Background: New challenges in urban development
The last decade has produced extensive and convincing proof that the world today is facing environmental threats of an unprecedented scale in human history, which, moreover, concerns environmental issues far beyond the predominant debate on climate change (E.g. Rockström et al., 2009). There is also an on-going debate regarding attractive, safe and beautiful urban environments, especially in the aftermath of the modernistic city-planning paradigm. This put unprecedented expectations on the future governance, planning and design of cities, which increasingly, given the right strategies for their future development, are seen as the means to the solution rather than the root of the problem. However, this also creates knowledge demands that the practices in these fields currently are not prepared for; there typically is an implementation deficit.
Critical in this respect is the lack of comprehensive models of cities that bridges disciplinary boundaries, both academic and professional. Central here is the professional divide between what we may broadly term planners and architects, where the term planners are an amalgamation of road planners, public transport planners, town planners, etc. While there often has been an unfortunate lack of report between these categories, we may more recently see research directions that take increasing interest in each other’s fields. On the one hand, we have seen a decisive increase of interest transport modelling for pedestrian movement and walkability, areas earlier primarily addressed in architecture and urban design. On the other hand, we have space syntax research that grow out of architecture but has developed a methodology with affinities to urban modelling in planning. However, so far little has been attempted in actually linking all these in the aim of developing more comprehensive models. These models may be very important in planning routes for the entire trip; current models (like the ones used in Google maps) are more focused on planning trips per transport category.
This is unfortunate in several respects.
First, in any attempt to understand urban development, we know that the relation between transport and land-use is absolutely central. Even so, we have predominantly applied models that prioritise particular transport modes, especially private cars, while excluding others, such as biking and walking. The effect has been that one at the same time thwarts the reality of urban mobility and promotes particular subsystems.
Second and more specifically, the single most addressed issue in contemporary studies, policies and practices in sustainable urbanism is the need to increase public transport, for instance in concepts like transport oriented design (TOD). Again, this demands comprehensive models where public transport may be put in relation to other travel modes for a true understanding of the efficiency of such policy or we will produce ineffective policy. T
Third an more generally, there is broad agreement on the need to understand cities as systems, implying that the relation between its parts to some degree may prove more important than the properties of the parts in themselves, not least in the perspective of sustainability. However, essential for any systems thinking is to identify both the character and quantity of the flows between the different parts of the system. In cities, flows are primarily constituted by people, why any understanding of the city as a system demands a comprehensive mobility model.
There is therefore an urgent need to begin the development of integrated and comprehensive urban mobility models, both to support the further knowledge development of urban systems, especially to understand them dynamically over time, and to support current professional practice facing unprecedented challenges. In extension, we also see the potential of such models in informing the public and thereby supporting participatory processes in urban development.
Aim: Integrating transport modelling with space syntax
In this project we aim to take on this urgent challenge essential for a successful change towards more sustainable trajectories in contemporary urban systems. More specifically we aim to integrate current state of the art transport models both for trains and cars with the latest developments in space syntax methodology, thus integrating small-scale, soft and cognition driven mobility in cities with large scale, hard and technology driven mobility.
Hence, there are two major aims of this project. On the one hand to develop empirical knowledge about the ability of the spatial form of local street networks to benefit from large road investments. On the other hand, to develop methodological knowledge on how to combine and integrate different modelling traditions, in this case traditional transport planning models and space syntax.
The first aim concerns the fact that any major infrastructural investment of this kind must be continued on the smaller scale to have desired consequences. The true distribution and size of the effects of such investments are largely due to the spatial form and structure of the local street network used by cars, bikes and people walking. It is here that the primary flows of people take place and give rise to variations of co-presence and opportunities for exchange, with critical influence on local markets, rents, perception of security, social capital, well being etc, which together represent immense values both in monetary and other terms.
Moreover, the spatial form of the street system constitutes a fundamental variable possible to change and adopt through urban design, why it is essential to develop our knowledge of it effects. We here see the potential to adjust and learn from earlier experiences in how to develop cities and smaller towns so that they may benefit as much as possible from infrastructural investments, something that often has been missed in such projects at great loss to them.
The second aim concerns the exploration of combining space syntax to extant transport models. To fully understand travel behaviour and to be able to successfully plan and design for urban mobility we naturally need to create more life like models that integrates many if not all transport mode, what is called multi-modal transport models. There are two major obstacles for such modelling. First, to include pedestrian movement in such models and, to increasing degree, also bicycle travel. Second, to accurately modelling the critical links between different transports modes.
In both of these regards we see interesting developments taken in integrating space syntax to regular traffic models (Gil 2012; Gil & Read 2013), the benefit being the proven ability of space syntax to capture pedestrian movement. By creating such multi-modal models the opportunity to seamlessly analyse the performance of the complete transport network are made possible, whether from overarching sustainability aims of socio-economic cost-benefit analyses.
Right now there are also efforts to standardize and create descriptions for this kind of multi-modal networks, so we have also a possibility to participate in this effort, as well as getting benefits from it.
Case study E39: the ability of spatial form to benefit from road investments
This project will have as its basis the new ferry free E39 connecting a long series of mid-size cities and smaller towns along the western cost of southern Norway, stretching from Trondheim to Kristiansand. While we may know a lot about the impact of such investments on interurban travel behaviour, land-use development and urban growth, we know far less about how such huge investments affect the local environments on a detailed scale within cities and towns; how restructured and increased mobility is distributed locally and in turn affect the allocation of local land uses. While this may seem minor effects, the argument can be turned around; any major mobility and/or land use change must be grounded locally to have true effect.
Professor at Architecture, Urban Design and Planning
Funding years 2015–2019
Area of Advance
Chalmers Driving Force