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The Aggregate-Disaggregate-Aggregate (ADA) Freight Model System
... To compute modal shares with the estimated model, the aggregate freight flows in tons are then decomposed into smaller units, such as twenty-foot equivalent units (TEU), using a predetermined distribution of the weight per TEU. The Aggregate-Disaggregate-Aggregate (ADA) methodology [24], proposed by Ben-Akiva and de Jong, pushes the concept further by converting zone-to-zone flows into firm-to-firm flows and combining transport chain choice with other logistics decisions (e.g. shipment size, type of loading unit). ...
... This is the author's version which has not been fully edited and content may change prior to final publication. [29] MNL Rd-Rl-Air (✓) Ben-Akiva & de Jong [24] MNL or others Rd-Rl-Sea-Air ✓ ✓ (✓) (✓) De Bok et al. [32] MNL Rd-Rl-IWT ✓ ✓ Jourquin [27] Weighted Logit Rd-Rl-IWT ✓ Jourquin & Beuthe [25] Weighted Logit Rd-Rl-IWT ✓ Newton [31] MNL Rd-Rl-IWT-Sea ✓ Nuzzolo et al. [30] MNL Rd-Rl-Sea-Air ✓ ✓ Rich et al. [10] Weighted Logit Rd-Rl-Sea ✓ Zhang et al. [23] Binary Logit Rd-Rl ✓ Our model Weighted Logit Mixture Rd-Rl-IWT ✓ ✓ a Rd = road, Rl = (intermodal) rail, IWT = inland waterway transportation, Air = airplane, Sea = (short-)sea. ...
... Among the works reviewed previously, the ADA methodology is the most flexible to take heterogeneity into account as it allows the use of a Mixture model to capture variations of preferences or correlation between alternatives [24]. The method also estimates various coefficients according to the commodity type being shipped. ...
Understanding the modal split in freight transportation is a key factor for the successful implementation of innovations. Mode choice models should then be as representative of reality as possible. The use of disaggregate shipment data can help to achieve it. However, shipment data are often unavailable due to confidentiality issues. As a result, numerous models using only aggregate data have been developed, but their capacity to capture heterogeneity in preferences remains limited. In this paper, we propose a Weighted Logit Mixture model to estimate heterogeneous mode choice preferences of shippers directly from aggregate data. The proposed Weighted Logit Mixture is applied to a case study along the European Rhine-Alpine corridor and allows to estimate the probability distribution of the cost sensitivity among the population. The estimation results show that there exists a substantial variation of the cost sensitivity regarding intermodal transport. The proposed methodology is also compared to a state-of-the-art Weighted Logit model to assess its potential. This reveals that the proposed Weighted Logit Mixture exhibits at least a similar predictive power to the benchmark while achieving a better description of the population’s preferences that enables policy-makers to take better informed decisions and appropriate actions.
... Some of the state-of-the-art freight generation models [3][4][5][6][7][8][9][10][11][12] form the basis for freight demand modelling. Most of these freight generation models are developed using linear regression [4,7,8,[12][13][14][15][16] and econometric models, while a few are developed using computational approaches such as artificial neural networks (ANN) [16]. ...
... The works on freight distribution follow several models and algorithms in the literature. Many studies [3,8,10,[13][14][15][17][18][19][20][21][22][23][24] use gravity models with a few variations. Some of the advanced models such as fractional split distribution models [11] are also used. ...
... Some of the advanced models such as fractional split distribution models [11] are also used. Spatial computable general equilibrium models [23] and input-output tables for the regions [3,4,8,10,11,14,15,19,[24][25][26][27], are used in developing combined freight generation and distribution models. A summary of the reviewed literature is shown in Fig. 1. ...
India does not have a formal model for forecasting interstate freight travel demand perhaps because of lack of data or resource constraints. The authors make an attempt in this study to develop freight travel demand models using public sources of data. They use the data on freight productions and attractions of the states, and their distance slab-wise commodity distribution diagram published in the Total Transport System Study Report performed by RITES Ltd. They calibrate multiple regression models for freight generation and gravity models for freight distribution. They use tri-proportional algorithm for gravity model calibration. The results of freight distribution are compared with Preliminary Engineering cum-Traffic study (PETS) for Eastern Dedicated Freight Corridor (DFC) for validating the models.
... First, the order costs, which are depending on the commodity type and the shipment size. The cargo type is considered, both in research (Ben-Akiva and de Jong, 2008;Cosemans, 2010;Maes, 2013) and in practice, as a non-influencing variable for order costs. While transport costs -distance and time dependent are influenced by the cargo types. ...
... Both the capital costs of the goods during transit and in inventory are not considered as being influenced by the cargo type (Ben-Akiva and de Jong, 2008;Maes, 2013). However, the inventory costs themselves are on their turn influenced by the cargo type. ...
... Freight transport is however a concern of many actors, i.e. shippers, receivers, carriers, administrators, residents, commuters and customers (Tanigushi et al., 2012). Only few models are capable of simulating agents in a multimodal freight framework (Baindur and Viegas, 2011;Ben Akiva and de Jong, 2008;Holmgren et al., 2012, Maes, 2013Roorda et al., 2010). However, the modelling of the decisions of each one of all these actors -on different decision levels -is complex and not always appropriate. ...
Multimodal transport is considered as an important solution to tackle the sustainability concerns of the freight transport system. Multimodal transport is the movement of goods by at least two different modes of transport. Governments have set goals and taken actions to promote and stimulate multimodal transport. Despite the awareness and actions, the modal split has remained constant throughout the last decade in Belgium and Europe. A large body of research that demonstrates the economic and sustainability benefits of multimodal transport exists; it either compares the transport modes directly or focuses on multimodal transport of containerized goods. However, other cargo types are used in the supply chain as well, and they are, to the best of our knowledge, not considered in the research on multimodal transport and transport modelling. The incorporation of different commonly used cargo types in a framework that assesses the economic and sustainability potential of a modal shift of freight is new and needed to address the sustainability challenges which the freight transport sector is facing. This incorporation gave rise to the research of this thesis, which aims to answer the following question: What is the potential for multimodal transport taking into account different cargo types in transport modelling?
The cargo type is the classification, based on its appearance, of a load of goods that is transported or is intended to be transported. The cargo type can consist of either liquid or solid bulk without packaging, standardized units (such as pallets or containers), or unstandardized units (such as parcels). The first section of this thesis focuses on the importance of the cargo type in multimodal transport. In practice, the transport operations and decisions in the supply chain are influenced by the cargo type. The costs related to transshipment, inventory and transport are highly affected by it. Therefore, the different cargo types should be considered in the modal choice analyses (chapter 2).
The second section examines the potential for a modal shift of different cargo types. Special focus is given to the sustainability of the transport system in Belgium. First, an initial feasibility analysis was performed for a modal shift of palletized freight towards the inland waterways. The Location Analysis Model for Barge Transport of Pallets (LAMBTOP) was developed within this PhD research to do so. The model identifies the optimal transshipment locations, as well as the palletized transport flows that can be cost-efficiently shifted towards inland waterway transport. First, the model is applied to the flows of palletized building materials within Belgium (chapter 3). In a second stage, LAMBTOP was extended by considering the total logistics costs to include the reliability of the transport mode and the depreciation, shelf-life and value of the goods. In addition, the methodology was enlarged to the European scale (chapter 4). Cost-efficient transport flows were found, thus showing the potential of this market.
