Policy makers, from small municipalities to (inter)national government agencies, consult transport models output in order to enrich their decision-making process with as much information as possible. This makes the demand for specific and promptly available modelling data often bigger than actually can be met within the available personnel or budget. For this reason, quick scan tools are used in various stages of policy making. These tools shortcut the modelling process by employing less data, less calibration and less theoretically underpinned modelling approaches than proper transport models. Obviously, such tools cannot provide the same detail and quality than full transport models, and are therefore often dismissed in the community of traffic models as negligible at best, but most often are characterized as misleading and harmful to the decision-making process if applied beyond their scope.

However, the need for these tools is high and they are used in practice despite their reputation. Quick scan tools therefore can play an important role in the decisionmaking process. However, so far the quality of such tools and their role in the process of evaluating transport policy schemes is a topic that has gained little to no attention in the scientific community researching transport models. By rejecting the whole concept of quick scan tools, the chance has been missed to actually assess such tools with the necessary (scientific) scrutiny, in order to ensure that they are in the best shape they can be. As a result, at the moment, there is no common understanding on what these tools are or should be, what the minimum quality standards of such tools should be, and how they should be used in the different phases of transport planning.

This paper aims to discuss the pros and cons when it comes to working with quick scan tools, in the hope to kick-start a broader discussion about how to employ such tools in the best way possible. We discuss the challenges that come with making a tool that supports its users to perform meaningful analyses while limiting the possible interactions with the data/tool to an acceptable minimum. We address these issues by describing the design principles and procedural arrangements we apply to the quick scan tool owned by the Dutch Ministry of Infrastructure and Water Management, the ‘Mobiliteitsscan’ (Mobility Scan).@en

Nowadays traffic management is a complex task. Policy choices have to be made and operational decisions have to be taken on how to deal with car, trucks, busses, bicycles and pedestrians in the network and how to keep them safe and flowing, especially where they interact. Without a clear and transparent framework to base these decisions upon, problems and arbitrariness could occur. Sustainable regional and urban mobility requires a widely supported vision on the desired use of the different networks. A multimodal network management framework offers such a vision. It is a translation from mobility policy into and clear and unambiguous description of the desired situation for the different networks. Which mode has priority on route X? What is the average travel time mode Y has to meet? Which operational speed is the target for the bus on relation A-B? To compare this ideal situation with the actual one, it becomes clear where challenges are and bottlenecks between modes become visible. For the bottlenecks, policy makers and traffic managers can formulate solution directions in line with the desired situation for the networks.

The translation from a mobility policy into the desired situation is done in six steps
1. Start the project and involve all relevant stakeholders. In this step the goals of the project should be clearly defined.
2. Determine the basic principles and list the policy objectives are listed. What are the current agreements and ambitions for traffic and transport in the city or region?
3. Determine accessibility profiles. Accessibility profiles are the basic principles, but more specific and further detailed per area.
4. Determine the functional arrangement and describe and map the intended use of the network.
5. Decide on priorities to facilitate and manage traffic on those links. Choices have to be made: between traffic of different modes and functions, but also between the same modes and different functions.
6. Formulate the frame of reference, combining all results from the previous steps. Also, the practical consequences of policy choices are covered.

In the paper the steps are described in more detail and some applications of the multimodal network management framework are given.@en

Dit is de elfde uitgave van Verkeer in Nederland. We beginnen daarmee aan ons derde lustrum – een goede reden om de vormgeving onder handen te nemen, vonden we. We vroegen de vormgever om ‘herkenbaar maar met frisse look’ en dat hebben we gekregen ook. Ook voor de inhoud hebben we gekozen voor ‘herkenbaar maar
fris’. Ook voor de inhoud hebben we gekozen voor ‘herkenbaar maar fris’. In het eerste hoofdstuk komen, zoals elk jaar, de kale cijfers voorbij. Hoofdstuk 2 gaat, ook zoals elk jaar, over de thema’s die spelen.We maken daarin natuurlijk een beetje onze eigen keuzes: wat viel ons op en wat doet er volgens ons toe? Dan de hoofdstukken drie tot en met vijf, over onderzoek, pilots en programma’s. Ook die zijn qua opzet herkenbaar, maar fris van inhoud.

