Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration. The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).

Deze studie onderzoekt de integratie van cargobikes en microhubs in stedelijke logistiek, met een casestudie in Rotterdam. Microhubs worden gezien als een oplossing voor het defragmenteren van last-mile bezorging en het bevorderen van emissievrije stadslogistiek. Dit leidt tot toenemend gebruik van cargo bikes in de stedelijke omgeving. Tegelijkertijd wordt het gebruik van fietsen gestimuleerd, en al deze nieuwe stromen van mobiliteit en stadslogistiek maken gebruik van dezelfde stedelijke ruimte. Voor efficiënte planvorming is het nodig om op tijd de impacts van nieuw beleid te kunnen toetsen ter voorkoming van bottlenecks op het fietsnetwerk of in de stedelijke omgeving.

Het onderzoek maakt gebruik van het stadslogistieke simulatiemodel MASS-GT, uitgebreid met een fietsnetwerkmodel, om de bereikbaarheid en netwerkprestaties van cargobikes te evalueren. De simulatie is gebaseerd op een agent-gebaseerde benadering en maakt onderscheid tussen verschillende gebruikersklassen, waaronder een specifieke klasse voor cargobikes. Deze klasse houdt rekening met voertuiggrootte, snelheid en voorkeuren voor wegtype en infrastructuur.

In de usecase worden twee scenario’s vergeleken: één met individuele microhubs per vervoerder en één met gedeelde hubs. Beide scenario’s simuleren bezorgroutes en het gebruik van het fietsnetwerk door cargobikes. Het gedeelde hubscenario leidt tot minder cargo bike bewegingen, minder stops en lagere parkeerdruk. De simulaties tonen ook verschillen in netwerkbelasting en knelpunten, vooral in drukke gebieden zoals het Centraal Station. De resultaten laten zien dat gedeelde hubs efficiënter zijn in termen van netwerkbelasting en parkeerdruk. Knelpunten worden geïdentificeerd op basis van intensief gebruik door zowel cargobikes als reguliere fietsers. Heatmaps tonen de parkeerdruk, waarbij gedeelde hubs minder impact hebben op de openbare ruimte.

Gedetailleerde simulaties zijn essentieel voor het evalueren van stedelijke logistieke strategieën. De gepresenteerde aanpak biedt beleidsmakers inzicht in de effecten van cargobike-integratie en ondersteunt de optimalisatie van de planning van hublocaties. Toekomstig onderzoek richt zich op validatie van routevoorkeuren van cargo bike bezorgers, operationele strategieën van de bezorgdiensten, en verdere verfijning van het fietsnetwerkmodel.

Goederenvervoer speelt een cruciale rol in de Nederlandse economie. Maar het netwerk is kwetsbaar: een file, kapotte brug of beperkte spoorcapaciteit kan grote gevolgen hebben voor de leveringszekerheid van goederen. De huidige analyses, zoals de Integrale Mobiliteitsanalyse (IMA), richten zich vooral op tijdsverlies en capaciteitstekorten, maar laten minder goed zien hoe en waar knelpunten doorwerken in de vervoersketen.
Kwetsbaarheid voor het goederenvervoer gaat om de leveringszekerheid van goederen: dus hoe kwetsbaar zijn vervoerssegmenten voor stremmingen in het netwerk. In deze rapportage hebben we een kwetsbaarheidsindicator gemaakt voor regio’s. De kwetsbaarheid is een functie van twee deelaspecten:
(I) De afhankelijkheid van een regio van een goederenknelpunt, en
(II) De substitutiemogelijkheden
Afhankelijkheid en substitutiemogelijkheden zijn ook weer opgebouwd uit verschillende deelaspecten. De kwetsbaarheidsindicator meet voor een regio een combinatie van de mate waarin een knelpunt invloed heeft op het goederenvervoer en de substitutiemogelijkheden. Door de combinatie van afhankelijkheid van knelpunten en beschikbaarheid van alternatieven ontstaat een goed beeld van de zwakke plekken in het netwerk. Dit helpt beleidsmakers bij het nemen van gerichte maatregelen om de impact van verstoringen te verminderen. In deze bijdrage bespreken we de opbouw van deze indicator.

Despite the importance of urban freight transportation for the accessibility and livability of cities, few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight transportation solutions or policies. There is a lack of transparent literature on the full specification and estimation of these models, which not only hampers continued research, but also the development of evidence-based urban freight transport policies. We present the urban freight simulator Multi-Agent Simulation System for Goods Transport (MASS-GT) with its full specification and empirical implementation for a study area in The Netherlands. It concerns an agent-based model based on a framework of discrete choice and optimization models, which describes 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 is estimated and validated using a variety of data sources: truck trip diaries, supply/use statistics, an e-commerce demand survey, traffic counts and other relevant statistics. The article presents the full specifications of the model and their empirical estimation, including the data sources used. Also, the validity of the model is evaluated using road freight traffic counts. Finally, examples of applications of the model to case studies are provided.

Goederenvervoer is cruciaal voor de Nederlandse economie, maar transportnetwerken zijn kwetsbaar voor verstoringen zoals files of kapotte bruggen. Dit onderzoek richt zich op de impact van grootschalige (tijdelijke) beperkingen van het hoofdwegennet, bijvoorbeeld als gevolg van het onderhoudsprogramma van Rijkswaterstaat, op de vervoerssector en de veerkracht van de sector om deze beperkingen op te vangen. Veerkracht, in deze context, verwijst naar het vermogen van het goederenvervoersysteem om zich aan te passen aan, en te herstellen van, verstoringen zoals langdurige afsluitingen van belangrijke weggedeelten.