A second model was developed, called the TRansport Agent-BAsed Model (TRABAM), to consider different commonly used cargo types. The model incorporates the cargo type into the decision process with regards to the vehicle and mode choice. A differentiation is made between five cargo types (liquid bulk, solid bulk, containers, pallets and mobile units), as they all either positively or negatively influence the feasibility of a modal shift. TRABAM contributes to the MATSim freight extension by adding the multimodal transport and the cargo type used to it. By modelling the transport flows according to the commodity type and cargo type used between 4.934 zones subdividing the Belgian territory, TRABAM is more disaggregated than the existing freight models for Belgium (chapter 5). The shipments are generated via regression techniques based on aggregated data and economic and demographic data (chapter 6). The mode choice decisions are taken by the agents in the model, which are the Belgian carriers. TRABAM considers real-world Belgian logistic service providers, including their existing vehicle fleet and depot locations. In addition, passenger car flows are imbedded in the model as a base layer and for peak-hours. Import, export and transit flows are assigned to the agents representing foreign logistic service providers. Each domestic shipment is assigned to an agent that optimizes its routing, stop sequence, vehicle and mode choice and its departure time via an iteration process (chapter 7). The output consists of information on the movements of individual freight vehicles throughout time and space on a one-day basis. The multimodal potential for different cargo types is calculated accordingly (chapter 8). Containers, solid bulk and liquid bulk show the highest shares for rail and inland waterway transport (29,6%, 35,8% and 48,9% of the volume, respectively). The pallets on the inland waterways have a potential of 4,3%. When the variable costs for road transport would increase by 10%, it leads to a limited increase of 0,8% of the rail and inland waterway transport share. Pallets (+2,4%), solid bulk (+3,9%) and liquid bulk (+5,9%) are more sensitive to road transport cost increases. The output is also linked to vehicle-, traffic condition-, environment-, loading rate- and infrastructure-dependent emission factors. Two applications, i.e., air pollution in the Brussels Metropolitan Region (chapter 9) and off-hour deliveries to Walloon supermarkets (chapter 10) – are presented. TRABAM is capable of answering pertinent freight transport research challenges.
... Some of the state-of-the-art freight generation models [3][4][5][6][7][8][9][10][11][12] form the basis for freight demand modelling. Most of these freight generation models are developed using linear regression [4,7,8,[12][13][14][15][16] and econometric models, while a few are developed using computational approaches such as artificial neural networks (ANN) [16]. ...
... The works on freight distribution follow several models and algorithms in the literature. Many studies [3,8,10,[13][14][15][17][18][19][20][21][22][23][24] use gravity models with a few variations. Some of the advanced models such as fractional split distribution models [11] are also used. ...
... Some of the advanced models such as fractional split distribution models [11] are also used. Spatial computable general equilibrium models [23] and input-output tables for the regions [3,4,8,10,11,14,15,19,[24][25][26][27], are used in developing combined freight generation and distribution models. A summary of the reviewed literature is shown in Fig. 1. ...
Freight modelling is very important to understand how freight moves from one place to another place. Due to data and other resource constraints like time and cost of conducting surveys, freight models are not available for various countries. Overcoming these constraints, freight generation and distribution models are developed using secondary sources of data. The primary motivation of the study is to understand the different factors on which freight generation depends upon. This is accomplished by building ordinary least squares regression models. Net State Domestic Product, Area, Agricultural Area, Secondary sector workers, Petroleum and Electricity Consumption of the Traffic Analysis Zones are the factors that affect freight generation. The secondary motivation of the study is to estimate the friction factors for the gravity model by calibration using three-dimensional furness procedure, being used for the first time in freight distribution. The important contributions of this paper are an improved understanding of freight movement patterns at the regional level and the estimation of friction factors that can be used for predicting future freight movements when origin–destination data are not available.
... The main feature of recent national freight transport models in Europe is the incorporation of a logistic component (module) in the traditional freight demand-modelling framework (de Jong et al. 2013). Logistics decisions of firms are incorporated in the modelling process often based on shipment size optimization theory. 1 According to this theory, firms are assumed to minimize total annual logistics costs by trading-off inventory holding costs, order costs and transport costs. ...
... Such logistics modules have been developed for the national freight models of Norway, Sweden (SAMGODS model) 3 , Denmark and Flanders (see Ben-Akiva and de Jong, 2013), within the overall framework of the aggregate-disaggregate-aggregate (ADA) freight transport model. 4 The current logistic modules in these countries, however, lack two main elements. ...
... The Swedish national freight transport model-SAMGODS-is one of the models that applies the aggregate-disaggregate-aggregate (ADA) framework (see: de Jong and Ben-Akiva, 2007; Ben- Akiva and de Jong, 2013). 16 This framework is also used in the national freight transport models of Norway and Denmark and the model for the Flanders Mobility Masterplan (Belgium). ...
This paper presents estimation results for models of transport chain and shipment size choice, as well as an implementation of the estimated disaggregate models (for two commodity groups), in the context of the national freight transport model for Sweden. The new model is a disaggregate and stochastic (logit) model, whereas the existing Swedish national model is deterministic. One advantage of the new approach is that it bases the underlying behavior of shippers on a stronger empirical foundation (that is micro-data from the Swedish Commodity Flow Survey, CFS). Another advantage is that it overcomes a well-known disadvantage of deterministic models that lead to implausibly large responses to changes in scenario or policy variables. Although estimation and implementation of aggregate stochastic models were done before, in the context of a national freight transport forecasting model, we think this is the first implementation of disaggregate freight transport chain and shipment size models estimated on choice data for individual shipments, certainly in Europe. We carried out a number of model runs with both versions of the implemented model to compare elasticities and found that transport cost and time elasticities for tonne-km are smaller (in absolute values) in the disaggregate stochastic model than in their deterministic counterparts.
... Samgods v.1.2 is a Swedish national freight transport model used for forecasting and planning analyses (Bergquist et al. 2020;De Jong and Baak 2020) and is a so-called aggregate-disaggregate-aggregate model (Ben-Akiva and de Jong 2013). Samgods includes road, rail, sea, and air transport and covers all Swedish freight flows including domestic, import, export, and transit flows. ...
... not restricted by vehicle fleet or infrastructure capacity), while the supply of rail transport is constrained by limited capacity on the Swedish rail network. One fundamental assumption for Samgods is that each freight transport actor makes logistics decisions that minimize its logistics cost per transport flow (see Eq.1) (Ben-Akiva and de Jong 2013). The model calculates the logistic solution that minimizes logistics costs for each freight flow for an exogenous freight transport demand by optimizing the choice of transport chains, vehicle types and shipment size, etc. ...
... Examples of this approach are the strategic freight models of The Netherlands (BasGoed; see or Flanders (see Grebe et al., 2016). • An Aggregate -Disaggregate -Aggregate (ADA) model (see de Jong and Ben-Akiva, 2007; Ben-Akiva and de Jong, 2013). This model consists of three steps (see Figure 2). ...
... Structure of the ADA model (Source: Ben-Akiva andde Jong, 2013). ...
For the preparation of a new traffic forecast for several time horizons up to the year 2040 and beyond (Verkehrsprognose Österreich, VPÖ 2040+) an up-to-date transport model is necessary. Currently this new national transport model Austria (Verkehrsmodell Österreich, VMÖ) is developed.
The passenger model will be disaggregated tour-based model with 5 basic steps and some extensions for special applications, like for instance tourist traffic. The number of zones will be approximately 6000. In the model a special focus is on incorporating recent trends in mode choice like “park and ride” and other multimodal chains. The freight part of the model will be an Aggregated - Disaggregated - Aggregated (ADA) model with three steps: (1) the results of an input-output-model are transformed into firm-to-firm flows, (2) the choice of shipment size and transport chain is modelled and (3) the OD relations are aggregated for the individual modes and assignment to the networks.
