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Crowdshipping (CS) is an emerging form of freight transport that is expected to reduce the externalities of urban freight transport. The supply of CS services originates from people with an intention to travel, who can choose to engage in a parcel delivery service as incidental carrier. The popular expectation is that this consolidation of freight and passenger trips could save freight trips and thus alleviate urban transport congestion and environmental pollution. A key challenge in the prediction of CS service volumes and impacts, however, is to match existing service demand and supply. This has not yet been addressed in the literature with models that give an empirically realistic representation of individual decision-making. We approach this problem using a disaggregate activity-based models for urban passenger transport and freight transport. Allocation of parcels to travellers is done based on a simulated random utility discrete choice model. We present a first case study for the city of The Hague, The Netherlands, to illustrate empirically the model. Our findings suggest that CS could result in increased CO2 emissions and total vehicle distances travelled.

As part of a broader vision for emission-free city logistics, the city of Rotterdam plans to introduce a zero-emission zone in combination with urban consolidation centers (UCCs) on the outskirts of the city to generate a shift to zero-emission vehicles. For the design of this zero-emission zone, several research questions arise that require a systematic analysis of the impacts of the transition scenarios on freight demand patterns, the use and market shares of new (zero-emission) vehicles, and the impacts of truck flow and emissions. As a case study, we implemented heterogenous transition scenarios for each logistic segment into the Tactical Freight Simulator from the HARMONY project and analyzed the systemwide impacts. This model is multiagent, empirical, and shipment based and simulates long-term tactical choices (distribution channel choice, shipment size and vehicle type choice, sourcing) and short-term tactical choices (tour formation, delivery times). Results showed that the impact of UCCs is not trivial: we observed a small increase in vehicle kilometers traveled overall of +0.25%, which can be attributed to the rerouting of shipments through the UCCs. Calculations confirmed that emissions reduced dramatically, by 90%, inside the zero-emission zone. At the city scale this corresponds to a reduction of almost 10%, as most freight-related traffic is generated by the port and involves long-haul heavy goods vehicle transport that does not enter the city center. At a regional level, impact reduction was very small. More measures are needed if more ambitious reductions in emissions are to be achieved.

In this paper we explore the possible impacts of a distance- and emission-class based truck charge in The Netherlands. Earlier studies suggest that shifts may occur towards heavy vehicles, due to the relative inefficiency of lighter vehicles types. However, these studies have not taken into account the effects of changes in shipment size, as a response to pricing measures. Also, these studies have not considered emission-class dependent charges. Thirdly, no empirical disaggregate models or studies are available for the Netherlands for this problem. We present a discrete choice model for the joint choice of vehicle type and shipment size, estimated on a large dataset of disaggregate carrier freight trip data. The model explains variations in vehicle type choice for different transport purposes and contexts (e.g. commodity type, long-haul, urban transport, to/from logistic nodes). The analysis of emission based truck charging schemes shows that substitution towards low emission vehicles can be expected within the same vehicle class. It is also not likely that the truck charge will lead to a significant increase of shipment sizes or to substitution between vehicle types: a distance based truck charge increases transport costs but inventory costs restrain a shift to larger shipment sizes. This result points to a limited capability of supply chains to absorb transport cost increases by logistics re-organisation.

Reducing emissions caused by urban freight transportation is an increasingly important policy objective for transportation planners around the world. New and innovative ways of data collection provide new possibilities to analyze these issues. In this paper we present MASS-GT, a new multi-agent simulation system for urban goods transport. The empirical basis is provided by an exceptionally large dataset of truck trip travel diaries for The Netherlands that was collected from transportation management systems using an automated data collection interface. The dataset is very dense and includes information on vehicles, routes, and shipments carried. The strategic part of the model simulates the formation of individual shipments based on logistic processes at a strategic level, such as sourcing, distribution channel choice and shipment size choice. At tactical level disaggregate choices are simulated for tour formation, vehicle type- and time of day choice, based on observed distributions. The multi-agent approach allows to implement heterogeneous preferences and thus differentiated responses to new policies. We present an application of the model to study the impacts of urban consolidation centers (UCC) and zero emission zones. The freight transportation volumes transported to these UCC and their impact on logistic indicators are analyzed. Simulation results show that vehicle kilometers travelled within the wider region increase with the introduction of UCC, and at the same time the efficiency of deliveries increases as well. Thus the model allows to study trade-offs between regional and local systems that emerge from different behavioural responses to policies.

