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A natural, though by no means elementary, question that comes to mind when studying networks is that of the maximum possible flow between two specified nodes of the network. The physical problem arises in almost every instance in which commodities — physical or otherwise — flow from a source s to a destination t. Thus, in a traffic network we may be interested in the maximum rate of traffic flow between two cities; in an electric power distribution network we may be interested in the maximum power transmitted from a generating station (or stations) to a particular location; in a natural gas distribution network we may be interested in the maximum rate at which gas can be supplied to a particular consumer, etc.

La pubblicazione presenta un modello originale finalizzato a permettere la esplicita modellizzazione dei fenomeno di interscambio modale in contesti intermodali. Il modello tiene conto non solo delle alternative di percorso possibili su ciascuna delle sottoreti collegate dai nodi di interscambio, ma anche della localizzazione dei nodi di interscambi e della loro accessibilità, nonchè delle caratteristiche dei nodi e della domanda di mobilità, con particolare attenzione ai fenomeni di congestione delle disponibilità di sosta.

Equity issues among travellers are critical in congestion pricing. Failure to treat equity can lead to low acceptability towards pricing. In this paper, we develop congestion pricing schemes to improve both equity and traffic performance, for multimodal networks. We consider the equity issue by the existence of heterogeneous population, with respect to income level and value-of-time (VOT). An optimization framework is formulated for obtaining optimal toll schemes. We apply an aggregated network-level traffic flow model to reproduce congestion dynamics and mode choice behavior. The gain and loss for VOT-based user groups are investigated and discussed. We carry out simulation analysis over two pricing schemes: a unified toll and a VOT-based toll. In particular, we allow during the optimization process the VOT-based toll to obtain negative values for some users if it meets some system objectives. Our results confirm that significant differences in behavior and cost savings exist among groups, which justifies the need for a VOT-based pricing. It also demonstrates that properly-designed VOT-based tolls can improve the inequity in savings, e.g. users whose VOT values are lower may receive larger travel cost savings. Furthermore, a policy-oriented discussion on the design and implementation of the proposed equitable pricing schemes is provided.

I modelli di simulazione/previsione del traffico sulle reti stradali sono orientati a riprodurre, attraverso l'uso di un opportuno insieme di sotto-modelli, i flussi e le condizioni di deflusso che si determinano su una rete di traffico in funzione delle caratteristiche della rete stessa, delle esigenze di mobilità e dei comportamenti degli utenti. In questa pubblicazioni ci si intende riferire all'utilizzo dei modelli di simulazione/previsione del traffico finalizzate alla predisposizione di basi informative in tempo reale orientate ad applicazioni di tipo ATIS (Advanced Traveller Information Systems). In tale ottica, i modelli di assegnazione del traffico vengono visti come tecnologie abilitanti per applicazioni ITS (Intelligent Transportation Systems).

We propose a traffic control approach that integrates ramp metering and dynamic route guidance using a model predictive control framework. The main objective of the control is to minimize the total time spent (TTS) in the network by providing accurate travel times shown the dynamic route guidance panels (DRIPs) as controller input to the traffic network while taking into account the effect of other traffic control measures, such as ramp metering. By aiming at minimizing the TTS as well as the difference between travel times shown on the DRIPs and the travel times actually realized by the drivers, the interests of both the individual drivers as well as the road administration are pursued. Simulation results for a case study show that the proposed integrated MPC traffic control results in a lower TTS while the drivers get accurate travel time information.

This paper validates a colored timed Petri net (CTPN) model proposed to describe urban traffic networks. In particular, a CTPN models the dynamics of signalized traffic networks and timed Petri nets describe the traffic lights controlling the area. To this aim, the modeling framework is applied to a real intersection located in Bari, Italy. Discrete event simulations of the controlled intersection test the signal timing plan under different traffic scenarios and give a confirmation of the model capability to correctly predict the traffic performance

E' presentato un modello d’assegnazione a reti congestionate con esplicita simulazione dei vincoli di capacità, finalizzato a fornire un più avanzato stumento per il monitoraggio e la progettazione delle reti di traffico. I normali modelli di assegnazione stazionaria, infatti, non son in grado di rappresentare correttamente l'incidenza che le condizioni di sovrasaturazione hanno sulla propagazione del flusso. In alternativa a tali modelli vengono generalmente proposti modelli di assegnazione di tipo within-day-dynamic che, però, sono caratterizzati da un grado di complessità enormemente maggiore. In questa pubblicazione si dimostra come, per condizioni di sovrasaturazione non estrema delle reti, la maggior parte dei fenomeni possano essere colti sufficientemente bene da modelli stazionari in grado, però, di tenere conto dei vincoli di capacità. Le implicazioni teoriche e pratiche per la messa a punto di un modello originale in tale senso sono ampiamente discusse ed il modello è compiutamente sviluppato.

Traffic flow prediction has become a hot spot in the intelligent transportation system study. In this paper, novel methods are proposed to predict traffic flow. We divide 24 hours into 4 stages according to the bimodal distribution of traffic flow, and integrate topology features of urban traffic network into 4 typical machine learning methods. Experiments on the traffic flow of Qinhuangdao city demonstrate the effectiveness and potential of the proposed methods.

Road traffic simulation is a flexible tool used for a wide variety of applications including traffic studies. In addition to mathematical based simulation models, the INRETS (French National Institute for Research in Transportation and Safety) has conducted research based on the driver behavior and has developed a behavioral simulation model, ARCHISIM, by which the traffic is produced by the interaction of simulated drivers. ARCHISIM follows the multiagent principles and can be used for various traffic studies. However, it has not been widely used. Behavioral simulation needs more computing than mathematical simulation. But, as computers get powerful enough to allow the simulation of thousands of vehicles, INRETS and SRILOG (a company specialized in Intelligent Transportation Systems) decided to validate the model for complex high-density highway networks and realized a first decisive study last year. Now we are trying to validate the model for a highway network involving an adaptive ramp metering system. We first present behavioral road traffic simulation and the simulation model ARCHISIM. Then, we expose a high-density network study involving an adaptive ramp metering system on a highway section in the Paris outskirts during the morning rush hours. Finally, the encouraging results of the study are discussed.

Summarization: Traffic-responsive control approaches, including model-predictive control (MPC), are efficient methods for making the best use of the available network capacity. Moreover, gradient-based approaches, which can be applied to smooth optimization problems, have proven their efficiency, both computationally and performance-wise, in finding optima of optimization problems. In this paper, we propose an MPC system for an urban traffic network that applies a gradient-based optimization approach to solve the control optimization problem. The controller uses a new smooth integrated flow-emission model to find a balanced tradeoff between reduction of the congestion and of the total emissions. We also introduce efficient smoothening methods for nonsmooth mathematical models of physical systems. The effectiveness of the proposed approach is demonstrated via a case study. Παρουσιάστηκε στο: IEEE Transactions on Control Systems Technology

We demonstrate the successful trial of 400 to 600 Gb/s per carrier over Orange live network. Based on Nokia PSE-Vs technology, 400 and 600 Gb/s channels were transported up to 3446 and 1100 km respectively, thanks to probabilistic constellation shaping and flexible symbol rate optimization.

The construction of the urban transport line network is one of the fundamental problems in the traffic practice. Efficient functioning of the public mass transportation supported from the public sources in the towns is more urgent at present, when the individual automobile traffic leads to congestions in central parts of the cities. The demand to increase the culture of travelling in the public mass transportation requir es, however, subst antial costs. Therefore it is necessary to solve the balance between the inhabitants ́ requirements and the economy of the transportation system. The operation of the public mass transportation must be rational; the vehicles must not show unreasonable waiting times, etc. One of the possible ways how to rationalise the public mass transportation is to minimise the number of vehicles in operation complying with the requirements of the travellers. The paper deals with the problem of minimising the number of vehicles needed to operate the lines of the public mass transportation network. To solve this problem the methods of linear programming are used. There are four mathematical models described in which the vehicles are assigned to the individual lines. The models arise from the mathematical model PRIVOL [4], and they vary from this model especially by the variety of the rolling-stock the transport company has at disposal. By means of the constructed models a number of numerical experiments concerning the ne- twork corresponding to a medium-sized town were performed using the four constructed models. These numerical experiments demonstrated the functionality of the designed models. The main contribution of the presented modifications of the original model PRIVOL consists in the fact, that instead of the optimal number of seats the new models are able to directly find an optimal number of vehicles needed to operate the particular lines to meet the expected demand of the passengers. That way the proposed approach allows to objectify the decision making of the transport company concerning the allocation of vehicles to the network lines.

The paper deals with the application of the state and parameter estimation techniques in the area of traffic control. The most important properties of the traffic system are described and the model of the traffic system, based on the traffic flow conservation principle, is presented. Various estimation and identification techniques are briefly introduced and applied for three types of roads and micro-regions, namely for city ring road, peripheral road, and city centre. Performance of estimation techniques is validated, using the derived models on real and synthetic data coming from Prague, with respect to accuracy and complexity.

The route guidance system (RGS) has been considered an important technology to mitigate urban traffic congestion. However, existing RGSs provide only route guidance after congestion happens. This reactive strategy imposes a strong limitation on the potential contribution of current RGS to the performance improvement of a traffic network. Thus, a proactive RGS based on congestion prediction is considered essential to improve the effectiveness of RGS. The problem of congestion prediction is translated into traffic amount (i.e. the number of vehicles on the individual roads) prediction, as the latter is a straightforward indicator of the former. We thereby propose two urban traffic prediction models using different modeling approaches. Model-1 is based on the traffic flow propagation in the network, while Model-2 is based on the time-varied spare flow capacity on the concerned road links. These two models are then applied to construct a centralized proactive RGS. Evaluation results show that (1) both of the proposed models reduce the prediction error up to 52% and 30% in the best cases compared to the existing Shift Model, (2) providing proactive route guidance helps reduce average travel time by up to 70% compared to providing reactive one and (3) non-rerouted vehicles could benefit more from route guidance than rerouted vehicles do.