For individual transport with passenger cars and road freight, a quasi-dynamic road transport assignment will be developed. Public transport assignment is based on timetables. For the forecasts of travel demand for future years a pivot-point approach (with the changes) on the base matrices will be applied.
... Examples of this approach are the strategic freight models of The Netherlands (BasGoed; see or Flanders (see Grebe et al., 2016). • An Aggregate -Disaggregate -Aggregate (ADA) model (see de Jong and Ben-Akiva, 2007; Ben-Akiva and de Jong, 2013). This model consists of three steps (see Figure 2). ...
... Structure of the ADA model (Source: Ben-Akiva andde Jong, 2013). ...
For the preparation of a new traffic forecast for several time horizons up to the year 2040 and beyond (Verkehrsprognose Österreich, VPÖ 2040+) an up-to-date transport model is necessary. Currently this new national transport model Austria (Verkehrsmodell Österreich, VMÖ) is developed. The passenger model will be disaggregated tour-based model with 5 basic steps and some extensions for special applications, like for instance tourist traffic. The number of zones will be approximately 6000. In the model a special focus is on incorporating recent trends in mode choice like “park and ride” and other multimodal chains. The freight part of the model will be an Aggregated - Disaggregated - Aggregated (ADA) model with three steps: (1) the results of an input-output-model are transformed into firm-to-firm flows, (2) the choice of shipment size and transport chain is modelled and (3) the OD relations are aggregated for the individual modes and assignment to the networks. For individual transport with passenger cars and road freight, a quasi-dynamic road transport assignment will be developed. Public transport assignment is based on timetables. For the forecasts of travel demand for future years a pivot-point approach (with the changes) on the base matrices will be applied.
... Fernandez, de Cea, and Soto (8) further improve the shipper-carrier model and solve for the equilibrium between shippers and carriers over a multimodal network. Ben-Akiva and de Jong (19) introduce a novel approach in which commodity generation, commodity distribution, and route assignment are carried out at an aggregate level whereas the mode share process is at a disaggregate level. The model of Ben-Akiva and de Jong (19) is known as the "aggregate-disaggregate-aggregate" model. ...
... Ben-Akiva and de Jong (19) introduce a novel approach in which commodity generation, commodity distribution, and route assignment are carried out at an aggregate level whereas the mode share process is at a disaggregate level. The model of Ben-Akiva and de Jong (19) is known as the "aggregate-disaggregate-aggregate" model. ...
Canada signed the Canada–European Union (EU) Comprehensive Economic and Trade Agreement (CETA) in October 2016, which was later ratified by the European Parliament in February 2017. This agreement enables Canadian establishments to trade openly with EU members. Despite the Canadian government’s economical analysis, no study has been undertaken to investigate the impact of CETA on Canada’s transportation network. The objective of this paper is to assess the potential impact of CETA on the Canadian transportation network by estimating origin–destination trade flows, mode shares, and transportation flows before and after the agreement. Annual provincial commodity flows are obtained from a computable general equilibrium model. Mode shares are determined based on US commodity flow survey data. Finally, changes in freight flows by the rail and truck modes as a result of CETA are examined. The model results indicate an increase in freight movement to and from Eastern Canada and a decrease in trade movement near the US–Canada borders and Western Canada.
... A lack of data can hinder accurate demand modelling, leading to resource wastage (Abdelwahab & Sargious, 1992;Lu et al., 2021). Global forecasting methods and decision support systems aid freight flow prediction (Doustmohammadi et al., 2016;Ben-Akiva & De Jong, 2013). Developing countries like India also invest in freight transport modelling, with disaggregate and tour models proving useful (Venkadavarahan et al., 2020;Dhonde & Patel, 2021). ...
Advancing urban transportation in Bangladesh hinges on harnessing technology and data. The goal is twofold: drive economic growth and enhance transport services for a sustainable future. A robust data infrastructure, informed by global smart city insights, is essential to transform Bangladesh's transportation system into a model of efficiency and innovation. Despite investing heavily in road infrastructure, Dhaka, the capital of Bangladesh, continues to struggle with poor traffic performance. Thus, this study endeavors to review the potential of integrating data-driven methodologies into various aspects of transportation, namely transportation planning and management, smart public transit systems, traffic operation and management, freight operation and management, and pavement maintenance systems. To achieve this, the study draws inspiration from successful and efficacious implementations of intelligent transportation systems fortified with advanced ICT tools across developed countries. These state-of-the-art adaptations of advanced methodologies can lead to evidence-based decision-making, sustainable urban development, and improved transportation efficiency. This paper also presents strategic recommendations that outline a roadmap for Bangladesh to achieve its vision of a technologically advanced and seamlessly efficient transportation ecosystem by 2041.
... Integrated models are network-based, often addressing issues such as the creation of the infrastructure system, making a political decision, establishing a new system (Tavasszy et al. 2000, Comi et al. 2021. There are also studies in which the two methods are used together (Albino et al. 2011, Ben-Akiva andJong 2013). ...
This study aims to develop urban logistics plan to increase its applicability by utilizing a sophisticated software tool which allowed one to effectively create urban logistic plan through testing alternative planning scenarios. The methodological contribution of the study becomes evident in the sections of establishing generation-attraction models with discrete data, scenario definition, and development of production-testing methods. The model is applied to develop the urban logistics model for İzmir. The main objective is to organize the logistics system operating in the base case of İzmir, to propose new systems and to develop applications that closely follow the technology. In line with this goal, comprehensive multidimensional studies covering the whole of İzmir have been carried out. The study may contribute to successful development of urban logistics plans by providing a real case study.
... The logistic optimization is described in De Jong and Baak (2020). The fundamental principles behind the method can be found in Ben-Akiva and de Jong (2013) and De Jong and Ben-Akiva (2007). Limitations in railway capacity are handled via a special module which, in the event of congestion on certain sections, seeks alternative transport arrangements that relieve these congested sections of the railway at the least possible alternative cost. ...
... By new empirical methods (tracking) and the associated increased availability of disaggregated data, these models allow an explicit consideration of feedback from individual decision-making processes, decision-making levels and market interactions. This increases the measure and behaviour sensitivity of these models for urban transport planning (Ben-Akiva et al. 2013). There are three types of disaggregated freight transport models: goods flow-based, tour or vehicle-based and hybrid models. ...
Shared logistics (SL) is an increasingly critical solution to the challenges of urban
logistics, particularly in the context of limited resources, the energy crisis, and environmental
concerns. This study investigates the adoption of shared logistics among logistics service
providers in Poland. While SL is considered a promising strategy for addressing challenges
such as resource scarcity and environmental concerns, only 27.4% of surveyed companies
reported using it. Results suggest that small and micro-sized companies are more reluctant to
adopt shared logistics, and education and awareness-raising efforts may be necessary to
promote its adoption. The study provides valuable insights into the current and potential usage
of SL in Poland, identifies barriers to its adoption and potential opportunities for promoting its
use
... In particular, many authors have focused on developing advanced logistics modules that accurately reflect the logistics decision-making processes in the freight transport system (de Jong et al., 2013b). For example, the Norwegian National Freight Transport Model (Anne Madslien et al., 2015) uses a so-called aggregate-disaggregate-aggregate approach by Ben- Akiva & de Jong (2013). Here, aggregate production and consumption levels are translated to disaggregated firm-level transportation demands. ...
