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  • 1.
    Ekström, Joakim
    et al.
    Linköping Universitet.
    Kristoffersson, Ida
    KTH.
    Quttineh, Nils-Hassan
    Linköping Universitet.
    Surrogate-based optimization of cordon toll levels in congested traffic networks2016In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 50, no 6, p. 1008-1033Article in journal (Refereed)
    Abstract [en]

    The benefit, in terms of social surplus, from introducing congestion charging schemes in urban networks is depending on the design of the charging scheme. The literature on optimal design of congestion pricing schemes is to a large extent based on static traffic assignment, which is known for its deficiency in correctly predict travel times in networks with severe congestion. Dynamic traffic assignment can better predict travel times in a road network, but are more computational expensive. Thus, previously developed methods for the static case cannot be applied straightforward. Surrogate-based optimization is commonly used for optimization problems with expensive-to-evaluate objective functions. In this paper, we evaluate the performance of a surrogate-based optimization method, when the number of pricing schemes, which we can afford to evaluate (because of the computational time), are limited to between 20 and 40. A static traffic assignment model of Stockholm is used for evaluating a large number of different configurations of the surrogate-based optimization method. Final evaluation is performed with the dynamic traffic assignment tool VisumDUE, coupled with the demand model Regent, for a Stockholm network including 1240 demand zones and 17000 links. Our results show that the surrogate-based optimization method can indeed be used for designing a congestion charging scheme, which return a high social surplus.

  • 2.
    Grumert, Ellen
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Tapani, Andreas
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Traffic State Estimation Using Connected Vehicles and Stationary Detectors2018In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, article id UNSP 4106086Article in journal (Refereed)
    Abstract [en]

    Real-time traffic state estimation is of importance for efficient traffic management. This is especially the case for traffic management systems that require fast detection of changes in the traffic conditions in order to apply an effective control measure. In this paper, we propose a method for estimating the traffic state and speed and density, by using connected vehicles combined with stationary detectors. The aim is to allow fast and accurate estimation of changes in the traffic conditions. The proposed method does only require information about the speed and the position of connected vehicles and can make use of sparsely located stationary detectors to limit the dependence on the infrastructure equipment. An evaluation of the proposed method is carried out by microscopic traffic simulation. The traffic state estimated using the proposed method is compared to the true simulated traffic state. Further, the density estimates are compared to density estimates from one detector-based method, one combined method, and one connected-vehicle-based method. The results of the study show that the proposed method is a promising alternative for estimating the traffic state in traffic management applications.

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