Daarmee biedt deze 2024-uitgave weer een mooie snapshot van het verkeer en vervoer in Nederland. Uit de cijfers blijkt dat er nog veel te doen is om ons mobiliteitssysteem goed en gezond te houden. Dat is allerminst eenvoudig, want ons overzicht leert ook dat de materie er alleen maar complexer op wordt. Maar ook is duidelijk hoe gevarieerd het vakgebied is. Wiskunde, technologie, AI, gedrag: het komt allemaal samen in verkeer en vervoer. Alle reden dus om breed te blijven investeren en onderzoeken. Dat gebeurt gelukkig ook, merken we. Maar dat is voer voor de uitgave van volgend jaar!@en

Dedicated Lanes (DLs) have been proposed as a potential alternative for the deployment of Connected and Automated Vehicles (CAVs) to facilitate platooning and increase motorway capacity. However, the impact of the presence and utilization policy of such a lane on drivers’ preference to use automation and their behaviour has not yet been thoroughly investigated. In this study, a driving simulator experiment is conducted, where participants drive a CAV in the presence of a DL with different utilization policies. Drivers have the possibility to choose between driving in an automated mode or in a manual mode. In automated mode they could adjust the driving speed and time headway and initiate automated lane changes. Two utilization policies were examined: mandatory versus optional use of DLs when driving in an automated mode. The impact of the presence and utilization policy of the DL on drivers’ preference to use automation and their behaviour in car-following and lane changing are investigated. The study found that while the presence of a DL does not increase drivers’ preference for automation use, it encourages drivers to utilize the DL more when the utilization policy is mandatory (i.e., drivers can only use automation mode when driving on this lane). Furthermore, drivers are more conservative in automated mode and when driving in mixed traffic. However, they perform closer car-following and merge into smaller gaps when driving on DLs which on one hand can increase the capacity of the DLs, but on the other hand can increase the risk of collisions. These results are useful for road operators, and in setting-up a more realistically traffic simulation studies.

@en

The interplay between infrastructural development and transport policy measures requires comprehensive assessment methodologies to guide decision-making processes. Existing methodologies often fall short of encompassing the multifaceted nature of transport systems, the variety of stakeholder interests, and the broader social and environmental impacts. This chapter introduces the Assessment Method for Policy Options (AMPO), a framework designed to address this complexity by integrating cost-benefit analysis (CBA) and multi-criteria analysis (MCA) while promoting stakeholder engagement.

The background to this initiative stems from an identified gap within existing transport policy assessment frameworks. Traditional methods such as CBA, while methodologically sound, often overlook the socio-political dimensions inherent in infrastructure development and maintenance. Moreover, the dynamic nature of societal needs and environmental considerations calls for a more adaptive and inclusive approach to transport planning and assessment. In response to these challenges, the AMPO emerges as a comprehensive tool that aims not only to bridge the gap between quantitative and qualitative analysis but also to harmonise the myriad perspectives and objectives of stakeholders.

This chapter defines the structure and application of the AMPO and highlights its potential as a tool for transport policy and infrastructure planning. The sections in this chapter are methodically structured to provide insights into the AMPO. Section 5.2 describes the scope and other aspects of the AMPO and provides clarity on its application and relevance. Section 5.3 explains the ten steps of the AMPO and provides a detailed guide to its implementation. Section 5.4 presents a case study that demonstrates the practical application and effectiveness of the AMPO in a real-life scenario. Section 5.5 introduces the AMPO tool, a digital tool designed to facilitate the application of the AMPO framework. Finally, Section 5.6 provides a synthesis of the findings and provides recommendations for the future application of the AMPO to ensure its continuous development and relevance for transport policy and infrastructure development.@en

Ons mobiliteitssysteem inclusiever maken, komt voor een belangrijk deel neer op het slechten van barrières. Het gaat dan al snel om maatregelen in de categorie stations toegankelijker maken en de fietsinfrastructuur verbeteren. Maar is er ook winst te behalen met verkeersmanagement? Een beetje, aldus Isabel Wilmink en Henk Taale, die dit in een TrafficQuest-challenge onderzochten.@en

Within the area of mobility much discussion is going on about human well-being and how mobility can contribute to that. Human well-being is about everything what influences the well-being of people, in the broadest sense. It is about welfare beyond the Gross Domestic Product (GDP). Mobility makes a valuable contribution to the welfare and well-being of people. It provides means for them so that they can reach important destinations and participate in activities, like jobs, all kinds of facilities (cultural, shopping, recreation, etc.) and social contacts. In this way mobility has a positive effect on physical and mental health. However, mobility can also decrease well-being, for example due to traffic unsafety, noise and environmental pollution and climate change. Also, the pros and cons of mobility could be unevenly distributed among certain groups of people, regions or even generations. In this paper we look at the current contributions of traffic management to human well-being and we search for opportunities that could increase these contributions. The research consisted of a literature scan and two workshops. In the first workshop traffic management experts were connected with experts with a focus on human well-being. Together they discussed the possibilities of traffic management in relation to human well-being. In the second workshop the findings from literature and the first workshop were discussed with experts from the Dutch national road authority Rijkswaterstaat to test how these findings are aligned with practical experience. The literature scan showed that not many studies make a clear link between traffic management and human well-being. The current focus of traffic management is mainly on accessibility (travel times and delays) and traffic safety. Widening this perspective to the dimensions of health and the living environment is desirable and advisable. There is also a gap between traffic management, that is mainly focussing on the short-term solution of specific problems, and the more umbrella approach of well-being. The opportunities of (operational) traffic management to directly contribute to human well-being are currently limited, due to the way that traffic management is organised. Policy should make clear choices and give directions with respect to the goals that should be achieved with traffic management. Then traffic management can apply those directions in practice, using a network perspective and the experience with multimodal approaches and distribution of the scarce capacity in all kinds of networks, to find the desired balance between the various societal goals.@en