Understanding the logistic determinants of freight trips is an important goal in freight transport modeling. Freight shipments move between nodes in the supply chain for different logistic purposes, including production, storage, transshipment, and consumption. A key problem with data availability is that databases generally do not identify these purposes, given the commercial sensitivity of the data. In addition, including information on senders and receivers of the shipments is often prohibitively costly. Therefore, one of the challenges of transport data analysis is to identify freight trip purposes using data fusion, linking information about the main function of logistics nodes to trips in existing databases. This paper proposes a data fusion approach to enrich big truck shipment databases with firm registry data. We use the national freight shipment micro-database from the Netherlands which includes shipment, vehicle, and tour information. Although our presentation here uses formats and methods of accounting for freight data used in the Netherlands, it can be readily replicated for conditions in other countries, as long as similar data sets on shipment data and firm registry are available. The enriched, new database contains transport and firm data for more than 2 million observed trips with information on the vehicle used, shipments carried, and sender/receiver firm. An initial descriptive analysis provides unique empirical insights into the logistic determinants of freight trips. These include the share of national trips that use intermediate nodes, typical changes in shipment sizes, and the role of distribution centers for (de)consolidation of shipments.freight transportation data, shipment database, distribution centers data, freight big data, and data fusion

As part of a broader vision for emission-free city logistics, the city of Rotterdam plans to introduce a zero-emission zone in combination with urban consolidation centers (UCCs) at the outskirt of the city to generate a shift to zero-emission vehicles. For the design of this zero-emission zone many research questions arise that require a systematic analysis of the impacts of the transition scenarios on the freight demand patterns, the use and market shares of new (zero-emission) vehicles, and the impacts of truck flow and emissions. As a case study we implemented heterogenous transition scenarios for each logistic segment into the Tactical Freight Simulator from the project HARMONY and analysed the system wide impacts. This model is multi-agent, empirical and shipment based and simulates long-term tactical choices (distribution channel choice, shipment size and vehicle type choice, sourcing) and shortterm tactical choices (tour formation, delivery times).Results shows that the impact of UCCs is not trivial: we can see a small increase in vehiclekilometers travelled (VKT) overall: +0.25% which can be attributed to the rerouting of shipments throughthe UCCs. Calculations confirm that emissions are reduced dramatically, by 90%, inside the ZeroEmission Zone. At the city scale this corresponds to a reduction of almost 10%, as most freight relatedtraffic is generated by the port and involves long haul HGV transport that do not enter the city center. At aregional level the reduction of impacts is very small. More measures are needed if more ambitiousreductions in emissions are to be achieved.

In this paper we present a methodology to more accurately calculate emissions in regional freight transportation models by taking the loading rate of vehicles into account in the emission factors. This is done by incorporating the shipment-based demand data from a multi-agent simulation framework into the route assignment. In a case study we show that disregarding the vehicle loading rate can lead to underestimations of the amount of pollutant gasses. The application of this methodology in combination with a multi-agent simulation model allows to simulate impacts of changes in logistics behavior, such as vehicle type use or the scheduling of round tours, on emissions more accurately.

An increasing amount of research is dedicated to the consideration of tour formation in freight transportation demand models. While empirical tour formation models so far have been starting from limiting assumptions about the resulting trips, we develop a generalized shipment-based model. We formulate a random utility model embedded in an iterative algorithm to construct tours through the incremental allocation of shipments. It considers different objectives and constraints and acknowledges the difference between commodity, vehicle and location types. Parameters are estimated on a large and comprehensive shipment database. The model reproduces observed tour statistics well for the given set of shipments.

The Fourt Generation of Strategic Passenger Transport Models for Flanders are being developed to meet three objectives. It includes a Population Simulator to generate reliable population inputs for a disaggregate demand model, the demand model is based on disaggregate tour-based mobility demand model, which also includes a departure time choice model to improve the sensitivity to increasing congestion and congestion charging. Finally the model is updated to the base year. This article describes the development of the population simulator and mobility demand model. The population simulator simulates the demographic evolution of the Flemish population from 2001 to the new base year 2013 and subsequently for a given year in the future. The disaggregate choice models in the mobility-demand model are are estimated on the OVG and OWoWi surveys. The presented demand models are being implemented in a microsimulation application. In effect, the passenger transport model is sensitive to changes in the composition of the population and infrastructure developments.

