealing algorithm, and a local search performed by an algorithm chosen within an open-source library for nonlinear optimization. Some numerical results are reported in the paper to compare the two control functions and to verify the effectiveness of the proposed approach.

A comparative analysis of solution algorithms for nonlinear freeway traffic control problems

Objective of this paper is to test and compare different solution algorithms for solving nonlinear freeway traffic control problems. The motivation of this work is related to the fact that the nonlinear problems arising in freeway traffic control are very challenging from a computational point of view, since they are generally characterized by a large number of variables and are often nonlinear and nonconvex. Hence, efficient solution algorithms for solving these problems are required in order to design efficient control frameworks to be applied in large freeway networks, possibly in real time. In this paper, some solution algorithms, either gradient-based or derivative-free, are tested on a specific freeway traffic control problem, i.e. the definition of a two-class ramp metering strategy to reduce congestions and emissions in a freeway.

A nonlinear optimal control approach for two-class freeway traffic regulation to reduce congestion and emissions

This paper proposes a freeway traffic controller with the objective of minimizing, at the same time, congestion phenomena and traffic emissions. A multi-class framework is considered in the paper, i.e two classes of vehicles (cars and trucks) are explicitly modelled and specific control actions for each vehicle class are computed. The controller is based on the formulation and solution of a constrained discrete-time nonlinear optimal control problem for which a specific solution algorithm, the feasible direction algorithm, is used. The effectiveness of the proposed approach is shown and discussed in the paper by means of some simulation results.

A receding-horizon planning approach for rail operations in seaport container terminals

The increasing importance of environmental and social issues in transportation imposes to focus more and more on strengthening and improving rail transportation. This is even truer for logistics nodes, such as seaports, which represent places where intermodality occurs. The present paper is devoted to model and plan the rail port cycle, at an aggregate level, with the goal of satisfying a given demand of trains outgoing from a generic container terminal. In order to do that, a discrete-time queue-based model resulting in a mixed-integer linear mathematical programming problem has been formulated; moreover, an event-triggered receding-horizon planning scheme has been defined in order to take into account possible disturbances affecting the system. The proposed approach has been applied to a real container terminal located in the Northern Italy coast; the results obtained show the effectiveness of the presented planning framework.

A discrete-time model for optimizing the rail port cycle

Abstract The main objective of this work is to model and optimize the rail cycle in seaport terminals. The model proposed in the paper represents the transfer of import containers from their storage in the yard until their exit from the terminal by train. At this purpose, the standing of containers and their movements inside the terminal are modelled by a set of queues, whose dynamic evolution is described by discrete-time equations, where the state variables represent the queue lengths and the control variables take into account the utilization of terminal resources (handling systems as well as tracks) and the timing of train movements from the terminal towards their destinations. On the basis of this model, an optimization problem is defined that consists in minimizing the transfer delays of containers in the terminal while satisfying specific real constraints. This model has been tested on real data regarding an Italian container terminal, as reported in the paper.