Davide Giglio

Urban traffic control structure based on hybrid Petri nets

An urban network of signalized intersections can be suitably modeled as a hybrid system, in which the vehicle flow behavior is described by means of a time-driven model and the traffic light dynamics are represented by a discrete event model. In this paper, a model of such a network via hybrid Petri nets is used to state and solve the problem of coordinating several traffic lights with the aim of improving the performance of some classes of special vehicles, i.e., public and emergency vehicles. The proposed model has been validated using real traffic data relevant to the city of Torino, Italy. Some relevant experimental results are reported and discussed.

On applying Petri nets to determine optimal offsets for coordinated traffic light timings

Significant classes of transportation systems can be represented by Petri net models. In this paper, Petri nets are applied to provide a modular representation of urban traffic systems regulated by signalized intersections. The basic idea is to consider such systems to be composed of elementary structural components, namely, intersections and road stretches. In order to describe thoroughly the movement of vehicles in the traffic network, a microscopic representation is adopted and realized via timed Petri nets. An interesting feature of the designed model consists in the possibility of representing the offsets among different traffic light cycles as embedded in the structure of the model itself. In turn, that allows us to simply implement the coordination among traffic light timings, which facilitates the description and solution of the relevant optimization problems.

Modular representation of urban traffic systems based on hybrid Petri nets

The problem of providing a modular representation of urban traffic and roadways by means of Petri nets is addressed. A modular modelling methodology is presented. After defining the urban traffic model and identifying each one of its components, it is possible to define for each element a hybrid Petri net module (HPNM), and provide an internal representation of it at a desired level of detail. A synthesis procedure allows one to join the single modules and provide the representation of the whole urban roadway considered in terms of hybrid Petri nets. An interesting characteristic proper to the proposed methodology is the complete independence of HPNMs from their internal representations. This allows one to change the model without any effort by increasing/decreasing the specified level of detail of some HPNMs making up the HPN-model of the whole system.

On representing signalized urban areas by means of deterministic-timed Petri nets

Signalized urban areas are microscopically represented by means of deterministic-timed Petri nets (DTPNs), with the purpose of providing a suitable modelling tool for traffic management and signalling control. The model described in this paper consists of signalized intersections and roads. In order to properly model traffic congestion, intersections are divided into several crossing sections. An intersection always includes a multi-stage traffic signal, whose stage matrix (i.e., the sequence of signal stages) is a-priori known. The DTPN representing the traffic model, intended to traffic management and signalling control, is proposed and fully described in the paper.

On using petri nets for representing and controlling signalized urban areas: New model and results

A microscopic model of signalized urban areas and its representation by means of stochastic-timed Petri nets are described in this paper, where a traffic-responsive control strategy, whose objective is the optimization of green duration of each stage, is also proposed. The Petri net representation here proposed is the new version of a previously proposed one, which was based on deterministic-timed Petri nets. The motivations of the need of proposing a new version and the differences between the two Petri net representations are clearly described. In addition, some results on the application of the proposed methodology to a single signalized intersection are included in the paper.

A Deterministic and Stochastic Petri Net Model for Traffic-Responsive Signaling Control in Urban Areas

The problem of reducing congestion within urban areas by means of a traffic-responsive control strategy is addressed in this paper. The model of an urban traffic network is microscopically represented by means of deterministic and stochastic Petri nets, which allow a compact representation of the dynamic traffic network. To properly model traffic congestion, intersections are divided into crossing sections, and roads have limited capacity. Each intersection includes a multiphase traffic signal, whose sequence of phases is given and represented by a timed Petri net. The control strategy proposed in this paper aims at minimizing queue lengths by optimizing the duration of each signal phase. This is accomplished by heuristically solving a stochastic optimization problem within a receding-horizon scheme, to take into account the actual traffic flow entering the network, thus making the proposed approach traffic-responsive. In this framework, the Petri nets play a key role, as the cost function to be minimized is a function of the marking, and the constraints include the marking state evolution. The proposed strategy is applicable to both undersaturated and oversaturated traffic conditions.