Het wordt steeds belangrijker om vanuit een breder perspectief naar mobiliteits-vraagstukken te kijken. Dit houdt in dat we niet alleen kijken naar de impact van beleidsmaatregelen op bijvoorbeeld het fileprobleem, maar een goede afweging moeten maken tussen maatregelen aan de hand van de effecten op alle vier dimensies die in het kader van brede welvaart genoemd worden: bereikbaarheid, leefbaarheid, veiligheid en gezondheid. Daarbij is het ook van belang om zowel de effecten op de korte, middellange en lange termijn in ogenschouw te nemen én te kijken naar zogenaamde verdelingseffecten. Dit laatste heeft betrekking op de groepen die wel of niet profiteren van bepaalde beleidsmaatregelen. In deze paper is gekeken naar deze verdelingseffecten met behulp van data uit het Landelijk Reizigersonderzoek van het Ministerie van Infrastructuur en Waterstaat. Dit onderzoek wordt sinds 2019 jaarlijks uitgevoerd onder een representatieve steekproef van de Nederlandse bevolking van 18 jaar en ouder. De grootte van de steekproef (N=10.000 tot 12.000) maakt het mogelijk om diverse uitsplitsingen naar achtergrondkenmerken te onderzoeken. Voor bereikbaarheid hebben we ingezoomd op de subjectieve bereikbaarheid (hoe denken mensen zelf over de bereikbaarheid van voorzieningen), voor leefbaarheid op het parkeren bij de woon- en werklocatie, voor veiligheid op de invloed op de vervoerwijzekeuze van de ervaren veiligheid op de fietsroute van en naar het werk en voor gezondheid op de beweegnorm in het woon-werkverkeer. Bij elke indicator zijn uitsplitsingen gemaakt naar leeftijd, opleidingsniveau en stedelijkheid van de woonlocatie. We vinden voor alle indicatoren significante verschillen op deze kenmerken. Zo beoordelen ouderen de bereikbaarheid van voorzieningen hoger dan jongeren en voldoen werknemers die wonen in zeer sterk stedelijke gebieden en gebruik maken van actieve vervoerwijzen voor het woon-werkverkeer vaker aan de beweegnorm in vergelijking met inwoners van minder sterk stedelijke gebieden. Deze analyses en de gevonden verschillen tonen het belang van het meenemen van verdelingseffecten in de afweging van beleidsmaatregelen aan. Ook laten de analyses zien dat instrumenten zoals het landelijk reizigersonderzoek geschikt zijn om deze effecten in kaart te brengen. Wel zijn nadere analyses nodig om de gevonden verschillen beter te kunnen duiden en verklaren. @en

Route guidance in traffic management aims to improve traffic network performance aligned with a system optimum. However, service providers commonly offer user optimum travel advice that can negatively impact centralized route guidance. This paper quantifies and demonstrates the impact of different policy strategies for a centralized route guidance systems where road authorities and service providers work together in a coordinated approach. Cooperation through an intermediary is considered with various policy strategies that consider different approaches and levels of cooperation between road authorities and service providers, which are evaluated using traffic modelling. A use case for the ring network of Milan shows that cooperation between the two parties has the potential to get the best out of the measure by utilizing a system optimum approach, while still allowing service providers to offer individual travel advice. The results of the modelled case study clearly show that the two approaches of far-reaching cooperation and increased compliance have a greater positive effect on traffic network performance in terms of reduced delays, reduced congestion and total time spent. In addition, the future presence of connected automated vehicles (CAV) is also considered in which these vehicle demonstrate full compliance. This shows that with increasing percentage of CAVs that route guidance can have a substantial positive effect compared to low compliance or a smaller penetration rate of automated vehicles.@en

One of the options to reduce CO2 emissions as a result of transport, is to decrease the number of vehicle kilometres driven. Carpooling and teleworking are possibilities to obtain that goal. The paper will analyse their potential contribution.@en