To achieve carbon emission targets worldwide, decarbonization of the freight transport sector will be an important factor. To this end, national governments must make plans that facilitate this transition. National freight transport models are a useful tool to assess what the effects of various policies and investments may be. The state of the art consists of very detailed, static models. While useful for short-term policy assessment, these models are less suitable for the long-term planning necessary to facilitate the transition to low-carbon transportation in the upcoming decades. In this paper, we fill this gap by developing a framework for strategic national freight transport modeling, which we call STraM, and which can be characterized as a multi-period stochastic network design model, based on a multimodal freight transport formulation. In STraM, we explicitly include several aspects that are lacking in state-of-the art national freight transport models: the dynamic nature of long-term planning, as well as new, low-carbon fuel technologies and long-term uncertainties in the development of these technologies. We illustrate our model using a case study of Norway and discuss the resulting insights. In particular, we demonstrate the relevance of modeling multiple time periods, the importance of including long-term uncertainty in technology development, and the efficacy of carbon pricing.
... As most African countries attempt to modernize their railway system to meet international standards [10], the use of demand models is becoming important in the estimation of trip generation, distribution, mode choices, and traffic assignments. Depending on data availability, freight transport models are developed for purposes, including [8] forecasting demand in the medium to long run under various scenarios and can also test policy measures, such as road user charging. Modeling freight demand is premised on the need to move commodities [27] and a good number of widely documented modeling software packages are available for modeling traffic (passenger and freight) demand. ...
Ghana's once vibrant railway system is presently in a state of disrepair as a result of neglect and underfunding over the years; from an initial network size of 947 km in 1960 to an operational rail line of just 160 km in 2020. The Ghana railway sector's past performance is reviewed together with 5 other countries, namely; Nigeria, Kenya, South Africa, Germany, and the United Kingdom, as well as the prospects of the industry to the Government's intention. Four (4) indicators were considered in the assessment, they are, the effectiveness of the available rail line, total goods transported by rail, total passengers that traveled by rail, and accessibility to rail service. Relatively, Ghana showed the highest decline in the effectiveness of available rail lines, from 68% in 1980 to 16.9% in 2020. Again, Ghana and Nigeria experienced a substantial decrease in freight volumes transported (81%) between 1990 and 2020, whiles South Africa, Germany, and the United Kingdom witnessed increases averaging 100,000 million ton-km annually over the same period. Accessibility to railway services has consistently decreased over the years; from service access of 29.6% in 1960 to 0.6% in 2020 tells the awful state of the railway sector. However, the prospects of investing in a modernized railway system appear good as the government's drive to industrialize the country continues and new mineral deposits are exploited. The sector is undergoing restructuring to increase private sector participation in the delivery of rail transport services and to stimulate the country's socio-economic development.
... European modelers led early developments in this type of modeling. Roodra et al. (2010) described some of these modeling efforts, while more recent model applications are described in, for example, Cavalcante and Roodra, 2013;Holmgren and Ranstedt, 2017;Ben-Akiva and de Jong, 2013;Burgholzer et al., 2013;and Reis, 2014. Indeed, the state-of-the-art in freight modeling is still undergoing development even at the enterprise level. ...
... A description of the logistic optimization can be found in de Jong and Baak (2020). The fundamental model principles can be found in Ben-Akiva and de Jong (2013) and de Jong and Ben-Akiva (2007). ...
In this paper we present a method for evaluating social benefits of electric roads and apply it to the Swedish highway network. Together with estimated investments costs this can be used to produce a cost benefit analysis. An electric road is characterized by high economies of scale (high investment cost and low marginal cost) and considerable economies of scope (the benefit per kilometre electric road depends on the size of the network), implying that the market will produce a smaller network of electric roads, or charge higher prices for its use, than what is welfare optimal. For this reason, it is relevant for governments to consider investing in electric roads, making the cost-benefit analysis a key decision support. We model the behaviour of the carriers using the Swedish national freight model system, SAMGODS, determining the optimal shipment sizes and optimal transport chains, including mode and vehicle type. We find that if the user charge is set as to optimize social welfare, the revenue will not fully cover the investment cost of the electric road. If they are instead set to optimize profit, we find that the revenue will cover the costs if the electric road network is large enough. Electric roads appear to provide a cost-effective means to significantly reduce carbon emissions from heavy trucks. In a scenario where the expansion connects the three biggest cities in Sweden, emissions will be cut by one-third of the overall emissions from heavy trucks in Sweden. The main argument against a commitment to electric roads is that investment and maintenance costs are uncertain and that, in the long run, battery development or hydrogen fuel cells can reduce the benefit of such roads.
... Modal choice is one of those relevant decisions. Only few models are currently capable of simulating agents in a multimodal environment (Baindur and Viegas, 2011;Ben Akiva and de Jong, 2008;Holmgren et al., 2012;Roorda et al., 2010). Modal choice is included in TRABAM as part of the MATSim iteration process, where carriers are optimizing their day-plans by trying different available transport modes. ...
Freight transport is necessary to sustain economic activities and current lifestyles. However, the huge amount of freight movements is generating also negative effects, like congestion, air pollution, noise nuisance, climate change, accidents, etc. Both private and public decision makers are becoming more and more aware of those negative effects, and different incentives are applied. Measuring the negative effects and measuring the impact of such incentives is crucial to increase the sustainability of freight transport. This paper proposes a part of the development an agent-based freight transport model for Belgium, called TRABAM. TRABAM has the aim to improve external cost calculations. The model uses Belgian carriers as agents. These agents are multimodal, as the model considers road, rail and inland waterway transport. This paper focusses on the agents, being the Belgian carriers. Required assumptions and as well as a detailed description of the Belgian carriers are given in this paper. Transport contracts are assigned to those agents based on probability function considering proximity and notoriety of the carriers. As TRABAM is still under development, no validated results can be presented.
... Regional transit is also identified. We like to emphasize that we do not attempt to link origin-destination (OD) flows into (potentially multimodal) transport chains that go from the place of production to the place of consumption of the goods (see, e.g., Ben-Akiva and de Jong, 2013). This requires applying a logistics model. ...
Statistical information on freight transport does not adequately capture developments in practice. This paper applies a Bayesian framework to integrate statistics on regional freight transport with data on regional trade. The resulting data describe freight transport in the Netherlands at the NUTS 3 regional level by NSTR commodity groups, and by type of flow. We distinguish intraregional transport, regional exports and imports, international exports and imports, and regional transit. The contribution of this paper is that conditions driving regional transport flows are reflected more clearly in the data. The results show the relative importance of logistic processes in regional transport in the Netherlands. Similarly, specific regional production patterns are also reflected in the data. The results contribute to the development of more evidence-based, region-specific freight strategies.
Full paper available: https://authors.elsevier.com/a/1aDBE3Rd3ujw8a
... These questions cannot be answered by traditional freight transportation models. In recent years, many transportation researchers realized this necessity to include logistics in freight transportation models (Tavasszy (2006), Ben-Akiva and De Jong (2008), Rothengatter (2008)). The importance of the interface between economic activity and transportation has always been a main focus of transportation researchers (see Manheim (1979), p.5). ...
The study contributes to fill the gap between freight transportation analysis and logistic research. It describes the model SYNTRADE, a simulation model that reproduces logistic structures in the German food retailing sector. Logistic decisions and their interdependencies are simulated based on heuristics from the field of logistic optimization. The model provides the possibility to analyze changes in logistics and freight transport demand on a company, as well as on an overall sector level.