Bij de analyse is een unieke methodiek toegepast, waarbij twee nationale transportmodellen – BasGoed en LMS – zijn gecombineerd. Hierdoor kan de wisselwerking tussen veranderende bereikbaarheid en verschuivende vervoerspatronen iteratief worden doorgerekend.

In de analyse is een selectie gemaakt van een zestal knelpunten die de komende jaren op de planning staan voor groot onderhoud. De afsluiting van deze weggedeelten is als case doorgerekend. De veerkracht van het systeem is geanalyseerd met de veerkrachtsdriehoek (‘resilience triangle’). De mogelijke gedragsreacties van de vervoerssector die kunnen worden meegenomen zijn verandering van routekeuze, keuze toeleverancier en de modaliteitskeuze.

De resultaten laten zien dat routekeuze de belangrijkste gedragsreactie is: veel vrachtvervoerders kiezen bij een verstoring simpelweg een andere route. Hierdoor worden de effecten van afsluitingen op langeafstandsvrachtverkeer deels beperkt. In regio’s met goede alternatieven, zoals spoor- of binnenvaartterminals, is te zien dat ook de modaliteitskeuze verschuift. Het aandeel vracht op spoor en binnenvaart neemt daar aanzienlijk toe. Toch is er sprake van een waterbedeffect: regio’s die verder van het knelpunt liggen ondervinden indirecte negatieve gevolgen, doordat verkeer zich verplaatst en nieuwe knelpunten ontstaan.

Op nationaal niveau blijkt de veerkracht van het systeem relatief beperkt: hoewel sommige regio’s de initiële verslechtering van bereikbaarheid deels kunnen opvangen door andere vervoerwijzen te gebruiken, blijft er een aanzienlijk restverlies bestaan dat niet volledig te compenseren is. De mate van veerkracht verschilt sterk per regio, afhankelijk van de beschikbaarheid van alternatieve routes en modaliteiten.

Aanbevelingen omvatten het verbeteren van de integratie tussen LMS en BasGoed en het verminderen van modelruis in de RGM-procedure.

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.

Large-scale social digital twinning projects are complex with multiple objectives. For example, a social digital twinning platform for innovative last-mile delivery solutions may aim to assess consumer delivery method choices within their social environment. However, no single tool can achieve all objectives. Different simulators exist for consumer behavior and freight transport. Therefore, we propose a high-level architecture and present a blueprint for a generic modelling framework. This includes defining modules, input/output data, and interconnections, while addressing data suitability and compatibility risks. We demonstrate the framework’s effectiveness with two real-world case studies.

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.

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.

As the rapid growth of urban e-commerce increases the volume of last-mile deliveries, logistics service providers have difficulty in meeting the demand of on-demand consumer requests. This increase in demand challenges traditional delivery, with some parcels becoming disproportionately costly to deliver to their destinations. To address this, we introduce a cost-based outlier parcel selection mechanism that identifies parcels with a high negative impact on the marginal delivery costs. These outlier parcels are then eliminated from their tours and outsourced to a crowdshipping market, where individuals combine the delivery task with their already planned trips. We use unique data on delivery tours of six service providers for the province of South Holland in the Netherlands. The cost-based decision rule for identifying outlier parcels results in a low proportion of outsourcing to the crowdshipping market compared to earlier literature. We identify only about 1 % of the total parcel demand as outliers across all carriers combined. Of these outlier parcels, the proportion selected for crowdshipping based on their cost efficiency ranges from 42.78 % to 3 %, depending on the scenario. While crowdshipping provides a viable solution for handling a small portion of last-mile deliveries, its environmental and economic sustainability is restricted by factors such as compensation rates and the delivery mode used. This study demonstrates that outsourcing high-cost outlier parcels to crowdshipping can be cost-efficient and reduce emissions of last-mile logistics companies; however, the proportion of these parcels is very small, limiting the overall impact on sustainability.

The growing demand for parcel delivery contributes to traffic congestion, high emissions, and rising costs of freight logistics, particularly in urban areas. To address these issues, new and sustainable last-mile delivery methods must be implemented. However, estimating the impact of different logistics systems is complex, as it depends heavily on consumer adoption of these new delivery methods. This paper presents a simulation model that captures and explores the interconnections between multiple last-mile delivery methods and corresponding consumer preferences. Two key factors affecting consumer preferences are simulated: (1) consumers’ response to the performance and availability of delivery methods, and (2) the sharing of knowledge through word of mouth and familiarisation. System dynamics is applied at the aggregate level to simulate the evolution of consumer preferences for last-mile delivery across multiple methods. At the disaggregate level, an agent-based model simulates the operational performance of these delivery methods, which in turn influences consumer preferences in the system dynamics model. This integrated approach allows for the observation of the evolving interaction between urban logistics supply and demand, providing key performance indicators on consumer preferences and the delivery method operations at consecutive time points. The developed simulation model is applied to a case study in the Rotterdam-The Hague region, a highly urbanised region in The Netherlands. Results show that consumer preferences strongly depend on the carriers’ ability to fulfil the demand. The dynamic interaction between supply and demand creates a reinforcing feedback loop, where the adaptability of carriers is crucial for the long-term success of a delivery method. Additionally, the spatial results reveal that there are zonal differences in the performance of the delivery methods. Further findings indicate that, while total vehicle kilometres and CO₂ emissions will rise due to increasing parcel demand in all scenarios, the average number of van kilometres and CO₂ emissions per parcel will decrease as demand grows.

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.

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.

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.

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.

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.

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.

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.

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.

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.