Momenteel wordt binnen het vakgebied mobiliteit veel gesproken over brede welvaart en hoe vanuit de mobiliteitssector hieraan bijgedragen kan worden. Van oudsher was het mobiliteitsbeleid vooral gericht op het verbeteren van de bereikbaarheid. Naast het oplossen van knelpunten door de uitbreiding van de infrastructuur speelde verkeersmanagement daarin een belangrijke rol. Dat leidt tot de vraag hoe verkeersmanagement bijdraagt aan brede welvaart en of er veranderingen nodig zijn om dit beter te doen. Om deze vragen te beantwoorden is er een literatuurscan gedaan en zijn er workshops met verschillende experts gehouden. Uit de literatuur blijkt dat verkeersmanagementmaatregelen gericht zijn op een bepaalde dimensie van brede welvaart (bereikbaarheid), zonder dat er een afweging met de andere dimensies (veiligheid, leefbaarheid en gezondheid) gemaakt wordt. Ook laat de literatuur zien dat gemotoriseerd verkeer onbedoelde negatieve effecten heeft op de dimensie gezondheid, van zowel reizigers als niet-reizigers. Daarnaast is er aandacht voor de verdeling van effecten in de gezondheids- en bereikbaarheidsdimensie. De workshops lieten zien dat de bijdrage van verkeersmanagement aan brede welvaart in de praktijk nog vrij smal is en dat het beleid de keuzes maakt en niet de verkeersmanager, zodat er voor hem weinig speelruimte is. Ook is duidelijk dat het geografisch schaalniveau van belang is, omdat het veel uitmaakt of je verkeersmanagement toepast op autosnelwegen of in de stad. Verbreding naar brede welvaart lijkt in ieder geval niet zo eenvoudig te zijn. Maar er zijn wel mogelijkheden, zoals meer sturing en het versterken van de interactie tussen verkeers- en mobiliteitsmanagement, de monitoring en evaluatie uitbreiden voor brede welvaart en een verandering van zienswijze om te komen tot een bredere denk- en werkwijze.@en

In the Netherlands, one of the main goals of the Ministry of Infrastructure and Water Management is to increase accessibility and, at the same time, to reduce the negative externalities created by transport, such as congestion and greenhouse gas emissions. Within the Ministry, there was a clear need for a national and integrated monitoring instrument to measure the impact of policy measures on travel behaviour. To satisfy this need, we carried out a national traveller survey in 2019, 2020 and 2021. This paper describes some of the results of these surveys. Annual analyses include the trends in car ownership and mode choice for different purposes, with particular attention to commuting behaviour. It appears that travel time, convenience and flexibility play an important role in mode choice. Travel costs are less important and COVID-19 did not play a decisive role. It appears that free parking or availability of parking space has the most considerable impact on car use for commuting. In October 2019, employees travelled on average 3.8 days per week to work. In October 2020, mainly because of COVID-19, this number decreased to 2.9 travelling days and in October 2021, the number of travelled increased to 3.1. We examined the relationship between changes in car use for commuting between 2019, 2020 and 2021, and external developments in living and working, changes in the level of service of different transport modes and policy measures, both by the government and by employers. In addition, we investigated the influence of the COVID-19 pandemic on car use for commuting and this appeared to be an important factor, although external factors also play an important role. Finally, we estimated the effect of these changes in car use for commuting on congestion and CO2 emissions.@en

Kunstmatige of artificiële intelligentie, kortweg AI, speelt een steeds grotere rol in ons leven. Ook ons werkterrein verkeersmanagement kan er niet omheen: AI heeft zich al aardig weten binnen te werken in onze data-analyses en verkeerslichten. In deze bijdrage schetsen de auteurs de stand van zaken. Wat is AI? Wat kunnen we ermee? En met welke risico’s hebben we te maken?@en

The field of Artificial Intelligence (AI) seems promising for traffic and transport. All kinds of possibilities and applications are suggested, but are these suggestions feasible and when will they become available? To address this question for traffic management, a picture of the field and its latest, state-of-the-art innovations is painted and opportunities for the future are investigated. Applications that have already been implemented or tested as pilots are described, as well as those applications that domain experts expect to be developed within one to five years, with a focus on applications that generate the greatest improvements in terms of traffic flow, safety, and sustainability. Also, the study looks at what the possible pitfalls and challenges could be during development and implementation. The research method consisted of several elements. Interviews were conducted with experts in the field of AI and traffic management and the interviewees were asked about possible opportunities and obstacles. In addition to the interviews, relevant and current sources describing applications of AI in traffic management were studied. The focus was on the added value of applications that have already been implemented. Based on the information gathered, a selection of the most promising future applications was made and these applications were discussed in a workshop. The current applications of AI in traffic management show that the focus is now on performing one specific task, using a limited number of data sources. It also shows there is great future potential for AI-based applications that combine multiple data sources or address multiple complex tasks in a combined fashion. This could, for example, lead to new insights about traffic being derived from data; insights that are not readily apparent with existing methods and a single data source.@en