Suchergebnisse

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: With the increasingly widespread use of traffic flow simulation models, several questions concerning the reliability, efficiency and accuracy of such models need to be addressed convincingly. In general, the most time-efficient traffic flow models are based on the macroscopic approach to describe traffic dynamics. Macroscopic models reproduce the evolution of aggregated traffic characteristics over time and space with respect to observable variables, such as flow and speed, requiring much less computational time, compared to microscopic ones. This work assesses a second-order macroscopic gas-kinetic traffic flow (GKT) model and its numerical implementation using real traffic data from a motorway network in the U.K., where recurrent congestion originated from high on-ramp flows during the morning peak hours is observed. A parallel, metamodel-assisted Differential Evolution (DE) algorithm is employed for the calibration of the model parameters, and numerical simulations demonstrate that the DE algorithm can be a very promising method for the calibration of such traffic flow models. ; Παρουσιάστηκε στο: 2016 IEEE 19th International Conference on Intelligent Transportation Systems

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: The occurrence of perturbations in traffic flow may lead to the formation of stop-and-go waves traveling upstream, or to traffic jams. Therefore, traffic flow stability analysis is considered to be one of the fundamental problems in traffic flow theory, and a lot of effort has been spent to analyze the formation and evolution of such traffic flow instabilities. Recent advances in the field of Vehicle Automation and Communication Systems (VACS), including the most widespread Adaptive Cruise Control (ACC) systems, may consist a possible solution in reducing the magnitude or even eradicating the development of such traffic flow instabilities. This paper aims to perform a nonlinear stability analysis of a second-order macroscopic traffic flow model, which was recently developed by the authors for the simulation of the traffic flow of ACC-equipped vehicles, and identify the ways that ACC systems affect the stability of the flow, in relation with large traffic disturbances around the equilibrium state. Numerical simulations are additionally conducted, to validate the derived stability conditions. ; Παρουσιάστηκε στο: ASME 2016 International Mechanical Engineering Congress and Exposition

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: The calibration and validation of second-order macroscopic traffic flow models constitutes a difficult task; and in fact, relatively few calibration results for such macroscopic traffic flow models have been reported so far. This work evaluates a multi-lane second-order macroscopic gas-kinetic traffic (GKT) flow model and its numerical discretization, using real traffic data from a motorway network in the U.K.; where recurrent congestion originated from high on-ramp flows during the morning peak hours is occurring. In the model, the lane-changing terms, simulating lane-changes due to vehicle interactions as well as spontaneous ones, are introduced as source and sink terms in the model equations. The model provides the ability to use different calibration parameters per lane. A high-order finite volume scheme is implemented for spatial discretization, while time integration is based on a high-order implicit-explicit Runge-Kutta method. A relatively new optimization algorithm, namely a parallel, metamodel-assisted Differential Evolution (DE) algorithm, is employed for the calibration of the model parameters by searching for the global optimal solution. Numerical simulations demonstrate that the proposed model is reasonably accurate in reproducing traffic dynamics in the multi-lane framework, while the DE algorithm can be effectively used for its calibration, as well as for other similar macroscopic models. ; Παρουσιάστηκε στο: 96th Annual Meeting of the Transportation Research Board

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: Since the early days of traffic engineering, traffic flow stability has attracted a lot of attention, as the frequent occurrence of traffic jams, caused by small perturbations in traffic flow such as a sudden deceleration of a vehicle, deteriorate the performance of traffic flow and the utilization of the available infrastructure. Such traffic jams are usually related to instabilities in traffic flow, resulting in the formation of stop-and-go waves, propagating upstream the traffic flow. Emerging technologies in the field of Vehicle Automation and Communication Systems (VACS), such as Adaptive Cruise Control (ACC) systems, appear to be a remedy to reduce the amplitude or to eliminate the formation of such traffic instabilities. To this end, this work aims to derive a stability threshold of a novel macroscopic model, developed to simulate the flow of ACC-equipped vehicles, and study the impact of such vehicles on the stabilization of the traffic flow, with respect to small perturbations. The adopted macroscopic approach reflecting ACC traffic dynamics is based on the gas-kinetic (GKT) traffic flow model. The analytic results show that ACC vehicles enhance the stabilization of the traffic flow; the instability region is very narrow and by reducing the ACC time-gap setting it moves to higher values of density. ; Παρουσιάστηκε στο: ASME 2015 International Mechanical Engineering Congress and Exposition

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: Vehicle merging on highways has always been an important aspect, which directly affects the capacity of the highway. Under critical traffic conditions, the merging of main road traffic and on-ramp traffic is known to trigger speed breakdown and congestion. Additionally, merging is one of the most stressful tasks for the driver, since it requires a synchronized set of observations and actions. Consequently, drivers often perform merging maneuvers with low efficiency. Emerging vehicle technologies, such as cooperative adaptive cruise control and/or merging-assistance systems, are expected to enable the so-called "cooperative merging". The purpose of this work is to propose a cooperative merging system and evaluate its performance and its impact on highway capacity. The modeling and simulation of the proposed methodology is performed within the framework of a microscopic traffic simulator. The proposed model allows for the vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication, which enables the effective handling of the available gaps between vehicles. Different cases are examined through simulations, in order to assess the impact of the system on traffic flow, under various traffic conditions. Useful conclusions are derived from the simulation results, which can form the basis for more complex merging algorithms and/or strategies that adapt to traffic conditions. ; Presented on:

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. ; Summarization: Given the importance of the credibility and validity required in macroscopic traffic flow models while performing real-word simulations, the necessity of employing an efficient, computationally fast, and reliable constrained optimization scheme for model calibration appears to be mandatory to ensure that the traffic flow characteristics are accurately represented by such models. To this end, a parallel, metamodel-assisted Differential Evolution (DE) algorithm is employed for the calibration of the second-order macroscopic gas-kinetic traffic flow (GKT) model using real traffic data from Attiki Odos freeway in Athens, Greece. The parallelization of the DE algorithm is performed using the Message Passing Interface (MPI), while artificial neural networks (ANNs) are used as surrogate models. Numerical simulations are performed, which demonstrate that the DE algorithm can be effectively used for the search of the globally optimal model parameters in the GKT model; in fact, the method appears to be promising for the calibration of other similar traffic models as well. ; Presented on: