Last-mile delivery, one of the most polluting segments of the supply chain, is the focus of numerous studies. There are various innovative delivery methods aimed at mitigating its adverse effects. This study explores whether crowdshipping (CS) could serve as a sustainable urban logistics solution for Rome, assessing its environmental viability. It poses the question: Can Rome adopt CS, and if so, how sustainable would it be? Using real-world data, we employed the MASS-GT simulation tool to simulate parcel demand for various parcel companies in Rome’s urban areas. Additionally, we considered real data on trips made by employees to offices within the study area and their modes of transport. The analyses include predicting parcel demand and forming parcel schedules, both with and without CS.We also assessed employees’ willingness to make detours for parcel pickups. Our findings suggest that CS can reduce emissions depending on users’ willingness to adjust travel routes, which can be incentivized through monetization. Furthermore, by considering the fleet composition of parcel companies, we quantified the potential emissions savings achievable through CS. The results indicate that CS is applicable in Rome and could significantly reduce emissions by approximately 1.3 tonnes of CO2 per day, equivalent to 93 euros in the EU’s Emissions Trading System. This approach aligns with European emissions plans and validates the feasibility of CS in Rome through practical research. It offers valuable insights for policymakers, emphasizing the importance of encouraging user participation and supporting CS platforms.@en

The Internet of Things (IoT) can bring radical advancements in the domain of waste collection, as it enables the organization of demand-responsive schedules which leads to higher efficiency operations. One major challenge in the deployment of demand-responsive schedules, nevertheless, is the uncertainty they bring in the planning of resources as they follow the daily waste demand. This is undesirable in real-life operations as it makes it difficult to reserve resources and ensure the stability of operational processes. Therefore, waste collection scheduling approaches need to be devised that are not only demand-responsive but also supply-friendly. In this paper, we present a solution approach for the waste collection vehicle routing problem in an IoT context (IoT-WCVRP) that focuses on these requirements. We demonstrate its applicability through a case study of Rotterdam in The Netherlands, where real-life household waste data are used and the observed waste collection operations in the city are compared against the optimized outcomes of the model. The application results show that our IoTWCVRP approach achieves the stated demand and supply trade-off, increases the vehicle utilization rates by 5%, and reduces emissions and travelled kilometres by 6% and 8% respectively.@en

Very few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight solutions or policies. Especially the behavioral responses of logistic agents are difficult to include systematically in impact assessments. This is mainly due to limitations on urban freight data and absence of validated and proven simulation tools. We present an urban freight simulator: Multi-Agent Simulation System for Goods Transport (MASS-GT). MASS-GT is an agent-based model consisting of a framework of discrete choice and optimization models to describe the logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model was first implemented for a study area in the Netherlands and calibrated and validated using a variety of data sources.@en

This paper presents the integration of pipeline transport into the Dutch national freight transport model BasGoed.

This paper first provides a general overview of freight transport in the Netherlands. This overview covers all modes of transport, shipping, road transport, rail transport, inland navigation and pipelines. This overview is followed by a more detailed description of pipeline transport. We address the current use of pipelines, looking at the operational range, the existing infrastructure and the types of goods currently transported via pipelines, such as liquids and gases. With a SWOT analysis, we evaluate the strengths, weaknesses, opportunities and threats of pipeline transport. This analysis helped to prepare the functional and technical design of a pipeline module for BasGoed.

We then present the conceptual design and technical implementation of the pipeline transport module in BasGoed. The considerations behind the architecture and design are described. Modelling challenges include limited data availability, forecasting potential modal shift and potential demand for new transport due to energy transition (hydrogen, CO2). Use cases have been developed to ensure that the model properly reflects these developments in pipeline transport demand.

We further describe the technical integration into BasGoed, addressing the aspects of data integration and ensuring data accuracy and consistency. The paper discusses how the integration of pipeline transport leads to a better representation of freight transport within the Netherlands, by improving the BasGoed model.

The paper concludes with some conclusions and recommendations for including freight transport via pipelines in freight transport models.
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City logistics simulation can help to provide empirical proof of potential benefits of new solutions in city logistics but decision support tools for such analyses are scarce because of a lack of empirical data and resources. The Tactical Freight Simulator (TFS) is a multi-agent simulator that represents the decision-making of freight agents and individual freight shipments. In this study it is applied to four distinct use cases in city logistics: micro hubs, introduction of zero-emission zones, crowd-shipping and the land use planning of logistic facilities. The simulations show impacts of each development and provide learnings: the type of open or single carrier operation of micro hubs have big local impacts. The impact of freight traffic avoiding zero emission zones can have substantial local impacts. Depending on the configuration of the service, crowd-shipping can lead to more vehicle kilometres. A common finding is the impact of the chosen scenario parameters on the outputs: regulation is important to shape city logistics operations. This also illustrates that, although the technology seems to be ready for innovative solutions, the logistical organisation or business models and policies are not yet well developed.@en

This paper presents a hybrid system dynamics and agent-based model to simulate the dynamic evolution of consumer preferences for parcel delivery. Scenarios provide insight about preference development and capacity growth of delivery services.@en

Ondanks dat in Nederland jaarlijks 15%-20% van het goederenvervoer per buisleiding vervoerd wordt, bleef buisleidingentransport lange tijd buiten het zicht van beleidsmakers. Met de verwachte belangrijke rol die buisleidingen kunnen spelen in de energietransitie is dit veranderd, en is er een duidelijke wens van beleidsmakers om meer grip het vraagstuk van buisleidingenvervoer te krijgen. In opdracht van WVL Rijkswaterstaat heeft Significance een Buisleidingenmodule prototype ontworpen te geïntegreerd kan worden met het Nederlandse goederenvervoermodel BasGoed. De uitdagingen bij het ontwerp van
een kwantitatief buisleidingenmodel zijn een gebrek aan gedetailleerde data, beperkte
toekomstscenario’s en dat de buisleiding als modaliteit sterk afwijkt van conventionele
goederenvervoerswijzen. Uitgangspunten voor het prototype zijn (1) dat deze goed aansluit bij de huidige versie van BasGoed en (2) flexibel kan omgaan met verschillende detailniveau’s van de invoerdata. In dit paper wordt het ontwerp van het prototype en haar 4 submodules beschreven. Daarnaast wordt de praktische toepassing van het prototype getoetst aan de hand van twee uitgewerkte use cases. We laten zien dat het - ondanks zeer beperkte data - mogelijk is een kwantitatief buisleidingenmodel te ontwerpen dat consistente resultaten geeft in samenspraak met de huidige goederenvervoersmodellen in Nederland.
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Micro-hubs are considered to be a potential solution to increase the consolidation of inner-city deliveries: in the City of Rotterdam it is a potential measure to increase the logistic efficiency in and around the planned zero-emission zone in the city center. When designing the configuration of micro-hubs in an urban setting multiple aspects should be considered, such as their location, the type of vehicles to operate them, and the business model to be adopted for their operation. And although the topic is much studied it remains difficult to predict how different micro-hub configurations affect the transportation system in terms of transport movements, number of travelled kilometers, etc. This paper describes the use of the Tactical Freight Simulator (TFS) to investigate the impact of micro-hubs on the transportation system in case they would be implemented at a wider scale across the city center, and make a comparison with the current state of last-mile delivery. The case study explores three different design aspects: location, type of vehicles (delivery robots, cargo bike, LEV), and the business model (individual/full collaboration). Results show that the largest reduction of vehicle kilometers can be achieved in the scenarios with full collaboration between the CEPs.@en

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.