... Therefore, researchers tried new approaches with disaggregated models. A first step in this direction is the model proposed by Ben Akiva and de Jong in two articles (Ben-Akiva and de Jong (2013) and de Jong and Ben-Akiva (2007)): the Aggregated-Disaggregated-Aggregated (ADA) model. It disaggregates input data according to number of employees in order to get annual firm-to-firm flows. ...
Inside a logistic system, actors of the logistics have to interact to manage a coherent flow of goods. They also must deal with the constraints of their environment. The article's first goal is to study how macro properties (such as global performance) emerge from the dynamic and local behaviors of actors and the structure of the territory. The second goal is to understand which local parameters affect these macro properties. A multi-scale approach made of an agent-based model coupled with dynamic graphs describes the system's components, including actors and the transportation network. Adaptive behaviors are implemented in this model (with data about the Seine axis) to highlight the system's dynamics. Agent strategies are evolving according to traffic dynamics and disruptions. This logistic system simulator has the capacity to exhibit large-scale evolution of territorial behavior and efficiency face to various scenarios of local agent behaviors.
... -Modelling frameworks that reconcile micro (firm level), meso (segmented) and macro (zonal aggregates) scales of the system (Tavasszy et al., 1998;Roorda et al., 2010;Liedtke and Friedrich, 2012;Ben-Akiva and De Jong, 2013). -Interpretation and use of micro level optimization models to develop a better descriptive understanding of freight transport choices (De Jong and Ben-Akiva, 2007;Combes, 2012;Halim et al., 2016;Holguín-Veras, 2015;Anand et al., 2016;You et al., 2016). ...
This editorial introduces the papers of a special issue of the journal on freight transport modelling. Together, 9 papers present recent advances in 3 key areas of descriptive and predictive freight modelling: activity chaining, joint modelling of choices and segmentation of users. Next to a methodological contribution in one of these 3 areas, several papers also present empirical findings that are of broader relevance for different choice problems, industries and countries.
... In recent years, several activity-based and rule-based models have been adopted for mode choice and route assignment applications. For example, Ben-Akiva and de Jong propose an aggregate-disaggregate-aggregate model (9), in which commodity generation, commodity distribution, and route assignment are carried out at an aggregate level, whereas the mode choice process is at a disaggregate (activity-based) level. Arentze and Timmermans' developed a model referred to as ALBATROSS, for A Learning-Based, Transportation-Oriented Simulation System, which uses activity-based logic and decision-trees to model trip making behavior (10). ...
In recent years, improvements in pipeline capacities and connectivity have been inhibited by environmental and political concerns (e.g., the Dakota and Keystone XL pipeline expansion projects). This has resulted in a greater dependency on rail transport, and this modal shift of crude oil from pipeline to rail is likely to become more pronounced in the future. Therefore, there is a need to assess the impacts of future changes in pipeline/rail network connectivity, modal attributes, and shipment protocols, on the expected pattern of crude oil shipments. This paper presents a rule-based mode split and route assignment model that reflects real-world allocation, assignment, and apportionment rules. The decision-making process underlying this model is the shipper, who is prioritized by the carrier when there is limited pipeline capacity available. The proposed algorithm allows for the inclusion of crude oil shipments and the pipeline network into conventional freight demand models by capturing the complex interactions of crude shippers, pipeline carriers, and regulatory bodies. This paper demonstrates how the model can be used to predict changes in Canadian crude oil flow patterns and mode shares subject to changes in specific transportation network attributes or crude oil demands. © National Academy of Sciences: Transportation Research Board 2018.
... The existing literature concerning road freight demand has mainly focused on modelling commodity or vehicle movements in terms of certain explanatory variables. Demand modelling has been used for different purposes, such as testing transport policy measures, forecasting transport demand, or predicting the impacts of the provision of new infrastructure (Ben-Akiva et al. 2008). According to Nuzzolo et al. (2013), two main technical approaches have been adopted to that end: behavioral models and macro-economic models (both joint and partial share specifications). ...
During the last few decades, the European Union has promoted distance-based charges on heavy goods vehicles for the use of main roads as a means of funding the infrastructure and internalizing external costs. This approach has progressively been implemented by many European nations. From a macro perspective, this paper explores the impact of heavy vehicle tolling on road freight demand in the countries where it has been implemented. To that end, we develop a dynamic panel data methodology to analyze the evolution over time of road freight traffic and modal share for the European countries having implemented a nationwide per-km truck tolling policy. The results show that, with the exception of very specific cases, there is not strong evidence that heavy vehicle tolling had either influenced road freight volume or promoted the shift of freight to alternative modes. In addition, the limited effect of this charging policy has been partly or mostly counteracted by the evolution of other explanatory factors such as economic growth and the expansion of high capacity networks.
... The case study is carried out within the framework of the AggregateDisaggregate-Aggregate (ADA) model of Ben-Akiva and de Jong [2], an activitybased freight transportation model. The ADA-model is originally developed for the Netherlands but the concepts have also been applied to Flanders [15]. ...
In order to improve the competitive position and efficiency level of intermodal transport, consolidation of freight flows is often suggested. Bundling networks require cooperation between multiple partners in the intermodal transport chain. In this context, the question rises how benefits may be allocated fairly among the participants in the cooperation. A great deal of scientific literature reports on the behavior of allocation methods in collaborations between shippers or carriers making use of unimodal road transport. However, research on cost or savings allocation methods in intermodal transport is scarce. Moreover, since various types of vessels with differing price structures may be considered in intermodal barge transport, the application of allocation mechanisms is not so straightforward compared to a unimodal environment. The main contribution of this paper is thus to provide a first insight in the complexity of sharing cost savings fairly amongst shippers who bundle freight flows in order to reach economies of scale in intermodal barge transport. By applying three different allocation methods, a comparison is made between simple and straightforward allocation mechanisms and more advanced techniques based on cooperative game theory. Special attention is also paid to the stability of the found solutions. The situation of three-, four- and five-partner coalitions is investigated, both for partners with an equal and an unequal amount of shipments. For these six situations, the case of a common barge trajectory and a common end terminal are studied.
Freight demand models typically use a series of sub-models that relate several inputs to model outputs, without considering the uncertainty of typical data sources used in the model development process. Hence, the uncertainty of freight demand model outputs is typically not characterized, making it difficult to understand the robustness of the model results, or how the rigour of the results might be improved with additional data. This paper proposes a formal five-step framework to analyze the effects and propagation of input uncertainty from datasets used during model development on the uncertainty of the outputs in a freight demand model driven by exogenous economic forecasts. The framework is applied to a Canadian commodity-based freight demand model, inspired by the Aggregate-Disaggregate-Aggregate (ADA) model, used to analyze the effects of the Comprehensive and Progressive Trans-Pacific Partnership (CPTPP) on Canada's trade infrastructure. In this application of the framework, uncertainty for input datasets used to develop three sub-models is introduced and a set of outputs is simulated through repeated simulation. Descriptive statistics and rank error measures are used to access the uncertainty of the outputs. The results suggest that the case study model performs with adequate robustness in terms of aggregated outputs and for larger trade partners, while some specific disaggregate outputs and scenarios with smaller trade partners are less robust.
