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Two hierarchical control schemes for regulating traffic in freeway networks via ramp metering are developed in this article. Both schemes are characterized by a multiclass nature and aim to jointly improve the total time spent by the vehicles and their pollutant emissions in the freeway network. Moreover, these schemes have been designed to be “implementation-oriented,” i.e., they are characterized by a low computation and communication effort of the controllers while providing high performance in case of bottlenecks that may be far downstream on-ramp merging areas. The reduction of the computation and communication load is achieved through an event-triggered logic implemented at the higher level of the hierarchical scheme, in which the lower level is represented by extended multiclass ALINEA controllers characterized by time-varying parameters. The two proposed schemes differ for the fact that one is a centralized scheme, whereas the second one is decentralized. The effectiveness of the two schemes is evaluated by simulation in a realistic setting, also through a comparison with an optimization-based approach.

Sustainability is becoming a key factor in the design and control of traffic systems. In the field of traffic control for freeway networks, the performance criteria explicitly included in traffic control schemes to address sustainability are mainly referred to the reduction of the environmental impact and the decrease of accidents. These control objectives are generally considered together with the conventional goal of traffic control, i.e. the minimization of the total traveling times for drivers. This paper reports a bibliometric study based on keyword counting regarding the research works on freeway traffic control developed to improve sustainability. The main goal of such analysis is to evaluate how the interest of researchers on sustainability-related freeway traffic control has evolved over the last decades and which traffic control measures have been mostly used to address such issues.

International audience; In this paper a platoon-actuated mainstream traffic control is proposed to decongest bottlenecks due to recurrent and nonrecurrent events. Indeed, differently from traditional mainstream control strategies, i.e., control strategies applied with fixed actuators, platoon-actuated control can be applied at any location on the freeway. In this work, the control actions to be communicated to the platoons, i.e., speed and configuration, are defined by means of a predictive control law based on traffic and platoon state detected in an area identified immediately upstream of the bottleneck. The main peculiarity of this scheme is that the size of the controlled area is dynamically adjusted based on the predicted congestion at the bottleneck. This approach keeps the control law computation burden low, while not sacrificing much control performance. Specifically, the number of platoons to be controlled and the time at which the platoons begin to be controlled depend from the size of the controlled area. Simulation results reported in the paper show the effectiveness of the proposed scheme, eliminating from 60% to 80% of the delay incurred from congestion compared with the uncontrolled case, depending on the level of traffic.

This paper considers a freeway stretch controlled via ramp metering and proposes a stability analysis for this system. The dynamics of the system is represented with the Asymmetric Cell Transmission Model, so that a freeway stretch can be seen as a piecewise-affine system switching among different sets of linear difference equations. The stability analysis is firstly referred to the uncontrolled system and, secondly, to the closed-loop system in which a switching proportional feedback control law is applied. In particular, different on-ramp configurations are analysed, including to the two extreme cases of only one on-ramp in a freeway stretch or on-ramps in each cell of the freeway stretch.

The purpose of this paper is to provide a method that can be used to perform resilience analyses on large-scale multi-modal transportation networks. In particular, this work proposes an assignment model through which the allocation of mobility demand on a multimodal transport network is defined at a regional or supra-regional level. The results of the assignment problem are then used as input data of a macroscopic dynamic model specifically developed to represent the dynamics of a multi-modal transport network. Finally, the proposed methodology is applied to represent the behavior of users in the Nguyen-Dupuis test network.

Freeway traffic control is a broad research area, not only interesting for its applicative perspective, but also highly motivating for theoretical investigations. This research topic has been developed in the last decades by different research groups worldwide and still offers open problems and issues to tackle which may be a source of inspiration for the community of control engineers and scientists. Since the recent technological advances towards autonomous and connected vehicles suggest that a new era for road traffic is around the corner, a survey on well-established control methods for freeway traffic networks seems particularly useful now, to fix a milestone for all the researchers in the area, in order to be ready to face the challenges of the future traffic scenarios. In this survey paper, the control approaches developed in the last decades for freeway traffic control are reviewed and a bibliometric analysis on recent scientific works addressing this topic is reported.

In this paper, a modeling framework is proposed to represent the dynamic behavior of both passenger and freight flows in a large-scale multi-modal transportation network. It consists of a macroscopic model developed to support decision makers who intend to utilize the full mobility capacity of a geographical area by allocating the mobility demand on different modes (road and rail transport) or by suggesting multi-modal itineraries. In the proposed modeling framework, the passenger demand allocation on a multi-modal transportation network is obtained by defining and solving an appropriate multi-modal assignment problem.

