The issues in modelling freight transport at the national level

Jong, Gerard de; Tavasszy, Lóránt; Bates, John J.; Grønland, Stein Erik; Huber, Stefan; Kleven, Oskar; Lange, P. J. de; Ottemöller, Ole; Schmorak, Nora

doi:10.1016/j.cstp.2015.08.002

Cited by 28 publications

(17 citation statements)

References 20 publications

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“…Reis [13] reviewed 17 freight mode choice papers and discussed the variables involved in advanced freight mode choice models. Further, de Jong et al [14] Although some behavioral variables (e.g., reliability and exibility of a mode) are critical for logistical components of a freight model, all the \classic" data categories are available in the data. This is further elaborated in the following section.…”

Section: Datamentioning

confidence: 99%

Freight Modal Policies Toward a Sustainable Society

et al. 2019

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Freight transport policy analysts attempt to shift truck freight movements to rail so as to diminish transportation externalities including environmental costs and safety issues. Therefore, policy-makers need to be aware of the consequences of their decisions beforehand. This study is mainly focused on two policies targeting fuel price and access to rail transportation. A nation-wide freight mode choice model was developed for Iran, and shippers' tendency to choose rail or truck freight transportation was analyzed by considering the shipping time and cost, commodity weight, commodity type, and rail accessibility. Total fuel consumption and air pollution costs were compared in various scenarios. Based on the results, environmental transportation costs are signi cantly reduced as a result of the modal shift from truck to rail freight transportation if the government reallocates gasoline subsidy to the construction of prioritized railroads.

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Section: Datamentioning

confidence: 99%

Freight Modal Policies Toward a Sustainable Society

et al. 2019

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“…As pointed out by de Jong et al [1], it would also be interesting to go a step further in the validation process, performing some "backcasting" (use the model to calculate a "forecast" for a year in the past) or validity testing (asking industry experts and regional planners for their opinion on whether the model behavior and the model results look reasonable). Unfortunately, and especially for models covering international areas, there is a glaring lack of data and available expertise covering all the countries included in large strategic models.…”

Section: Discussionmentioning

confidence: 99%

“…The last map 1 In order to avoid an infinite set of possible combinations, one mode is considered as the reference mode, and its initial α i remains unchanged. Figure 1.…”

Section: Application To the Trans-european Networkmentioning

confidence: 99%

“…The validation step in regional, national or international multimodal freight models is, however, considerably less documented, while it has a very important impact on the level of confidence one can have in a model (de Jong et al [1]). An interesting discussion about the reasons why calibration and validation of such models is difficult can be found in Zhang [2].…”

Section: Introductionmentioning

confidence: 99%

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Calibration and Validation of Strategic Freight Transportation Planning Models with Limited Information

Jourquin¹

2016

JTTs

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Strategic transportation network models are often used as support tools in the framework of decisions to be taken at the policy level, such as the Trans-European Network projects. These models are mostly setup using aggregated or limited data. If their calibration is regularly mentioned in the literature, their validation is barely discussed. In this paper, several modal choice model specifications that make only use of explanatory variables available at the network level are described and applied to a large scale case. A validation exercise is performed at three levels of aggregation. The paper is designed from a strategic transport planning perspective, and does not present new modal choice formulations or assignment procedures. Its main added value is the focus on calibration and validation considerations. Despite the limited explanatory information used, the global performance of the best models can be considered as satisfactory. However, the quality of the models varies from mode to mode, the use of railway transport being the most difficult to predict without more specific input.

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“…Four-step models are calibrated and validated against a chosen base-year, using data from e.g. travel surveys, trip-diaries, statistical freight data or commodity flow surveys [19], [23].…”

Section: Transport Modellingmentioning

confidence: 99%

Supporting Cities’ Emission Mitigation Strategies: Modelling Urban Transport in a Times Energy System Modelling Framework

Forsberg¹,

Krook‐Riekkola²

2017

WIT Transactions on the Built Environment

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The transport sector is a significant emitter of greenhouse gases (GHGs) and air pollutants in urban areas. How the transport sector evolve during the coming decades will have significant impact on the possibilities to meet tough climate and environmental targets. This makes transportation an important part of cities' Sustainable Energy and Climate Action Plans. Still, transportation is somewhat overlooked in many city-level analyses. Energy system optimisation models, like the TIMES modelling framework, are useful tools in identifying energy pathways to reach ambitious energy savings and emission mitigation targets. Based on the identification of urban transport-energy system characteristics, the needs of local governments, and insights from traditional transport models, we propose a partly new representation of the transport sector within a TIMES-City modelling framework, adapting it to the urban transport-energy setting to improve model realism and power of insight. TIMES-City supports analysis of intracity and long-distance passenger and freight transportation, including only the city organisation or the entire administrative city area. Detailed techno-economic-environmental representation of all major existing and emerging modes, technologies and fuels provides basis for consistent long-term analyses. Keywords: energy system optimisation model, urban energy system, urban transports, transportenergy setting, TIMES-City, sustainable energy and climate action plan, sustainable urban mobility plans, local energy policy. INTRODUCTIONThe European Commission (EC) have highlighted cities as the drivers of the European economy, while also emphasizing the importance of well-functioning urban transportation to continue to attract investments and create jobs [1]. However, transportation also bring significant external effects. From a global perspective, emissions of greenhouse gases (GHGs) is top priority, and transportation accounts for more than 20% of energy-related carbon emissions [2], but locally, air pollutants, congestion, noise, and safety are as important [3]. These emissions are attributed to the currently dominant technologies and fossil fuels. Mitigating emissions calls for comprehensive city-level strategies, assessing feasible and effective measures within the entire spectrum of the avoid-shift-improve framework [4].An operations research approach can be useful to help structure the problem, and identify the system environment, its resources, and decision-makers [5]. When approaching problems of systemic character, mathematical models can be powerful tools for 'mental experiments' aimed at exploring system dynamics in an uncertain future [6]. Hence, comprehensive energy system optimisation models (ESOM) can be useful for cities when identifying energy, climate, and clean air strategies.In this study, a TIMES-based ESOM is adapted and applied to the urban scale. Focus is on the urban transport-energy setting, which is somewhat overlooked or neglected in many urban energy system studies. We attempt...

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The issues in modelling freight transport at the national level

Cited by 28 publications

References 20 publications

Freight Modal Policies Toward a Sustainable Society

Freight Modal Policies Toward a Sustainable Society

Calibration and Validation of Strategic Freight Transportation Planning Models with Limited Information

Supporting Cities’ Emission Mitigation Strategies: Modelling Urban Transport in a Times Energy System Modelling Framework

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