Despite high ambitions, policies for a modal shift in Europe have largely been unsuccessful. Part of the explanation relates to the inelasticity of freight transport demand. Understanding the demand elasticity of freight transport is important to design and appraise policies for external cost reductions in the transport sector. There have been many studies focused on estimating the elasticity of demand for short-sea shipping, a mode which policy makers have often aimed to strengthen to facilitate a modal shift from road freight. The objective of this review is to build upon the available literature by presenting and comparing estimated elasticities and to demonstrate the state of evidence through the application of two methodological approaches. Our review shows that there is a surprising degree of variation in elasticity estimates, part of which can likely be explained by differing methodological approaches. Applying a deterministic cost-minimising freight transport model and a stochastic multinomial logit approach based on responses from the Swedish Cargo Flow Survey, we demonstrate the inelasticity of Swedish maritime freight flows and provide suggestions for future research and policy discussions. For future studies of maritime transport demand elasticities to arrive at reliable and policy-relevant results, we highlight the need for combined and pluralistic methodological approaches and an increased use of real-world data.
This paper presents an analysis of the potential impacts of large-scale adoption of driverless trucks on transport patterns and system costs for a national freight transport system with Sweden as a case study. The analysis is performed by extending the application domain of the Swedish national freight transport model Samgods to analyze two types of driverless truck scenarios. The first scenario represents a full adoption of driverless trucks that can operate the complete road network and thereby substitute manually driven trucks. In this scenario, road transport tonne-kilometers on Swedish territory increase by 22%, vehicle kilometers traveled by trucks increase by 35% and annual total system costs decrease by 1.7 B€ compared to a baseline scenario without driverless trucks. In the second scenario, the current fleet of manually driven trucks is complemented by driverless trucks that can operate on major roads between logistics hubs, but not in complex traffic environments like urban areas due to a limited operational design domain. This may be an initial use-case for driverless trucks operating on public roads. In this scenario, road tonne-kilometers increase by 11%, truck vehicle kilometers traveled increase by 15%, and annual total system costs decrease by 1.2 B€ compared to the baseline. For both scenarios, the impacts of driverless trucks vary significantly between commodity types and transport distances which suggests heterogeneity of benefits of automated driving between different types of freight flows. A sensitivity analysis is performed in which the costs for driverless truck operations is varied, and for the second scenario, also which parts of the road network that driverless trucks can operate are varied. This analysis indicates that the magnitude of impacts is highly dependent on the cost level of driverless trucks and that the ability for DL-trucks to perform international, cross-border transport is crucial for achieving reductions in system costs. An overarching conclusion of the study is that driverless trucks may lead to a significant increase in road transport demand due to modal shifts from rail and sea as a result of the improved cost performance of road transport. This would further strengthen the need to decarbonize road transport to meet non-negotiable climate targets. Important topics for future research include assessing potential societal costs related to driverless trucks due to infrastructure investments and negative externalities such as increasing CO2 emissions and congestion.
Freight transport modelling has seen many developments in this century. A key trend was the inclusion of more aspects of logistics thinking in freight transport models for the public sector. In de Jong et al. (2013) is a list of topics that were expected to be the main areas for further development in freight transport modelling in the next decade. The current paper describes the developments that have actually taken place in modelling freight transport, at the international, national, regional and urban level, and compares these to the list in the 2013 paper.
Freight is transported by the use of different cargo types to increase efficiency. However, multimodal freight transport research does not include different commonly used cargo types in its analyses. The literature has illustrated that the cargo types used affects transport, storage and transshipment costs, and consequently cost-based decision making in the supply chain. Moreover, from a practical point of view, it can be seen that local market players have begun to successfully shift new cargo types to rail and inland waterways. This research presents the incorporation of five different commonly used cargo types into an agent-based freight transport model for Belgium. The MATSim freight extension is extended by considering the cargo type used and by adding mode choice to the optimization process. The results demonstrate that the potential for a modal shift varies greatly between the considered cargo types. Solid bulk, liquid bulk and containers show the highest shares for rail and inland waterway transport (35,8%, 48,9% and 29,6% respectively). Moreover, the sensitivity of the modal split towards changes in the transport costs of road transport (+10%) differs according to the cargo type used. Containers are not very sensitive (+1,2%), while pallets (+2,4%), solid bulk (+3,9%) and liquid bulk (+5,9%) show higher increases. Consequently, some cargo types are more favorable for a modal shift than other cargo types. Tthe idea of considering the cargo type as a variable that affects the modal choice is new.
Statistical information on freight transport does not adequately capture developments in practice. This paper applies a Bayesian framework to integrate statistics on regional freight transport with data on regional trade. The resulting data describe freight transport in the Netherlands at the NUTS 3 regional level by NSTR commodity groups, and by type of flow. We distinguish intraregional transport, regional exports and imports, international exports and imports, and regional transit. The contribution of this paper is that conditions driving regional transport flows are reflected more clearly in the data. The results show the relative importance of logistic processes in regional transport in the Netherlands. Similarly, specific regional production patterns are also reflected in the data. The results contribute to the development of more evidence-based, region-specific freight strategies.
Strategic freight transport models can be used for a quantitative analysis of long
term forecasts. This paper discusses an analysis of the bandwidth of freight transport forecasts for The Netherlands with the strategic freight transport model ‘BasGoed’. This model was developed over the past years as a basic model, satisfying the needs of policy making, based on proven knowledge and available transport data. Starting point for the analysis are the long-term scenarios for The Netherlands developed recently by CPB Netherlands Bureau for Economic Policy Analysis and PBL Netherlands Environmental Assessment Agency (WLO scenarios : Future outlook on welfare, prosperity and the human environment). The scenarios describe two base cases : The High and Low scenario. Both scenarios include a consistent set of assumptions on economic development (domestic growth by industry sector and international trade), infrastructure development, fuel prices, and logistic efficiency. The bandwidth of freight forecasts is further explored in five distinctive sensitivity analyses : different development in fuel prices, energy markets, CO2-pricing, dematerialization and modal shift in the port of Rotterdam. The sensitivity analysis provides more insight in the level of importance of each scenario assumption and it can be useful in estimating a bandwidth for freight transport demand. This is valuable in providing insight in the robustness of the freight transport forecasts for policy studies.
The traditional model-based approach is no longer capable of grasping developments in freight transport within an ever more rapidly changing world. Most models that have been used in the past to explain and predict the demand for freight transport did not devote sufficient consideration to structural, organisational and behavioural changes. Several important global developments that are taking place could have a structural effect on freight transport, with a number of consequences for modelling. This paper addresses several global developments in greater depth, along with their impact on freight transport. This is followed by a discussion of the future of freight models. It is unclear which approach would be appropriate for freight transport under these conditions. This is a clear problem that is linked to a research agenda.
This paper presents the estimation of a discrete freight transport chain choice model for Europe, which was developed for the European Union as part of the Transtools 3 project. The model describes nine different multi- and single mode chain alternatives of which three can be either container or non-containerised, and it segments freight into dry bulk, liquid bulk, containers and general cargo. The model was estimated on the basis of disaggregate data at the shipment level (Swedish CFS and French ECHO data). Several transport costs specifications and nesting structures were tested and elasticities compared with reference literature. It was found that freight models are characterised by heterogeneity, non-linearity in transport costs and hence Value of Times and non-constant rates of substitution. Not taking these elements into account will have consequences for the evaluation of transport policies using the freight transport model.
