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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.

  • 3.
    Lindberg, Therese
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Johansson, Fredrik
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Peterson, Anders
    Linköpings Universitet.
    Tapani, Andreas
    Transportstyrelsen.
    Discrete Event Simulation of Bus Terminals: A Modular Approach with a High Spatial Resolution2021In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2021, article id 8862893Article in journal (Refereed)
    Abstract [en]

    Interchange stations with their many connecting modes and lines are central for a high-qualitypublic transport system. Bus access at the station needs to operate reliably and efficiently in order to prevent congestion and queues. To this end, a conceptual simulation model for evaluation of bus terminal operations is presented in this paper. It is based on discrete event simulation and able to describe the detailed movements and interactions that occur between vehicles at larger terminals. The model has a modular approach, where common spatial sections at terminals are represented bymodules that can be easily combined into many different terminal layouts. An implementation of the model is presented and, as a first sensitivity test, applied in a numerical experiment representingNorrköping interchange station in Sweden. The results indicate that the model can be a useful tool in planning processes.

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  • 4.
    Olstam, Johan
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Bernhardsson, Viktor
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Choudhury, Charisma F.
    University of Leeds.
    Klunder, Gerdien
    TNO.
    Wilmink, Isabel
    TNO.
    van Noort, Martijn
    TNO.
    Modelling Eco-Driving Support System for Microscopic Traffic Simulation2019In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2019, article id 2162568Article in journal (Refereed)
    Abstract [en]

    Microscopic traffic simulation is an ideal tool for investigating the network level impacts of eco-driving in different networks and traffic conditions, under varying penetration rates and driver compliance rates. The reliability of the traffic simulation results however rely on the accurate representation of the simulation of the driver support system and the response of the driver to the eco-driving advice, as well as on a realistic modelling and calibration of the driver's behaviour. The state-of-the-art microscopic traffic simulation models however exclude detailed modelling of the driver response to eco-driver support systems. This paper fills in this research gap by presenting a framework for extending state-of-the-art traffic simulation models with sub models for drivers' compliance to advice from an advisory eco-driving support systems. The developed simulation framework includes among others a model of driver's compliance with the advice given by the system, a gear shifting model and a simplified model for estimating vehicles maximum possible acceleration. Data from field operational tests with a full advisory eco-driving system developed within the ecoDriver project was used to calibrate the developed compliance models. A set of verification simulations used to illustrate the effect of the combination of the ecoDriver system and drivers' compliance to the advices are also presented.

  • 5.
    Olstam, Johan
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Johansson, Fredrik
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics.
    Alessandrini, Adriano
    University of Florence.
    Sukennik, Peter
    PTV Group.
    Lohmiller, Jochen
    PTV Group.
    Friedrich, Markus
    University of Stuttgart.
    An Approach for Handling Uncertainties Related to Behaviour and Vehicle Mixes in Traffic Simulation Experiments with Automated Vehicles2020In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2020, article id 8850591Article in journal (Refereed)
    Abstract [en]

    The introduction of automated vehicles is expected to affect traffic performance. Microscopic traffic simulation offers good possibilities to investigate the potential effects of the introduction of automated vehicles. However, current microscopic traffic simulation models are designed for modelling human-driven vehicles. Thus, modelling the behaviour of automated vehicles requires further development. There are several possible ways to extend the models, but independent of approach a large problem is that the information available on how automated vehicles will behave is limited to today's partly automated vehicles. How future generations of automated vehicles will behave will be unknown for some time. There are also large uncertainties related to what automation functions are technically feasible, allowed, and actually activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. This article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. The driving logics are also linked to assumptions on which logic that could operate in which environment at which part of the transition period. Simulation results for four different types of road facilities are also presented to illustrate potential effects on traffic performance of the driving logics. The simulation results show large variations in throughput, from large decreases to large increases, depending on driving logic and penetration rate.

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  • 6.
    Tsanakas, Nikolaos
    et al.
    Linköping University.
    Ekström, Joakim
    Linköping University.
    Olstam, Johan
    Swedish National Road and Transport Research Institute, Society, environment and transport, Traffic analysis and logistics. Linköping University.
    Estimating Emissions from Static Traffic Models: Problems and Solutions2020In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, Vol. 2020, article id 5401792Article in journal (Refereed)
    Abstract [en]

    In large urban areas, the estimation of vehicular traffic emissions is commonly based on the outputs of transport planning models, such as Static Traffic Assignment (STA) models. However, such models, being used in a strategic context, imply some important simplifications regarding the variation of traffic conditions, and their outputs are heavily aggregated in time. In addition, dynamic traffic flow phenomena, such as queue spillback, cannot be captured, leading to inaccurate modelling of congestion. As congestion is strongly correlated with increased emission rates, using STA may lead to unreliable emission estimations. The first objective of this paper is to identify the errors that STA models introduce into an emission estimation. Then, considering the type and the nature of the errors, our aim is to suggest potential solutions. According to our findings, the main errors are related to STA inability of accurately modelling the level and the location of congestion. For this reason, we suggest and evaluate the postprocessing of STA outputs through quasidynamic network loading. Then, we evaluate our suggested approach using the HBEFA emission factors and a 19 km long motorway segment in Stockholm as a case study. Although, in terms of total emissions, the differences compared to the simple static case are not so vital, the postprocessor performs better regarding the spatial distribution of emissions. Considering the location-specific effects of traffic emissions, the latter may lead to substantial improvements in applications of emission modelling such as dispersion, air quality, and exposure modelling. © 2020 Nikolaos Tsanakas et al.

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