to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

Introduction to linear and nonlinear programming

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

The current decade sees a considerable growth in worldwide container transportation and with it an indispensable need for optimization. Also the interest in and availability of academic literatures as well as case reports are almost exploding. With this paper an earlier survey which proved to be of utmost importance for the community is updated and extended to provide the current state of the art in container terminal operations and operations research.

Operations research at container terminals: a literature update

Connected and automated vehicles (CAVs) have the potential to improve safety by reducing and mitigating traffic accidents. They can also provide opportunities to reduce transportation energy consumption and emissions by improving traffic flow. Vehicle communication with traffic structures and traffic lights can allow individual vehicles to optimize their operation and account for unpredictable changes. This paper summarizes the developments and the research trends in coordination with the CAVs that have been reported in the literature to date. Remaining challenges and potential future research directions are also discussed.

A Survey on the Coordination of Connected and Automated Vehicles at Intersections and Merging at Highway On-Ramps

The objective of this paper is the regulation of freeway traffic by means of optimal control techniques. A first innovative aspect of the proposed approach is the adopted objective function in which, besides the reduction of traffic congestion (which is typically considered in traffic control schemes), the minimization of traffic emissions is also included. Moreover, a multi-class framework is defined in which two classes of vehicles (cars and trucks) are explicitly modelled, and specific control actions for each vehicle class are sought. This results in the formulation of a multi-objective optimal control problem which is described in the paper and for which a specific solution algorithm is developed and used. The algorithm exploits a specific version of the feasible direction algorithm whose effectiveness is demonstrated in the paper by means of simulation results.

Two-class freeway traffic regulation to reduce congestion and emissions via nonlinear optimal control

Objective of the paper is to define a new freeway traffic control approach based on the Model Predictive Control methodology. The control strategy adopted is ramp metering, which is able to reduce the flow entering the mainstream from the on-ramps so as to enforce traffic regularity. To determine the ramp metering actions, an innovative MPC scheme is proposed and is characterized by two major novel aspects. First of all, the finite horizon problem to be solved has a mixed-integer linear form, so that efficient solvers can be used to find the optimal solution. Secondly, in order to reduce the number of computations, the proposed MPC scheme is of event-triggered type, i.e. the control law is not updated at each time step but only when a given set of conditions is verified. The proposed scheme is assessed in the paper via simulation showing its effectiveness in different traffic scenarios.

Event-triggered model predictive schemes for freeway traffic control

The paper proposes a multi-class control scheme for freeway traffic networks This control scheme combines two control strategies, ie ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way In particular, the ramp metering and route guidance controllers are feedback predictive controllers, ie they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type

A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

The main objective of this paper consists in modelling, optimizing, and controlling container transfer operations inside intermodal terminals. More specifically, maritime container terminals are here considered, involving three kinds of transportation modes, i.e., maritime, rail, and road transport. Generally speaking, an intermodal port terminal can be seen as a system of container flows with two interfaces, towards the hinterland and towards the sea, respectively. Moreover, inside a terminal, unloading operations of inbound containers, container storage, and loading operations of outbound containers are carried out. A simple model for maritime container terminals is proposed in this paper. In the model, a system of queues represents the standing of containers and their movements inside the terminal. The dynamic evolutions of these queues are 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 such as load/unload handling rates. On the basis of the proposed model, an optimization problem is defined that consists in minimizing the transfer delays of containers in the terminal. The problem is stated as an optimal control problem whose solution is sought by adopting a receding-horizon strategy.

Modelling and Optimal Receding-horizon Control of Maritime Container Terminals

The problem of clearing congestion situations in freeway traffic is addressed for both an N-stage and an infinite-stage control horizon (in the latter case, a receding-horizon control mechanism is used). Traffic is controlled by regulating the vehicle access to the freeway and by limiting the vehicle speed by means of variable message signs. To describe the traffic behavior, a "classical" macroscopic model, first proposed by Payne (1971), is adapted. Even though the problem is stated within a deterministic context, an optimal control law in feedback form is sought to react to unpredictable events. The resulting functional optimization problem is reduced to a nonlinear programming problem by constraining the control law to take on a fixed structure in which free parameters have to be optimized. For such a structure, a multilayer feedforward neural mapping is chosen. Simulation results show the effectiveness of the proposed method in two different case studies. For the simulation of the second case study, real traffic data are used, which allows one to very well represent critical traffic conditions on freeways.

Simona Sacone

Papers

Two-class freeway traffic regulation to reduce congestion and emissions via nonlinear optimal control

Event-triggered model predictive schemes for freeway traffic control

A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

Modelling and Optimal Receding-horizon Control of Maritime Container Terminals

Neural approximations for feedback optimal control of freeway systems