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Knowledge of the hierarchical organization of urban heavy truck flows is important for understanding the structure of urban freight system and underlying interactions dynamics, providing insights to assess and develop freight policies. The complexity and dynamic nature of urban freight system pose significant challenges in comprehensively capturing structured arrangement of heavy truck movements. In this paper, we uncover the hierarchical organization of urban heavy truck flows by using complex network theory. We use large-scale heavy truck GPS data and urban freight location point-of-interest (POI) data to construct urban heavy truck mobility networks, and detect their community structure. The empirical results suggest different sets of locations are closely linked to each other to form multiple clusters. By integrating the categories of locations, we reveal the cluster-specific industry concentration and industry-specific location roles, informing evidence-based policy formulation. To capture the interaction dynamics of locations, we develop a spatial network growth model that considers the spatial agglomeration of industrial clusters and interaction pattern of locations. The model provides a mathematical tool to simulate the formation process of real-world networks for logistics planning and management.

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The growth of e-commerce and omnichannel retailing has led to significant changes in urban logistics deliveries. In addition to the traditional delivery channels, new solutions have been introduced, such as click-and-collect, parcel locker delivery, crowdshipping, and on-site delivery. However, such solutions require seamless connections between different layers of the city logistics system. These connections form, in the Physical Internet terminology, a “hyperconnected city”. In this context, how do consumers make decisions about logistics services, either as prospective users or as suppliers of last mile logistics services? We argue that a thorough understanding of consumers’ decision-making about last mile services is a prerequisite for the effective exploration of future demand for these services and the design of transport policies. While there is abundant literature on new approaches of last mile logistics, a review of research on consumers’ decision-making and participation in such services is absent. This paper aims to provide such a review and, based on this, provides directions for future research. Based on the existing literature, we propose a conceptual framework that categorises decisions and system attributes affecting consumers’ decision-making. Highlights for future research include interaction between consumers’ demand and supply decisions, changes in consumer preferences, the importance of social networks, and the city-level impacts of hyperconnected last mile delivery.@en

Crowdsourced shipping or crowdshipping is a promising contender for sustainable parcel delivery services due to the potential to consolidate freight trips with pre-existing passenger trips. However, the opportunity for private persons to act as occasional carrier can also generate new trips, which could then increase traffic volumes. Previous literature has focused on the consolidation case only, and has not addressed new activity generation in crowdshipping. In this study we investigate the willingness of private persons to accept shipments based on a newly generated home-based trip and compare this to choices of occasional carriers who had already planned their travel, in this case related to the daily commute. We conduct two stated preference experiments and apply a multinomial logit model to identify preferences. Additionally, a latent class choice model is utilized to explore the existence and effect of heterogeneity in preferences. The results show that commute-based and home-based trips have different VoT parameters and the former is higher than the latter. Parcel lockers as delivery points have a positive effect on acceptance since they allow for more flexibility in delivery times. The latent class model suggests that the distinction between low income and high-income groups is relevant; here, the low-income group has a lower value of time and is more willing to make a detour to execute the delivery. The study provides first quantitative evidence that crowdshipping can act as a potential trip generator in households and recommends that this is taken into account in passenger transportation models.@en

Rijkswaterstaat gebruikt het goederenvervoermodel BasGoed om lange termijn prognoses te maken van het goederenvervoer. Economische verwachtingen spelen hierbij een belangrijke rol. Het model BasGoed begint dan ook met een module waarin de economische groei bepaald wordt en vervolgens vertaald wordt naar de hoeveelheid vervoerde goederen. De vorige versie van de economie module was verouderd. Deze paper beschrijft de nieuw ontwikkelde module op basis van multiregionale input-output analyses, aansluitend bij de manier waarop het Planbureau voor de leefomgeving economische analyses maakt. De werking van de module wordt toegelicht, en de eerste resultaten worden vergeleken met de uitkomsten van de oude module.@en

Knowledge of the core structure and inherent dynamics of urban freight transport systems is important for the development of policies, aimed at improving the livability and sustainability of cities. The past decade has witnessed a great deal of efforts into analyzing the geographic structure of urban freight transport systems. However, in-depth studies on the system core structure and underlying dynamics are still absent. This study contributes to the field by analyzing large scale freight truck trip data from Chinese cities, using complex network analysis. We empirically reconstruct and characterize the urban freight truck mobility networks and reveal the underlying spatial interaction patterns. We develop a spatial network growth model which explains how hub-and-spoke core structure of urban freight transport systems are formed. The developed model captures the essential interaction dynamics of freight locations, and explains the effects of spatial distance, economic size and business pattern replication. Inspired by the model, we provide policy implications for land-use planning, transportation planning and sustainable urban development.