The purpose of this paper is to implement a dynamic model as a base for evaluating the resilience of a traffic network, capable of describing its evolution shortly after the occurrence of a disruptive event. First of all, a User-Equilibrium traffic assignment problem is solved in order to obtain an estimation of the system state before the disruption. Starting from the critical event, a Progressive Assignment procedure is performed in order to obtain reasonable traffic assignments on the network, taking into account the users' tolerance to increases in travel times as well as the inherent inertia of the system.

The purpose of this paper is to present an assignment model as a basis for evaluating the performance of a traffic network, capable of describing its evolution immediately after the occurrence of a disruptive event. First of all, a User-Equilibrium traffic assignment problem is solved in order to obtain an estimation of the system state before the disruption. Starting from the critical event, a Progressive Assignment procedure is performed in order to obtain reasonable traffic assignments on the network, taking into account the users’ tolerance to increases in travel times as well as the inherent inertia of the system. Therefore a metric for the description of the network performance is proposed as well as implementation of the model on a test network.

Summarization: The efficiency of freeway systems is often hindered by recurrent and non-recurrent congestion. The occurrence of these events is due not only to the high number of vehicles trying to use a shared infrastructure, but also by phenomena that temporarily deteriorate the capacity of the infrastructure itself. Among them, road accidents are considered as one of the primary causes of non-recurrent congestion. At the same time, several studies also identify traffic breakdowns as events leading to vehicle crashes. A specific goal of this research is to develop a global safety index that quantifies the expected number of crashes as a function of the current traffic state in the freeway system. Moreover, on the basis of this new index and the performance indicator generally adopted to evaluate the traffic delay, a coordinated ramp metering scheme is proposed jointly considering the reduction of travel times for the drivers and the improvement of safety in the freeway system. The control strategy is sought by defining a nonlinear optimal control problem with constrained control variables, solved by applying a specific gradient-based algorithm. The simulation analysis investigates the multi-objective nature of the problem assessing whether and to what extent the two components of the cost criterion are conflicting objectives. Presented on: IEEE Transactions on Intelligent Transportation Systems

The present work deals with the problem of regulating traffic in freeway networks via ramp metering with the twofold objective of reducing congestion and traffic emissions. In this paper, an answer to this problem is given by proposing a multi-class decentralised control scheme that acts according to an event-triggered logic. Local control algorithms receive local measurements from the freeway network and make a periodic prediction on the local system evolution. On the basis of this information, the local control algorithms communicate suitable parameters to the local feedback controllers, which produce control actions able to jointly reduce the congestion and the traffic emissions in a neighbourhood of the controlled on-ramp. Since these local controllers are of the multi-class type, the resulting ramp metering control actions are distinguished for different classes of vehicles. The results obtained by applying such a decentralised scheme are compared in the paper with those achieved by using a centralised control framework.

This paper introduces a new concept for traffic control in freeway systems by considering the presence of vehicle platoons as possible actuators to mitigate traffic congestion. It is known that the formation of platoons presents relevant advantages for the involved vehicles, first of all in terms of fuel consumption. Besides this, in this paper, the concept of platoon is further developed and it is investigated if the presence of platoons in the traffic stream can be exploited by a traffic controller to reduce traffic congestion. In this sense, each platoon can be seen as a moving bottleneck which influences the surrounding traffic conditions. The dimension of the platoon (i.e. number of vehicles composing it) and its velocity can be seen as control variables of a traffic management tool. In this paper, only the platoon speed is considered as control variable. Feedback regulators are discussed and their effectiveness is analyzed in simulation.

Sustainability is a key point in the design and management of mobility and traffic systems, which affects also the development of traffic control strategies for freeway networks. According to sustainability-related concepts, freeway traffic controllers should be devised not only for maximally exploiting the road capacity and decreasing vehicles travel delays, but also for reducing pollutant emissions, fuel consumptions, accidents, noise, and so on. This paper analyses the state of the art of freeway traffic control strategies characterised by sustainability-related objectives, in particular referred to traffic emissions and traffic safety, by providing a classification of the research papers in this area. The final part of the paper highlights the main research challenges for modelling and control techniques brought by the introduction of emerging information and communication technologies, that are becoming more and more widespread and are transforming the concept of vehicles in intelligent and connected agents, able to measure the traffic state and to implement specific traffic control policies.

In this paper, a freeway traffic system regulated with feedback ramp metering controllers is studied. In particular, a switched controller including the proportional-integral feedback regulator PI-ALINEA and a simpler control law is considered. The Asymmetric Cell Transmission Model, properly rewritten as a piecewise-affine system switching among different sets of linear difference equations, is the model adopted for representing the system dynamics. The closed-loop stability of this switched system is investigated in the paper and the obtained results are used to properly calibrate the controller gains. These results are then tested and discussed with a simulation analysis reported in the paper.

This paper proposes an optimization approach for sizing port rail networks and planning railway shunting operations by adopting a discrete-time model of the overall system. First, a mixed-integer linear mathematical programming problem is defined in order to optimize shunting operations to be performed on the considered network by satisfying certain arrivals and departures of import and export flows. Moreover, the proposed procedure can be used to evaluate the capacity of a port rail network, in terms of maximum number of trains that can be managed over a certain time horizon, and to carry out what-if analyses aimed at testing different scenarios. The effectiveness of the proposed approach is shown by applying the optimization problem to a real case study referred to the port rail network of La Spezia Container Terminal located in Northern Italy. A computational analysis realized by varying the dimension and complexity of the problem instances is also reported in this paper to discuss the computational performance of the proposed model.

Nowadays the majority of goods passing through seaports are transported by road, resulting in a large number of empty movements and high total costs. This paper proposes an optimization model for the cooperative planning of multiple truck carrier operations in a seaport environment for maximizing the total profit derived from their cooperation. A compensation mechanism is introduced to motivate carriers to share their trips. Time windows, trip deadlines and fleet sizes are considered. The planning approach is evaluated using real data sets from the Italian port of Genoa. Numerous scenarios are tested and an extensive computational analysis is reported.

This paper presents an optimization approach for sizing the capacity of port rail networks, in terms of maximum number of trains that can be managed over a certain time horizon. The proposed optimization method is based on a discrete-time model of the overall system in order to represent the shunting operations in the port rail network. The resulting MILP optimization problem has been applied to a real case study referred to the port rail network of La Spezia Container Terminal, in Northern Italy. What-if analyses have been carried out to test the system potentiality by varying some parameters, i.e. the terminal equipment productivity, the number of locomotives and the time to perform some technical operations.

This paper relates with the assignment of trucks to time slots in container terminals equipped with Truck Appointment Systems. A two-phase approach is provided: first, export and import containers are matched in tuples with a clustering analysis to reduce the number of empty trips and, then, tuples are assigned to time slots to minimize trucks deviation from their preferred time slots and truck turnaround times. Real case instances related to Mexican and Italian container terminals are tested. Results show that our approach reduces empty-truck trips up to 33.79% and that it can be successfully applied to any container terminal.

This paper introduces a new hybrid traffic flow model in which the presence of truck platoons is explicitly taken into account. The coordination of fleets of trucks is a relevant issue in the field of freight transport thanks to the benefits that vehicles platooning yield in the reduction of fuel consumption. However, it is recognised that truck platoons behave as moving bottlenecks causing a detrimental impact on the surrounding flows. The definition of an appropriate modelling framework is therefore needed to represent such traffic scenarios. Furthermore, this work proposes a control scheme in which the speed of each platoon is controlled according to a feedback controller that takes into account the traffic conditions detected in the freeway in which the platoon travels in order to reduce the time spent by truck platoons in the traffic jam, and to avoid abrupt decelerations.

Truck congestion is one of the most critical problems that affect many port realities around the world. To alleviate the truck congestion problem in container terminals, several approaches have been proposed and implemented. One of them refers to Truck Appointment Systems (TASs), which are technological platforms aiming to coordinate truck flows at ports, by supporting the scheduling of truck arrivals and truck operations. In this paper an integer programming model is formulated to schedule the operations of trucks that have to pick up or deliver containers in a container terminal operating with a TAS. The mathematical model seeks to assign appointments to the different time slots composing the gate opening time, with the goal of optimizing terminal resources, guaranteeing a predefined service level to haulers (i.e. maximum turnaround times in the container terminal), while minimizing congestion inside the terminal. The validity of the proposed optimization approach is highlighted by an experimental campaign based on real data sets provided by some Italian and Mexican container terminals. The obtained results highlight that the proposed model is efficient in reducing waiting times of trucks, improving both the operation efficiency and the accuracy of resource allocation in container terminals. Particularly, it can be observed that the terminal vehicle capacity and the truck arrival pattern are the most significant factors that affect the total truck delay.