Freight forecasting models have been significantly improved in recent years, especially in the field of goods vehicle behavior modeling. On the other hand, the improvements to commodity flow modeling, which provide inputs for goods vehicle simulations, were limited. Contributing to this component in urban freight modeling systems, we propose an error component logit mixture model for matching a receiver to a supplier that considers two-layers in supplier selection: distribution channels and specific suppliers. The distribution channel is an important element in freight modeling, as the type of distribution channel is relevant to various aspects of shipments and vehicle trips. The model is estimated using the data from the Tokyo Metropolitan Freight Survey. We demonstrate how typical establishment survey data (i.e. establishment and outbound shipment records) can be used to develop the model. The model captures the correlation structure of potential suppliers defined by business function and provides insights on the differences in the supplier choice by distribution channel. The reproducibility tests confirm the validity of the proposed approach, which is currently integrated into a metropolitan-scale agent-based freight modeling system, for practical use.
Freight transportation and logistics decisions such as modal choice decisions are strategically important for effective supply chain operation and economic benefits. The freight selection logistic is a multi-criteria multi-objective (MCMO) process, crucial for smooth sourcing of materials, cost-effective delivery of products to customers in the right time, at the right quantity. The study discusses the major transport logistics attributes and the order preference by similarity ideal solution (TOPSIS) algorithm as the preferred MCMO model to support comparative ranking among the alternative freights. The entropy weight coefficient method minimizes the subjectivity in the selection of weight of the attribute. This study integrates the entropy technique on TOPSIS platform to improve the freight selection decision. A numerical example illustrates the procedure of the proposed algorithm and ranks the choices among truck, rail, and several intermodal transport combinations (rail/truck and air/truck) in a transportation selection model.
In order to improve the competitive position and efficiency level of multimodal transport, consolidation of freight flows is often suggested. Bundling networks require cooperation between multiple partners in the multimodal transport chain. In this context, the question rises how benefits may be allocated fairly among the spatially distributed participants in the cooperation. A great deal of scientific literature reports on the behavior of allocation methods in collaborations between shippers or carriers making use of unimodal road transport. However, research on cost or savings allocation methods in multimodal transport is scarce. The main contribution of this paper is thus to provide a first insight in the complexity of sharing cost savings fairly amongst shippers who bundle freight flows in order to reach economies of scale in multimodal barge transport. By applying four different allocation methods to two realistic case studies, a comparison is made between simple and straightforward allocation mechanisms and more advanced techniques based on cooperative game theory. Special attention is paid to the savings division amongst coalition partners and collaborative stability. Results demonstrate the influence of cooperation characteristics on allocation outcomes and underline the value of carefully selecting appropriate allocation mechanisms when long-term stability of the multimodal barge collaboration is aspired.
The paper presents a new model for trade flows in Europe that is integrated with a logistics model for transport chain choice through Logsum variables. Logsums measures accessibility across an entire multi-modal logistical chain, and are calculated from a logistics model that has been estimated on disaggregated micro data and then used as an input variable in the trade model. Using Logsums in a trade model is new in applied large-scale freight models, where previous models have simply relied on the distance (e.g. crow-fly) between zones. This linkage of accessibility to the trade model makes it possible to evaluate how changes in policies on transport costs and changes in multi-modal networks will influence trade patterns. As an example the paper presents outcomes for a European-wide truck tolling scenario, which showcases to which extent trade is influenced by such a policy. The paper discusses how such a complex model can be estimated and considers the choice of mathematical formulation and the link between the trade model and logistics model. In the outcomes for the tolling scenario we decompose the total effects into effects from the trade model and effects from the logistics model.
In order to meet future goals in reducing the resulting carbon emissions from transport networks, vast investment in the development of a more energy-efficient and sustainable infrastructure is required. This study investigates the infrastructure implications of a green economy transition in the Western Cape Province of South Africa with a particular focus on the transport sector. Utilising a system dynamics modelling approach, the research effort aimed to improve understanding of how technical, economic, political, social, and environmental factors interact, particularly in the context of the uncertainties encountered during this transition. The key findings of the research indicate that investment in a better public transport system, as well as shifting the movement of freight onto the rail network, would deliver long-term positive effects, including a possible carbon emission reduction of up to 17.89%.
Integrating the decisions and the behavior of Logistics Service Providers (LSPs) into freight transport models is essential to be capable of accurately describing future developments in freight transport systems. Knowledge on the spatial distribution patterns of LSP locations, e.g. to represent network routing of shipments more accurately, is of paramount importance. Moreover, attributes characterizing the LSP locations are helpful to relate them to traffic generation. Therefore, the objective of this paper is to present intermediate results of an empirical study on LSP locations in Germany. Drawing on these findings, the freight generated by German less than truckload networks is estimated on an aggregate level. These findings shed some light on the spatial and structural patterns of the locations allocable to the German logistics sector and the freight transport it generates. These insights are highly relevant for freight transport and land use planning policies.
Freight transportation and logistics decisions such as modal choice decisions are strategically important for effective supply chain operation and economic benefits. The freight selection logistic is a multi-criteria multi-objective (MCMO) process, crucial for smooth sourcing of materials, cost-effective delivery of products to customers in the right time, at the right quantity. The study discusses the major transport logistics attributes and the order preference by similarity ideal solution (TOPSIS) algorithm as the preferred MCMO model to support comparative ranking among the alternative freights. The entropy weight coefficient method minimizes the subjectivity in the selection of weight of the attribute. This study integrates the entropy technique on TOPSIS platform to improve the freight selection decision. A numerical example illustrates the procedure of the proposed algorithm and ranks the choices among truck, rail, and several intermodal transport combinations (rail/truck and air/truck) in a transportation selection model.
Freight sustains our daily lives and economy. Information on its characteristics, its production and consumption locations and its modes of transport are consequently of a crucial importance for private and public decision makers. This paper presents a freight generation model for the Belgian territory. Based on data gathered on transport flows by commodity type and loading unit and data on population density and business establishments with their characteristics, generated and attracted freight volumes were obtained for 4934 zones subdividing the country. A generalized linear regression analysis with log link was used to do so. Both generated and attracted volumes are connected to one another by a conditional probability function, resulting in an origin-destination matrix. The analysis is to our knowledge unique as modelled volumes and flows can be distinguished by commodity types and loading unit, and this at very detailed geographical scale. This will lead to new in-depth analyses and added value, including effects of loading unit dependent logistics cost structures.
A logistic system is an essential component of a spatial system. Actors are organised around infrastructures in order to move different kinds of flow (of goods, of information, or financial) over a territory. The logistic organisation comes from an auto-organised and distributed process from the actors.
This works aims to understand, at different scales, how autonomous and heterogeneous actors (according to their goals and methods to take decisions) are collectively organised around infrastructures to manage different kinds of flow, and despite numerous constraints (temporal, spatial,...).
We propose an agent-based model which allows to simulate the processes to create and organise logistic flow over a territory. The model describes an interface between international and urban flow in order to understand how the port and urban dynamics work together. The model integrates a structural and organisational dynamics thanks to dynamic graphs in order to represent the evolution of this kind of system. Thus, the agents can adapt themselves to system's perturbations as in the reality.
The purpose of the paper is to analyze model uncertainty and economies of scale of the Swedish national freight transport model system Samgods to changes in its zone-to-zone base matrices. Even though economies of scale is an important factor in freight transport, there are few studies that analyze model uncertainty and economies of scale at a national level. Compared to many large scale network-based freight models working on aggregated transport flows, an important feature in the Samgods model is that it contains a logistics module that simulates logistics behavior at a disaggregated firm level. The paper studies effects on total tonne- and vehicle-kilometre, modal split, consolidation and logistics costs when the zone-to-zone-matrices are scaled up and down and estimates the economies of scale for Swedish freight transports in Sweden. The results indicate that the logistics model can find new logistics solutions for larger demand volumes, mainly by shifting freight to sea transport. If transport volume increases with one percent, the logistics cost per tonne is on average reduced by about 0.5 percent. Part of the cost reduction comes from increased consolidation of shipments due to larger transport volumes. The results derived in the paper can serve as a reference for empirical validation and comparisons with other large scale freight models. The paper is a first contribution that tries to fill the knowledge gap on the impact of base matrices on transport model outcomes, such as economies of scale, in the context of a full-fledged real-world freight transport model.