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Goederenvervoer is het transport gedeelte van het logistieke systeem: goederen worden van A naar B vervoerd. Een groot gedeelte is onderdeel van logistieke ketens. Waar data over goederenvervoer in toenemende mate beschikbaar is voor onderzoek en planningsdoeleinden, blijft de beschikbaarheid van logistieke data schaars. In deze bijdrage presenteren wij de resultaten van een data gedreven onderzoek waarbij ‘big’ tripdata van transporteurs zijn geanalyseerd op distributiestructuren. Uitdaging daarbij is de transport data te verrijken met logistieke informatie: vond deze rit plaats vanuit een multimodale terminal, een distributiecentra, of kwam deze vanaf een producent? Op de TU Delft hebben we een effectieve methode opgezet om structurele distributiepatronen te ontdekken, ondanks de data-inefficiënties. De resultaten geven een relevante inkijk in distributiestructuren voor verschillende segmenten in het goederenvervoer: informatie die tot nog toe nog ontbreekt.@en

Crowdsourced shipping or crowdshipping is a promising solution to sustainable parcel delivery, owing to the potential to consolidate freight trips with preexisting passenger trips. Previous literature focuses on these consolidation benefits but does not address the possibility of new activity generation in crowdshipping. In this study, we investigate the willingness of private persons to accept shipments based on a newly generated home-based trip. We compare this to the choices of occasional carriers who build on the daily home–work commute to deliver parcels. Two stated preference experiments are conducted and a multinomial logit choice model and a latent class choice model are employed. These allow us to provide values of time of the occasional carriers, as an original contribution to the literature. The results show that commute-based carrier values of time are higher than those of home-based carriers. Concerning the trip generating power of crowdshipping, we find that low-income groups have a relatively high propensity to generate a home-based pickup and delivery trip. Finally, parcel lockers as delivery points positively influence acceptance of crowdshipping requests, as they allow for more flexibility in delivery times. Together, these results support the notion that crowdshipping can act as a potential trip generator in households.@en

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.@en

This chapter introduces the topic of freight transport modelling in the urban context. Urban freight transport is typical in several aspects: the defragmentation of product flows, the use of modes, and the commodity mix. Freight traffic is also in competition for space with other traffic and users of the urban environment. Real-world applications of urban freight models are scarce because of a lack of data and methods to adequately simulate impacts of urban freight policies. However, recent applications of information and communications technology offer new opportunities for the development of urban freight transport models. At the same time, these developments are reshaping the scope of urban freight models more and more into tools for operational management. The aim of this chapter is to provide an overview of the key developments in urban freight modelling of the past decades, with a focus on the latest research and innovation directions. It will also introduce the subsequent chapters of this section that will focus on the modelling of the demand for freight services, microsimulation, and agent-based modelling, and the latest developments in freight trip generation models.@en

The fast growth of e-commerce in urban areas has led to a surge in last-mile transportation demand and an associated increase of external effects: congestion, noise and visual pollution. This paper analyses a new urban freight transport service that has a potential to reduce this footprint: crowdshipping. Crowdshipping is a service where a package is delivered via a traveller who is already making a personal trip for other purposes. The decision of whether or not to use crowdshipping is known to be subject to various service, time and price conditions, including trust in a correct delivery. The effect of trust has not been investigated explicitly, however. We conduct a stated choice experiment and estimate a hybrid choice model with trust as a situation-specific latent variable. The research design allows us to explore how the relevant attributes influence service adoption via trust. We find a significant influence of established choice attributes on service adoption, except for the delivery company’s reputation and the possibility of damage. In addition, all attributes except delivery time have a significant influence on trust. We conclude that trust has a partially mediating effect on the adoption of the service except delivery time, and a fully mediating effect on adoption via reputation and damage.@en

