1,721,014 research outputs found
"Reconstructed trajectories" dataset from the US FHWA NGSim project I80-1 dataset
No full textIl dataset contiene le traiettorie di veicoli "ricostruite" dal dataset originale - I80 (04:00pm-04:15pm) - ricavato nell'ambito del programma Next Generation Simulation (NGSIM) della US Federal Highway Administration. Il dataset di traiettorie "ricostruite" è pubblicato sul sito governativo USA "ITS DataHub" (si veda l'URL riportato sopra), insieme al dataset originale ricavato nel progetto. Il dataset è stato ottenuto con la metodologia descritta nell'articolo: M. Montanino, V. Punzo, 2015. Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns. Transportation Research Part B: Methodological 80, 82-106. Si veda anche il report disponibile sul sito del progetto MULTITUDE - http://www.multitude-project.eu/reconstructed-ngsim.htm
On string stability of a mixed and heterogeneous traffic flow: A unifying modelling framework
No full textUrged by a close future perspective of a traffic flow made of a mix of human-driven vehicles and connected, automated vehicles (CAVs), research has recently focused at making the most of CAVs capabilities to mitigate the instability of the whole, i.e. mixed, traffic flow. In all works, however, either the two sub-flows are studied under a simplifying but unrealistic assumption of flow homogeneity, or drivers’ and vehicles heterogeneity is not correctly taken into account within each sub-flow. We show here that the only condition developed so far to study a car-following model string stability for a heterogeneous flow, is inaccurate. Therefore, we propose a methodology to model string stability that considers drivers’ and vehicles heterogeneity, which is the essence of a real traffic. Uncertain transfer functions are introduced to map the probability distributions of car-following model parameters into a L2 stability measure of a mixed and heterogeneous traffic. Specifically, they allow us to move from the stability analysis of a car-following model, or of a controller, to the stability analysis of a traffic flow, as interpreted by that model, or controller. Eventually, several other theoretical contributions on stability analysis are given in the paper, aiming at reconciling approaches from different fields. Among these, a mathematical justification of the equivalence between the asymptotic stability of a closed-loop platoon system – which has been studied through the famous “traffic wave ansatz” on a ring-road – and the L2 stability of an open-loop platoon system
Car-following models evaluation through accurate experimental data
No full textINRETS, Arcueil (Paris
Car-following models evaluation through accurate experimental data
No full textINRETS, Arcueil (Paris
RailBit
No full textIL PROGRAMMA E' UN SOFTWARE DI SIMULAZIONE DEL TRAFFICO FERROVIARIO, FUNZIONANTE SU PC E MAC IN AMBIENTE OPERATIVO WINDOWS, MAC OS E LINU
Sensitivity analysis and how to choose parameters to calibrate
Full text linkThe MULTITUDE Project (Methods and tools for supporting the Use, caLibration and validaTIon of Traffic simUlations moDEls) is an Action (TU0903) supported by the EU COST office (European Cooperation in Science and Technology) and focuses on the issue of uncertainty in traffic simulation, and of calibration and validation as tools to manage it. It is driven by the concern that, although modelling is now widespread, we are unsure how much we can trust our results and conclusions. Such issues force into question the trustworthiness of the results, and indeed how well we are using them.
The project consists of 4 Working Groups (WGs) which hold short, focussed, meetings on topics of interest and propose work items on key issues. Additionally the project holds an annual meeting, as well as training schools, where the latest thinking can be passed on to young researchers and practitioners.
This report covers much of the technical work performed by Working Group 4 ‘Synthesis, dissemination and training’, and has been contributed to by:
- Costas Antoniou, NTUA, GR
- Jaume Barcelo, UPC, ES
- Mark Brackstone, IOMI, UK
- Hilmi Berk Celikoglu, ITU, TR
- Biagio Ciuffo, JRC, IT
- Vincenzo Punzo, JRC/UNINA, IT
- Pete Sykes, PS-TTRM, UK
- Tomer Toledo, Technion, IL
Peter Vortisch, KIT, DE
Peter Wagner, DLR, DE
This document assesses the current situation regarding guidelines for traffic simulation model calibration and validation worldwide, discusses the problems currently faced, and suggests potential ways in which they can be addressed, both directly, and indirectly through the development of the overall field of traffic simulation as a whole
NinjaPark
No full textIl software abilita una gestione efficiente della sosta su strada condividendo informazioni sulla sosta all'interno della comunità di utenti
A two-level probabilistic approach for validation of stochastic traffic simulations: impact of drivers’ heterogeneity models
No full textThis paper shows how traffic heterogeneity, and the way it is encoded into a model, drastically affects a model ability to reproduce observed traffic. Being heterogeneity a major source of uncertainty, to correctly frame the proposed validation methodology we have first reviewed and adapted cross-disciplinary theoretical concepts about uncertainty modelling to traffic simulation. A number of open issues, including error compensation and model overfitting, has been interpreted and clarified through the proposed framework. A two-level probabilistic approach has been applied to run stochastic simulations of three NGSIM I-80 traffic scenarios, and quantitatively infer the impact of heterogeneity. According to this approach, both the car-following and the lane-changing models of each vehicle have been calibrated against observed trajectories. Based on the estimated parameters distributions, different models of heterogeneity have been quantitatively validated against macroscopic traffic patterns. Being traffic a collective phenomenon emerging from microscopic interactions, even models calibrated on microscopic trajectories need to be quantitatively validated on macroscopic traffic patterns too. Among other results, normal distributions of the model parameters, which are customarily applied in traffic simulation practice, have been found unable to reproduce the observed congestion patterns. Parameters correlation, being claimed as highly influential in previous works, is responsible for a model overfitting in traffic scenarios with low congestion. In the end, it has been demonstrated that a thorough characterization of parameters heterogeneity cannot be left out in traffic simulation, if an ersatz representation of traffic is to be avoided
Calibration and comparison of simulation models for road network planning: the congested network of Pozzuoli
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From homogeneous to heterogeneous traffic flows: Lp String stability under uncertain model parameters
No full textThis paper shows that the heterogeneity of drivers’ and vehicles characteristics makes platoons, on average, more string-unstable. However, the string instability degree of unstable platoons is much higher in a homogeneous flow than in a heterogeneous one. These results are based on an L∞ characterization of string stability, which is shown to be the most appropriate one from a traffic safety viewpoint. Mechanisms and conditions are discussed in which an L2 characterization is not able to capture the amplification of a speed drop through a string of vehicles. An analytical sufficient condition for the L∞ string stability of heterogeneous vehicles, which move according to a general class of car-following models, is derived. Above all, a thorough comparison of L∞ and L2 string stability characterizations between a homogeneous and a heterogenous flow, is performed. To this aim, the Lp norms of heterogeneous platoons are calculated within a quasi-Monte Carlo framework. The variability of the Lp norm values due to the platoon length, the equilibrium speed, and the probability distribution model of the uncertain vehicle parameters, is analysed. Overall, it is shown that the platoon stability behaviour sensibly changes with the shape and the correlation structure of vehicle model parameter distributions. Therefore, traffic heterogeneity needs to be modelled in order to correctly characterize the string stability of a mixed traffic flow
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