The spatial economic effects in integrated land use and transport models are increasingly disaggregate and can benefit from improved knowledge into the effect of accessibility and agglomeration on the spatial behaviour of firms. This article strives to contribute to this knowledge by first analysing the influence of accessibility and agglomeration on firm behaviour with exceptionally detailed firm data for the province of South Holland in The Netherlands. Next the added value of incorporating such effects in urban simulation models is tested with two series of validation runs with a microscopic model for firm dynamics. The presented Spatial Firm-demographic Micro-simulation (SFM) model simulates transitions and events in the firm population, including firm relocations, firm growth, firm dissolution and firm formation. Accessibility is measured with proximity to infrastructure access points and logsums of business and commuting trips from a transport model. Agglomeration measures are based on theories from urban economics and integrate travel time range bands into measures for specialisation and diversification. Estimation results confirm a significant influence of accessibility and agglomeration on the choice behaviour of firms. Application of these measures prove to increase the validity of the firm-demographic simulation model to a significant but modest extend.

This paper describes the empirical results of the estimation of discrete choice models for the location decision of moving firms in a spatial disaggregated environment. Systematic choice sets are applied to account for the choice context of each relocated firm. Each location alternative is described by a set of spatial attributes, including accessibility variables and the migration distance between the origin of the moving firm and the alternative. The firms analyzed are categorized by their mobility profile. These mobility profiles are homogeneous groups of firms with similar mobility characteristics. The models are estimated on an extensive revealed-preference data set with firm migration observations between 1988 and 1997 in the province of South Holland in the Netherlands. The results indicate that it is essential for modeling the spatial behavior of relocating firms to account for the original location. The accessibility of locations appears to be of modest importance in the location preference of firms; measures describing the distance to transport infrastructure appear to have the most significant influence. Finally, distinctive taste preferences are observed in firms with different mobility profiles and of different sizes.

The development of the theories underlying applied employment location models for urban simulation models is far from linear. This book presents an overview of contemporary studies, including continuing refinements to existing model packages, and new developments. We discuss the main drivers behind employment location, a generalization of approaches and relevant issues for the future development of these models.

We examine the accessibility benefits associated with some land-use policy strategies for the Netherlands that anticipate on expected climate change. A disaggregate logsum accessibility measure using the Dutch national land-use/transport interaction model TIGRIS XL is used to compute changes in consumer surplus. The measure provides an elegant and convenient solution to measure the full accessibility benefits from land-use and/or transport policies, when discrete choice travel-demand models are available that already produce logsums. It accounts for both changes in generalised transport costs and changes in destination utility, and is thus capable of providing the accessibility benefits from changes in the distribution of activities, due to transport or land-use policies. The case study shows that logsum accessibility benefits from land-use policy strategies can be quite large compared to investment programmes for road and public transport infrastructure, largely due to changes in trip production and destination utility, which are not measured in the standard rule-of-half benefit measure.

Existing integrated land use transport interaction models simulate the level of employment in (aggregated) zones and lack the individual firm as a decision making unit. This research tries to improve the behavioural foundation of these models by applying a firm demographic modelling approach that first of all accounts for the individual firm as a decision making unit and secondly represents the urban system with high spatial detail. A firm demographic approach models transitions in the state of individual firms by simulating transitions and events such as the relocation decision, growth or shrinkage of firms or the death of a firm. Important advantage of such a decomposed approach is that it offers the opportunity to account for accessibility in each event in the desired way. The firm demographic model is linked to an urban transport model in order to obtain a dynamic simulation of mobility (and accessibility) developments. The paper describes the firm demographic model specifications as well as the interaction of the model with the urban transport model. The integrated simulation model can be used to analyse the effects of different spatial and transport planning scenarios on the location of economic activities and mobility.

Accessibility is a concept central to integrated transport and land use planning. The goal of improving accessibility for all modes, for all people, has made its way into mainstream transport policy and planning in communities worldwide. This unique and fascinating book introduces new accessibility approaches to transport planning across Europe and the United States.