1. Overview and motivation
E-commerce is a rapidly developing segment within urban goods transportation. While currently making up only 5.5% of all kilometers driven by vans in the Netherlands (CBS, 2018), this segment is experiencing rapid growth. For example, in the Netherlands, the volume of parcel deliveries grew by 20% in 2018 (ACM, 2018). This growth is further accelerated by the current coronavirus pandemic. The increasing importance of this segment is not reflected yet in strategic models used in practice for transportation demand forecasting. Parcel deliveries are not modelled explicitly, which does not only prevent the model users from calculating effects of scenarios and policies related to e-commerce, but it also disregards the unique nature of this segment (e.g. specific depot locations, strong growth rates) and, therefore, leads to flawed reference forecasts of van traffic.
In the scientific literature there are some first examples of simulation models for parcel deliveries (Sakai et al, 2020; Hörl & Puchinger, 2021; Llorca & Moeckel, 2021; Mommens et al., 2021; Reiffer et al., 2021). However, each of these examples lacks an empirical disaggregate demand model, focusses on one (part of a) city rather than a whole region, or focusses on one product/service segment rather than all parcel deliveries in a region. Moreover, little experience is gathered in applying such urban freight simulators for traffic forecasting.

2. Methodology, results and main contributions
To combat these shortcomings of the state-of-practice freight models, we developed a module for last-mile parcel deliveries and used it to explore the impacts of different scenario assumptions regarding parcel demand and scheduling. The module consists of two sub-modules: the parcel demand sub-module and the parcel scheduling sub-module.
The parcel demand sub-module calculates parcel demand based on the households and businesses in each zone. For parcels to households (B2C), a logit model is estimated on the Mobility Panel Netherlands, which included several questions regarding parcel orders in 2017 (Hoogendoorn-Lanser et al., 2015). For parcels to businesses (B2B) an average factor is deduced from aggregate statistics reported by ACM (2018). Once the total number of parcels is determined, they are spread over the different courier companies, based on their respective market shares in terms of number of parcels. Finally, for each zone and courier, the nearest depot is determined; from this depot the parcels will be shipped to their end destinations.
The parcel scheduling sub-module forms round-tours to deliver all the parcels for each parcel courier in the study area. From each depot, simple heuristics (such as nearest-neighbor and 2-opt) are used to form efficient tours that respect the vehicle capacity (in terms of number of parcels) and maximum shift lengths for drivers. This, in turn, leads to trip matrices that can be assigned to the network to arrive at network statistics such as vehicle kilometers and emissions.
The conceptual architecture of this module has been applied in four modelling systems:
(1) the strategic freight model of Flanders (SVRM);
(2) the travel demand model of the Municipality of Amsterdam (VMA);
(3) the module for logistical decision-making of the national strategic freight model of the Netherlands (BasGoed);
(4) and the tactical freight simulator of the HARMONY project for the European Commission (test bed: Province of Zuid-Holland, the Netherlands).
In this research we will analyze the impacts of different scenarios and policies, for this purpose we will use the HARMONY implementation of the model in Zuid-Holland. The scenarios explore the impacts of different developments for:
• increased demand for parcels;
• horizontal collaboration between couriers, with shared use of depots;
• a zero-emission zone in Rotterdam, in combination with consolidation centers at the outskirts of the city.

3. Conclusion and future works

A disaggregate region-wide simulation model for parcel deliveries is necessary to evaluate the impacts of policies and developments in e-commerce. Using the developed model, we can show, for example, that vehicle kilometers do not increase linearly with parcel demand due to increased consolidation and that the impacts of zero-emission zones can be diffuse due to rerouting of van trips.

Future efforts may focus on modelling the whole transport chain of e-commerce, rather than only the last-mile deliveries. Furthermore, a demand model for parcels to businesses in line with the model for households is desired, this would require additional data collection.
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