On the eve of the large-scale introduction of electric vehicles, policy makers have to decide on how to organise a significant growth in charging infrastructure to meet demand. There is uncertainty about which charging deployment tactic to follow. The main issue is how many of charging stations, of which type, should be installed and where. Early roll-out has been successful in many places, but knowledge on how to plan a large-scale charging network in urban areas is missing. Little is known about return to scale effects, reciprocal effects of charger availability on sales, and the impact of fast charging or more clustered charging hubs on charging preferences of EV owners. This paper explores the effects of various roll-out strategies for charging infrastructure that facilitate the large-scale introduction of EVs, using agent-based simulation. In contrast to previously proposed models, our model is rooted in empirically observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. In addition, the simulation incorporates different user types (inhabitants, visitors, taxis and shared vehicles) to model the diversity of charging behaviours in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging) and the intensity of rollout (EV to charging point ratio). The simulation predicts both the success rate of charging attempts and the additional discomfort when searching for a charging station. Results suggest that return to scale and reciprocal effects in charging infrastructure are considerable, resulting in a lower EV to charging station ratio on the longer term.
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What is this publication about?In this publication on ‘New urban economies’, we search for answers and insights to a key question: how can cities foster economic development and develop ‘new urban economies’. And, importantly, how can they do that:◗ in concertation with different urban stakeholders, ◗ responding adequately to key challenges and developments beyond their control, ◗ building on the cities’ own identity, industries and competences, ◗ in a sustainable way, ◗ and without compromising weaker groups.
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Developers of charging infrastructure, be it public or private parties, are highly dependent on accurate utilization data in order to make informed decisions where and when to expand charging points. The Amsterdam The Amsterdam University of Applied Sciences in close cooperation with the municipalities of Amsterdam, Rotterdam, The Hague, Utrecht and the metropolitan region of Amsterdam developed both the back- and front-end of a decision support tool. This paper describes the design of the decision support tool and its DataWareHouse architecture. The back-end is based on a monthly update of charging data with Charge point Detail Records and Meter Values enriched with location specific data. The design of the front-end is based on Key Performance Indicators used in the decision process for charging infrastructure roll-out. Implementing this design and DataWareHouse architecture allows all kinds of EV related companies and cities to start monitoring their charging infrastructure. It provides an overview of how the most important KPIs are being monitored and represented in the decision support tool based on regular interviews and decision processes followed by four major cities and a metropolitan region in the Netherlands.
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The Dutch Environmental Vision and Mobility Vision 2050 promote climate-neutral urban growth around public transport stations, envisioning them as vibrant hubs for mobility, community, and economy. However, redevelopment often increases construction, a major CO₂ contributor. Dutch practice-led projects like 'Carbon Based Urbanism', 'MooiNL - Practical guide to urban node development', and 'Paris Proof Stations' explore integrating spatial and environmental requirements through design. Design Professionals seek collaborative methods and tools to better understand how can carbon knowledge and skills be effectively integrated into station area development projects, in architecture and urban design approaches. Redeveloping mobility hubs requires multi-stakeholder negotiations involving city planners, developers, and railway managers. Designers act as facilitators of the process, enabling urban and decarbonization transitions. CARB-HUB explores how co-creation methods can help spatial design processes balance mobility, attractiveness, and carbon neutrality across multiple stakeholders. The key outputs are: 1- Serious Game for Co-Creation, which introduces an assessment method for evaluating the potential of station locations, referred to as the 4P value framework. 2-Design Toolkit for Decarbonization, featuring a set of Key Performance Indicators (KPIs) to guide sustainable development. 3- Research Bid for the DUT–Driving Urban Transitions Program, focusing on the 15-minute City Transition Pathway. 4- Collaborative Network dedicated to promoting a low-carbon design approach. The 4P value framework offers a comprehensive method for assessing the redevelopment potential of station areas, focusing on four key dimensions: People, which considers user experience and accessibility; Position, which examines the station's role within the broader transport network; Place-making, which looks at how well the station integrates into its surrounding urban environment; and Planet, which addresses decarbonization and climate adaptation. CARB-HUB uses real cases of Dutch stations in transition as testbeds. By translating abstract environmental goals into tangible spatial solutions, CARB-HUB enables scenario-based planning, engaging designers, policymakers, infrastructure managers, and environmental advocates.
There is increasing interest for the use of Virtual Reality (VR) in the field of sustainable transportation and urban development. Even though much has been said about the opportunities of using VR technology to enhance design and involve stakeholders in the process, implementations of VR technology are still limited. To bridge this gap, the urban intelligence team of NHTV Breda University of Applied Sciences developed CycleSPEX, a Virtual Reality (VR) simulator for cycling. CycleSpex enables researchers, planners and policy makers to shape a variety of scenarios around knowledge- and design questions and test their impact on users experiences and behaviour, in this case (potential) cyclists. The impact of infrastructure enhancements as well as changes in the surrounding built environment can be tested, analysed an evaluated. The main advantage for planners and policy makers is that the VR environment enables them to test scenarios ex-ante in a safe and controlled setting.“The key to a smart, healthy and safe urban environment lies in engaging mobility. Healthy cities are often characterized by high quality facilities for the active modes. But what contributes to a pleasant cycling experience? CycleSPEX helps us to understand the relations between cyclists on the move and (designed) urban environments”
The pipelines are buried structures. They move together with the soil during a seismic event. They are affected from ground motions. The project aims to find out the possible effects of Groningen earthquakes on pipelines of Loppersum and Slochteren.This project is devised for conducting an initial probe on the available data to see the possible actions that can be taken, initially on these two pilot villages, Loppersum and Slochteren, for detecting the potential relationship between the past damages and the seismic activity.Lifeline infrastructure, such as water mains and sewerage systems, covering our urbanised areas like a network, are most of the times, sensitive to seismic actions. This sensitivity can be in the form of extended damage during seismic events, or other collateral damages, such as what happened in Christchurch Earthquakes in 2011 in New Zealand when the sewerage system of the city was filled in with tonnes of sand due to liquefaction.Regular damage detection is one of key solutions for operational purposes. The earthquake mitigation, however, needs large scale risk studies with expected spatial distribution of damages for varying seismic hazard levels.