Optimal Strategies for Multiclass Job Scheduling on a Single Machine With Controllable Processing Times

A particular scheduling problem over a single machine is considered. Jobs belong to different classes, and two jobs belonging to the same class are considered as completely equivalent. A sequence of due dates is specified for each class of jobs, and the serviced jobs, for each class, are assigned to the due dates according to the EDD rule. The service time of any job of a given class has to be selected within an interval of possible values (the highest possible one being the nominal service time). A deviation of the actual service time from the nominal value determines a cost that has a linear dependence on such a deviation. The cost function to be minimized is the sum of the total (weighted) tardiness cost and the overall service time deviation cost. The decision variables are those concerning job sequencing (taking into account the equivalence of jobs of the same class) and service times. In this paper, a solution to this problem is provided in terms of closed-loop strategies.

Traffic-responsive signalling control through a modular/switching model represented via DTPN

Urban signalized traffic areas are considered in this paper, with the aim of minimizing congestion situations via a traffic-responsive signalling control procedure founded on a hierarchical Petri net (PN) representation of the system. The higher level of the PN representation consists of net modules, each one representing an intersection, a road, a signal staging, etc.; the description of each module in terms of deterministic-timed Petri nets (DTPN) is given at the lower level. Such a representation leads to a corresponding two-level control procedure. The high-level control system, which acts over the modular representation, switches among internal module structures so as to modify some parts of the model of the traffic system (e.g., signal plans, turning rates, etc.), depending on both state and time. The low-level control system, which acts over the DTPN representation, optimizes the performances of the traffic system, by solving a mathematical programming problem which minimizes the number of vehicles in the system. In the paper, the adopted model of the signalized urban area is briefly presented, and the two-level representation and the control system are described in details

On adopting a Petri net-based switching modelling system to represent and control urban areas

Deterministic timed Petri nets are a suitable mod- elling formalism to represent signalized urban areas microscopi- cally, when pursuing traffic management and control purposes. In the proposed model, an urban transportation network is considered to be composed of signalized intersections and roads. So as to properly model any traffic condition, including congestion, any intersection equipped with a multi-phase traffic signal is divided into several crossing sections. The modular deterministic timed Petri net representing the overall traffic network allows to implement a switching modelling system. In fact, the representation of some parts of such a Petri net can become more or less detailed, whenever some event modifying the current traffic state occurs. I. INTRODUCTION Nowadays, it is widely recognised that the search for effec- tive solutions to pressing problems of traffic in metropolitan areas is a primary task to perform. In the past decade, urban traffic has known an enormous growth, making the need for new approaches to deal with it critical, in order to spare time, money, and lives. The application of information technologies to model, analyze, and control transportation systems, that is, Intelligent Transportation Systems (ITS), seems to offer promising solutions to the above mentioned problems. In the related framework, the focus is two-folded, on both intelligent infrastructures and intelligent vehicles. An intelligent infrastructure could fulfil transportation needs inside and around cities, whereas intelligent vehicles could complement it by making a real-time traffic information exchange feasible and improving safety. Since the sixties, the flows of vehicles in metropolitan areas have usually been regulated via the implementation of some kind of control on traffic lights. That usually consists in changing, according to the time-varying behaviour of the incoming traffic, the intersection stage specification, the relative green duration of each stage, the intersection

Simulated annealing algorithms for the multi-manned assembly line balancing problem: minimising cycle time

Multi-manned assembly lines are often designed to produce big-sized products, such as automobiles and trucks. In this type of production lines, there are multi-manned workstations where a group of workers simultaneously performs different operations on the same individual product. One of the problems, that managers of such production lines usually encounter, is to produce the optimal number of items using a fixed number of workstations, without adding new ones. In this paper, such a class of problems, namely, the multi-manned assembly line balancing problem is addressed, with the objective of minimising the cycle time. A mixed-integer mathematical programming formulation is proposed for the considered problem. This model has the primary objective of minimising the cycle time for a given number of workstations and the secondary objective of minimising the total number of workers. Since the addressed problem is NP-hard, two meta-heuristic approaches based on the simulated annealing algorithm have been developed: ISA and DSA. ISA solves the problem indirectly while DSA solves it directly. The performance of the two algorithms are tested and compared on a set of test problems taken from the literature. The results show that DSA outperforms ISA in term of solution quality and computational time.