Freight Trip Generation (FTG) in general and FTG modelling in particular are fields that are not concentrated upon as much as passenger trip generation. Therefore, the main objective of this work was to improve the understanding of the underlying processes that generates freight trips and through this understanding, to improve the modelling of FTG. To achieve this goal, the authors first had an extensive literature review to understand the reasons for the weaknesses of the current FTG modelling approaches. After identifying these weaknesses, some of them were brought to a focus in this work. One of the main weaknesses was the inadequacy of the classification system which was used to group commercial establishments in a set of standardized classes. Hence, firstly an experiment was conducted to create groups of logistical sites that had homogeneous FTG characteristics. It was observed that one of these segments had too many zero trips for a particular vehicle category, namely tractor-trailers. Then, to solve this problem, a new ‘conditional’ modelling approach for FTG modelling of this group and this vehicle category was proposed and tested using the data obtained from Kocaeli City Logistics Master Plan. This new hypothesized conditional approach aimed to find the probability of the segment generating tractor-trailer trips using the binary logit model and the generated trips given that the sites produced tractor-trailer trips using the regression technique. Afterwards, the models developed using the new approach were compared with the models obtained using only the common modelling approach of the regression analysis. The results indicated that creating homogeneous groups of logistical sites was possible and the new conditional modelling approach which was applied to one segment of the logistical sites for FTG of tractor-trailers, performed better than the regular regression modelling. Lastly, some recommendations for further improvement of this modelling approach were provided.
Freight transport flows are generating high number of vehicle movements. Modelling freight flows gives consequently crucial information for both public and private decision makers. Generally freight transport models consider flows by commodity type between meso-level traffic analysis zones. Only a few models are taking into account loading units, as they make the difference between containers and general cargo. There is, however, a huge variety within the general cargo category. Pallets, liquid bulk, solid bulk and others have different characteristics in terms of volumes, inventory costs, transshipment costs, et cetera. Considering those issues is new and primordial contribution in the evolution of freight transport modelling towards more disaggregated agent-based systems. Nine different types of loading units are together with ten commodity types integrated in an agent-based freight transport model for Belgium which is currently under development.
The past decade has seen many new freight transport models for use in transport planning by public authorities. Some of these models have developed new concepts, such as logistics modules, inclusion of transshipments, storage and sourcing and the determination of shipment size. This paper provides a review of the European literature on freight transport models that operate at the national or international level and have been developed since 2004. The introduction of elements of logistics thinking is identified as a common theme in recently developed models, and further worked out. Furthermore, ideas on what might be the next key developments in freight transport modelling are presented.
Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects of changes in logistics systems on future transport flows. As such it provides better estimations of the costs of interaction and allows to predict changes in spatial patterns of freight transport flows more accurately. In recent years, the attention for freight modelling has been growing and new research work has appeared aimed at incorporating logistics in freight models. In this paper we review the state of the art in the representation of logistics considerations in freight transport demand models. Our focus is on the service and cost drivers of changes in logistics networks and how these affect freight transport. Our review proceeds along a conceptual framework for modelling that goes beyond the conventional 4-step modelling approach. We identify promising areas for freight modelling that have an integrative function within this framework, such as spatial computable general equilibrium models, supply chain choice models and hypernetwork models.
A large co-ordinated program of work is underway exploring techniques for integrated land
use transport modelling, including elements of agent-based micro-simulation. The intention
is to demonstrate the practical viability of these techniques and help provide guidance in
their further development and use in policy analysis considering transport policy and the
impacts of transport on society. This has given rise to a number of questions about the nature
of the behaviour of the agents being considered (including people, households, business
establishments and developers) and about potential methods for implementing practical
representations of this behaviour. This paper describes the modelling system and techniques
being considered, and sets out some of the questions about behaviour and its representation
that have arisen together with some of the more promising ideas and approaches being
considered for addressing these questions.
The paper discusses the theoretical and empirical evidence on the subject and concludes that freight mode choice can be best
understood as the outcome of interactions between shippers and carriers, and that mode choice depends to a large extent on
the shipment size that results from shipper-carrier interactions. These conclusions are supported by economic experiments
designed to test the hypothesis of cooperative behavior. This was accomplished by conducting two sets of experiments (ones
with the shipper playing the lead role in selecting the shipment size; and others in which the shipment size decision was
left to the carriers), and by comparing their results to the ones obtained numerically under the assumption of perfect cooperation.
The comparison of results indicated that the experiments converged to the perfect cooperation case. This is in line with the
conclusion from game theory that indicates that under typical market conditions the shipper and carrier would cooperate. These
results also imply that it really does not matter who “makes” the decision about the shipment size and mode to be used at
a given time period, as over time the shipper—that is the customer—ends up selecting the bids more consistent with its own
interest. In other words, these results do not support the assumption that freight mode choice is solely made by the carriers.
KeywordsExperimental economics–Freight mode choice–Shipper-carrier interactions–Game theory
Production, Exchange and Consumption Allocation System (PECAS) is a generalization of the spatial input-output modelling approach used in earlier land use transport modelling systems. PECAS has two component modules. One is the space development module that represents the actions of developers in the provision of space, land and floor space, where activities can locate, including the new development, demolition and re-development. The other is the activity allocation module, which represents how activities locate within the space provided by developers and how these activities interact with each other at a given point in time.
Introduction. 1. Transportation Systems. 2. Transportation Supply Models. 3. Random Utility Theory. 4. Transportation Demand Models. 5. Models for Traffic Assignment to Transportation Networks. 6. Intra-Period (Within-Day) Dynamic Models*. 7. Algorithms for Traffic Assignment to Transportation Networks. 8. Estimation of Travel Demand Flows. 9. Transportation Supply Design Models. 10. Transportation Systems Engineering for Planning and Evaluation. A. Review of Numerical Analysis. References. Index. Main Variables.
A prototype spatial computable general equilibrium model is developed and illustrated by a numerical example. The theoretical
basis is a complete Arrow-Debreu equilibrium under perfect competition. The leading principle of model design is parsimony:
The specification restricts the number of parameters in a way allowing for a model calibration relying on a limited data base,
which is readily available in a country with a well developed statistical service. No “data generating” first stage, using
entropy maximisation or other methods not in line with the philosophy of microeconomic equilibrium analysis, is required.
The authors argue that travel forecasting models should be dynamic and disaggregate in their representation of demand, supply, and supply-demand interactions, and propose a framework for such models. The proposed framework consists of disaggregate activity-based representation of travel choices of individual motorists on the demand side integrated with disaggregate dynamic modeling of network performance, through vehicle-based traffic simulation models on the supply side. The demand model generates individual members of the population and assigns to them socioeconomic characteristics. The generated motorists maintain these characteristics when they are loaded on the network by the supply model. In an equilibrium setting, the framework lends itself to a fixed-point formulation to represent and resolve demand-supply interactions. The paper discusses some of the remaining development challenges and presents an example of an existing travel forecasting model system that incorporates many of the proposed elements.
Includes bibliographical references (p. 179-189) Thesis (doctoral)--Universität, Karlsruhe, 2006.
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