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This is an extract from a positioning paper I recently co-authored for Space Syntax around the future of the city. This post is an extract of the longer-term risks and opportunities.

The paper set out short- and long-term issues facing society, and suggested opportunities for technology to help address them.

Existing and emerging technologies provide potential solutions, but these need to be developed carefully to deliver a vision that everyone supports. Without going through this process and agreeing a social contract to operate them within, the risks have been widely publicised: a surveillance state, loss of privacy, loss of control and lives being ruled by multi-national tech giants.

This post sketches out a positive future supported by technology, where, in an older, post-work society, the city as an organisation plays a different role. In this future, tech provides a platform to stimulate local economic activity, provide access to services, develop new models of housing, protect privacy, and by integrating all of these, to attempt to address inequality.

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Data

There are lots of interesting things going on using data in cities at the moment. Many articles and blog posts talk about how data, and open data in particular, has the potential to deliver public services better, start to address long-term outcomes (such as health problems), and create a basis for decision-making. In times when public sector funding is under pressure delivering these outcomes is even more important than normal.

Collecting data in cities is helpful as it provides something to measure progress against. It means measuring specific outcomes, which also means being very precise about what outcomes are important.

It can also be a link between deciding a wider objective (improve air quality) and a specific implementable actions (make public transport free). However, to do this requires both domain and data expertise:

  • to understand the difference between data on the outcomes of a system, and the variables in that system
  • to measure and analyse the urban systems that form the variables
  • to know how data is recorded on urban systems and what it actually represents Read More

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This is both a follow-up to an earlier post on filtered permeability in de Beauvoir, and a response to the current Walford Road area consultation.

The earlier post identified three negative impacts of filtered permeability:

  1. Filtered permeability breaks the street network and pushes traffic away from “residential streets” on to the surrounding roads which increases congestion, air pollution, and journey times.
  2. By describing these areas as “residential streets” it implies that no one lives anywhere else. Often the streets that traffic is filtered towards are actually high streets with higher densities and a wider mix of uses. There are consequently more people on them, and therefore more people exposed to increased traffic and air pollution.
  3. The streets where traffic has been restricted are already quiet, and experience further reductions in natural surveillance, reducing personal safety (and the perception of safety).

These points were made on the basis of street network analysis, and some further investigations in to the distribution of land use and density in and around de Beauvoir.

A further consideration in the earlier study is that the resulting distribution of traffic volumes (and air pollution) is socio-economically distorted: higher density, multi-dwelling, buildings are more exposed to traffic, while lower density houses are less exposed.

The drive for filtered permeability is to encourage cycling, and this is positive for many reasons. However, cities are complex systems that work across many scales simultaneously, and are formed from different layers of infrastructure, public transport, land use, density, and people, all of which need to be considered in an integrated way.

The last fifty years of urban planning, and specifically the dominance of traffic engineering, shows how negative outcomes for the whole city arise by working with one infrastructure system in isolation from the others. Despite the positive objective, the risk of using filtered permeability to try to deliver improved cycling infrastructure is that it will create unintended negative outcomes across the wider area.

Hackney council currently has a consultation running to extend a filtered permeability scheme further north into Stoke Newington. This post uses spatial network analysis to test the impact of these new proposals.

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This is the summary of a talk I gave recently at a Mob Ox event in Oxford. It picks up some of the ideas in this post about Uber, and is especially relevant in relation to Waymo’s recent announcement.

It focusses on some work we’ve been doing to understand how infrastructure and land use interact in cities, and uses this to frame the conversation around these mobility services

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Culford_Rd

A couple of weeks back the Design Council Newsletter re-published some work from 2014, looking at how Hackney had become one of the most liveable boroughs in London. This is evidenced by an increase in people cycling to work and a decline in those driving – both around or over 10%.

One of the reasons set out for this change in behaviour is the success of policies implemented over the last 10 years, which include re-designing residential streets. In particular the use of “filtered permeability” – using bollards to make some streets only accessible to pedestrians and cyclists – is described as part of this achievement.

Increasing active travel share and decreasing private car use is very positive, however, closing streets immediately raises questions around the wider impacts.

In a very quick summary there are three major issues with filtered permeability:

  • Fragmented networks increase congestion and lengthen car trips
  • Increased likelihood of air pollution in higher density, mixed use areas
  • Reduced levels of natural surveillance impact personal safety

These points are expanded in the post below: Read More

As Uber has lost its license to operate in London, here are some points about the potential it offers and how it could be improved further:

1. Provide mobility in places traditional public transport can’t work

2. Apply dynamic pricing in a progressive way

3. Provide driver facilities

These are described in a little more detail below – this is all written from an urban perspective, and excludes everything around business ethics, personal safety, insurance  etc which has had a lot of coverage in the mainstream media.

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Centrelines

These are some notes from a talk I gave at Space Syntax’s last Urban Imperative: Improve, Extend, Create series of events in July. It looks at how to think about designing a city from scratch. The focus of this post is to look at exactly which components of a masterplan to design and why.

This shows some work that is slightly experimental. At the moment it’s about testing ideas through a process, and at the moment it’s only a process. It started as a real project to look at ideas about how to develop a city from scratch but then some further research work was done.

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This is a research paper I recently presented at the 11th Space Syntax Symposium in Lisbon, co-authored with Stephen Law and Laurens Versluis.

The paper has been reformatted for re-production here and the original published version can be found here .

 

Abstract

This paper describes an exploratory methodology used to study the national scale issues of population growth and infrastructure implementation across the UK. The project was carried out for the Government Office for Science in 2015, focussing on two key questions: how could a “spatially driven” scenario provoke new thinking on accommodating forecast growth, and; what would be the impact of transport infrastructure investments within this context.

Addressing these questions required the construction of a national scale spatial model that also needed to integrate datasets on population and employment. Models were analysed and profiled initially to identify existing relationships between the distribution of population and employment against the spatial network. Based on these profiles, an experimental methodology was used to firstly identify cities with the potential to accommodate growth, then secondly to allocate additional population proportionally. This raises important questions for discussion around which cities provide the benchmark for growth and why, as well as what the optimal spatial conditions for population growth may be, and how this growth should be accommodated locally.

Later the model was used to study the impact of High Speed Rail. As these proposed infrastructure changes improve service (capacity, frequency, journey time), rather than creating new topological connections, the model was adapted to be able to produce time based catchments as an output. These catchments could then be expressed in terms of the workforce population within an hour of every city (a potential travel to work area), as well as the number of employment opportunities within an hour of every household.

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