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  • 101. Osorio, Carolina
    et al.
    Flötteröd, Gunnar
    Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
    Bierlaire, Michel
    A differentiable dynamic network loading model that yields full link state distributions and accounts for spillback2010Ingår i: Proceedings of the 3rd International Symposium on Dynamic Traffic Assignment, 2010Konferensbidrag (Refereegranskat)
  • 102. Osorio, Carolina
    et al.
    Flötteröd, Gunnar
    Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
    Bierlaire, Michel
    Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
    A differentiable dynamic network loading model that yields queue length distributions and accounts for spillback2010Konferensbidrag (Övrigt vetenskapligt)
  • 103. Osorio, Carolina
    et al.
    Flötteröd, Gunnar
    Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
    Bierlaire, Michel
    Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne, Switzerland.
    Computing full link state distributions in the dynamic network loading problem2010Ingår i: 2010 Proceedings European Transport Conference, 2010Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    This paper derives a new dynamic network loading model that yields full link queue length distributions, properly accounts for spillback, and maintains a differentiable mapping from the dynamic demand on the dynamic link states. The approach builds upon an existing stationary queuing network model that is based on finite capacity queuing theory. The original model is specified in terms of a set of differential equations, which in the new model are carried over to a set of equally smooth difference equations. The representation of full dynamic link state distributions has so far been reserved to microsimulations. The approach used in this paper differs from previous work in that it (i) exploits closed-form results from queuing theory, (ii) provides the additional benefit of a closed-form expression of the system's stationary state, and (iii) consists of one integrated set of smooth equations whereas previous research deployed a switching logic between multiple linear models. Essentially, the original stationary model the authors use starts from the link state distributions from the standard queuing theory global balance equations. Coupling equations are used to capture the network-wide interactions between these single-link models. The new dynamic version of this model consists of a dynamic link model and a static node model. The global balance equations are replaced by a discrete-time closed-form expression for the transient link state distributions. This expression guides the link model's transition from the full queue distribution of one time step to the next. It is available in closed form under the reasonable assumption of constant link boundary conditions during a simulation step. No dynamics are introduced into the node model, which maintains the structure of the original stationary model. Disposing of both the dynamic model and the according stationary model is useful because it allows for the evaluation of the stationary limit of the dynamic model at a low computational cost. In the analysis of the new model, this consistency is checked by running the dynamic model until it is stationary and comparing the resulting link state distributions with those of the original model. The realism of the new model's dynamics is investigated by comparison with empirical distributions obtained from a calibrated microscopic simulation model of the city of Lausanne during the evening peak hour. There are various applications of the new model. Full dynamic link state distributions can be used as inputs for route or departure time choice models that capture risk-averse behavior. The analytically tractable form of the stationary model has enabled engineers in the past to use it to solve traffic control problems using gradient-based optimization algorithms. Since the dynamic formulation preserves the smoothness of the original model, the authors expect it to be of equal interest for problems that involve derivative-based algorithms, including solution procedures for the dynamic traffic assignment problem.

  • 104.
    Osorio, Carolina
    et al.
    MIT.
    Flötteröd, Gunnar
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Transportvetenskap, Trafik och logistik.
    Bierlaire, Michel
    Dynamic network loading: a differentiable model that derives link state distributions2011Ingår i: Papers selected for the 19th International Symposium on Transportation and Traffic Theory / [ed] Cassidy, MJ; Skabardonis, A, Elsevier, 2011, s. 364-381Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    We present a dynamic network loading model that yields queue length distributions, accounts for spillbacks, and maintains a differentiable mapping from the dynamic demand on the dynamic queue lengths. The model also captures the spatial correlation of all queues adjacent to a node, and derives their joint distribution. The approach builds upon an existing stationary queueing network model that is based on finite capacity queueing theory. The original model is specified in terms of a set of differentiable equations, which in the new model are carried over to a set of equally smooth difference equations. The physical correctness of the new model is experimentally confirmed in several congestion regimes. A comparison with results predicted by the kinematic wave model (KWM) shows that the new model correctly represents the dynamic build-up, spillback, and dissipation of queues. It goes beyond the KWM in that it captures queue lengths and spillbacks probabilistically, which allows for a richer analysis than the deterministic predictions of the KWM. The new model also generates a plausible fundamental diagram, which demonstrates that it captures well the stationary flow/density relationships in both congested and uncongested conditions.

  • 105. Osorio, Carolina
    et al.
    Flötteröd, Gunnar
    Bierlaire, Michel
    Dynamic network loading: A stochastic differentiable model that derives link state distributions2011Ingår i: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 45, nr 9, s. 1410-1423Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a dynamic network loading model that yields queue length distributions, accounts for spillbacks, and maintains a differentiable mapping from the dynamic demand on the dynamic queue lengths. The model also captures the spatial correlation of all queues adjacent to a node, and derives their joint distribution. The approach builds upon an existing stationary queueing network model that is based on finite capacity queueing theory. The original model is specified in terms of a set of differentiable equations, which in the new model are carried over to a set of equally smooth difference equations. The physical correctness of the new model is experimentally confirmed in several congestion regimes. A comparison with results predicted by the kinematic wave model (KWM) shows that the new model correctly represents the dynamic build-up, spillback and dissipation of queues. It goes beyond the KWM in that it captures queue lengths and spillbacks probabilistically, which allows for a richer analysis than the deterministic predictions of the KWM. The new model also generates a plausible fundamental diagram, which demonstrates that it captures well the stationary flow/density relationships in both congested and uncongested conditions.

  • 106. Wagner, Peter
    et al.
    Flötteröd, Gunnar
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Transportvetenskap, Trafik och logistik.
    Nippold, Ronald
    Flötteröd, Yun-Pang
    Simplified car-following models2012Ingår i: TRB 91th Annual Meeting Compendium of Papers CD-ROM, Washington DC, USA, 2012Konferensbidrag (Refereegranskat)
  • 107. Zhang, Chao
    et al.
    Osorio, Carolina
    Flötteröd, Gunnar
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Transportvetenskap.
    Efficient calibration techniques for large-scale traffic simulators2017Ingår i: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 97, s. 214-239Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Road transportation simulators are increasingly used by transportation stakeholders around the world for the analysis of intricate transportation systems. Model calibration is a crucial prerequisite for transportation simulators to reliably reproduce and predict traffic conditions. This paper considers the calibration of transportation simulators. The methodology is suitable for a broad family of simulators. Its use is illustrated with stochastic and computationally costly simulators. The calibration problem is formulated as a simulation based optimization (SO) problem. We propose a metamodel approach. The analytical meta model combines information from the simulator with information from an analytical differentiable and tractable network model that relates the calibration parameters to the simulation-based objective function. The proposed algorithm is validated by considering synthetic experiments on a toy network. It is then used to address a calibration problem with real data for a large-scale network: the Berlin metropolitan network with over 24300 links and 11300 nodes. The performance of the proposed approach is compared to a traditional benchmark method. The proposed approach significantly improves the computational efficiency of the calibration algorithm with an average reduction in simulation runtime until convergence of more than 80%. The results illustrate the scalability of the approach and its suitability for the calibration of large-scale computationally inefficient network simulators. (C) 2016 Elsevier Ltd. All rights reserved.

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