39 research outputs found
CALIBRATION AND VALIDATION OF A MACROSCOPIC TRAFFIC FLOW MODEL BASED ON PLATOON DISPERSION AND QUEUE PROPAGATION
No full textThis paper proposes a preliminary calibration and validation of a macroscopic traffic flow model for signalised junctions. In fact, on the network signal setting design problem, a reliable modelling approach must be adopted to acknowledge the traffic flow effects, considering two phenomena: queue dispersion and spillback. The proposed model is an extension of the space-time discrete Cell Transmission Model (CTM), which can simulate dispersion and horizontal queue. This preliminary calibration and validation use real-world data collected on an arterial of the city of Salerno (south of Italy). Results showed that the estimated parameters are consistent with the literature
Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design
No full textThis paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis
Analisi e confronto di strategie di intervento per la gestione delle intersezioni stradali in ambito urbano
No full textNegli ultimi anni le rotatorie sono diventate protagoniste dei principali interventi sulle reti stradali in quanto “istituzionalmente” più funzionali, più eleganti, più sicure e più eco-friendly. In particolare, la rotatoria ha assunto quasi il ruolo di soluzione/infrastruttura “verde”, in contrasto con le più tradizionali (“grigie”) soluzioni di gestione delle intersezioni basate su regolazione semaforica e/o complesse canalizzazioni dei flussi veicolari. In questo scenario la soluzione “grigia” ha rapidamente lasciato il passo alla soluzione “verde”, trascurando l’elevato costo di realizzazione, gli effettivi impatti in termini di inserimento paesaggistico-ambientale e, soprattutto, la loro effettiva efficacia in termini di livello di servizio e impatti rispetto a soluzioni alternative basate su regolazione semaforica tradizionale o attuata.
In un siffatto contesto, il presente lavoro ambisce a confrontare tre differenti soluzioni di gestione di un’intersezione: una soluzione “verde” rappresentata da una rotatoria, una “grigia” rappresentata da una regolazione semaforica a piani fissi (indipendentemente dalla dinamica con cui i flussi di veicoli arrivano all’intersezione), la “smart” rappresentata da una regolazione semaforica attuata (basata sull’andamento nel tempo dei veicoli in arrivo all’intersezione, pertanto, intrinsecamente dinamica)
Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts
No full textThe paper focuses on the evaluation of the combined effect of Traffic Signal Control Strategy (TSC) and Variable Message Sign (VMS). With reference to the TSC a dynamic selection strategy based on macroscopic flow variables was considered for off-line traffic signal plans design. The combination of two ITS solutions, TSC and VMS, was tested through microscopic approach by SUMO traffic simulator which allows to directly reproduce the pollutant emissions and fuel consumptions
Network signal setting design with stage sequence optimisation
No full textOne of the most straightforward short term policies to mitigate urban traffic congestion is control through traffic lights at a single junction or network level. Existing approaches for single junction Signal Setting Design (SSD) can be grouped into two classes: Stage-based or Phase-based methods. Both these approaches take the lane marking layouts as exogenous inputs, but lane-based optimisation method may be found in literature, even though for isolated signal-controlled junctions only. The Network Signal Setting Design (NSSD) requires that offsets are introduced; a traffic flow model is also needed to compute total delay. All existing methods for NSSD follow a stage-based approach; these methods do not allow for stage matrix optimisation: it is shown that explicit enumeration of stage sequences is only practicable for very small networks.
This paper focuses on Network Signal Setting Design introducing the so-called scheduled synchronisation that includes green scheduling, green timing and coordination into one optimisation problem. The paper proposes a stage-based method to solve such a problem, as an extension of the synchronisation method and the traffic flow model proposed in Cantarella et al. (2015): first a set of candidate stages is defined for each junction, then the stage sequences, the stage lengths and the offsets are optimised all together. To the authors’ knowledge, no other one-step optimisation method is available in literature for scheduled synchronisation. Results of the proposed method to a small network were compared with those from explicit enumeration of all stage sequences; results for a larger network are also discussed
Network Signal Setting Design: Meta-heuristic optimisation methods
No full textAbstract This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design. The adopted approaches are (i) three step optimisation, in which first the stage matrix (stage composition and sequence), the green timings at each single junction are optimised, then the node offsets are computed in three successive steps; (ii) two step optimisation, in which the stage matrix is defined at a first step, then the green timings and the node offsets are computed at a second step. In both approaches the stage matrix optimisation is carried out through explicit complete enumeration. In the first approach multi-criteria optimisation is followed for single junction signal setting design (green timings), whilst the coordination (node offsets) is approached through mono-criterion optimisation, as well as for the synchronisation (green timings and offsets) in the second approach. A new traffic flow model mixing CTM and PDM has been applied. This model allows to explicitly represent horizontal queuing phenomena as well as dispersion along a link. Some meta-heuristic algorithms (i.e. Genetic Algorithms, Hill Climbing and Simulated Annealing) are investigated in order to solve the two problems. The proposed strategies are applied to two different layouts (a two junction arterial vs. a four junction network) and their effectiveness is evaluated by comparing the obtained results with those from benchmark approaches implementing mono-criterion optimisation only
Network traffic control based on a mesoscopic dynamic flow model
No full textThe paper focuses on Network Traffic Control based on aggregate traffic flow variables,
aiming at signal settings which are consistent with within-day traffic flow dynamics. The
proposed optimisation strategy is based on two successive steps: the first step refers to
each single junction optimisation (green timings), the second to network coordination (offsets).
Both of the optimisation problems are solved through meta-heuristic algorithms: the
optimisation of green timings is carried out through a multi-criteria Genetic Algorithm
whereas offset optimisation is achieved with the mono-criterion Hill Climbing algorithm.
To guarantee proper queuing and spillback simulation, an advanced mesoscopic traffic flow
model is embedded within the network optimisation method. The adopted mesoscopic
traffic flow model also includes link horizontal queue modelling. The results attained
through the proposed optimisation framework are compared with those obtained through
benchmark tools
Signal Setting Design at a Single Junction through the Application of Genetic Algorithms
No full textThe purpose of this paper is the application of Genetic Algorithms to solve the Signal Setting Design at a single junction. Two methods are compared: the monocriteria and the multicriteria optimisations. In the former case, three different objectives functions were considered: the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation; in the latter case, two combinations of criteria were investigated: the total delay minimisation and the capacity factor maximisa-tion, the total delay minimisation and the total number of stops minimisation. Furthermore, two multicriteria genetic algorithms were compared: the Goldberg’s Pareto Ranking (GPR) and the Non Dominated Sorting Genetic Algorithms (NSGA-II). Conclusions discuss the effectiveness of multicrite-ria optimisation with respect to monocriteria optimisation, and the effec-tiveness of NSGA-II with respect to the GPR
Macroscopic vs. Mesoscopic traffic flow models in Signal Setting Design
No full textThe simulation of interactions among vehicles
approaching signalised junctions, at urban level, is still an open
issue. Based on this consideration, this paper aims at comparing
the macroscopic and mesoscopic approaches for traffic flow
simulation in signalised junctions. In terms of signal setting
design, the considered decision variables are the green timings,
the scheduling and the offsets thus the three steps optimisation
(i.e. each step is referred to the optimisation of each decision
variable) has been applied. In particular, the green timings and
the scheduling are carried out at single junctions, by
multicriteria optimisation, and the offsets are computed by
monocriteria optimisation. Finally, the optimisation problems
are solved through metaheuristics algorithms
