I recently started to get involved in a discussion on Twitter about the merits of low traffic neighbourhood (LTN) schemes. Generally I am much in favour of these, which I see as giving great improvement to the quality of life in residential streets, as well as being part of a bigger movement to reduce car dependence in society generally, with economic, environmental, social, health and equity advantages.
Now the point about Twitter is that it is a social medium marked by many separate groups of associates and interests, engaging in many different simultaneous conversations under almost no discipline whatsoever other than very tight limits on message length. This can create discussions that on occasion move faster and more elegantly and more democratically than any other medium I know, often with impressive summaries on transport topics by many of the thinkers, campaigners and policy-makers I respect most in the world. It can also be a place of insults, threats, subversive and mischievous trouble-making, and lies. Anonymity is chosen by some, legitimately in a few cases, and false identity by others, drastically reducing credibility.
I started to find the discussion itself, and the way it was conducted, interesting from a research point of view, and this column is by way of notice that I have started to engage on a study not only of the core issue of LTNs themselves but also of the way in which Twitter has shifted the arguments, and the evidence used. People go succinctly on the record in a way that is very suitable for analysis of the discourses of transport policy, and I’ll report on this from time to time.
The trigger for this is a report of which I was, long ago, a co-author (Traffic Impacts of Highway Capacity Reductions, by Cairns, Hass-Klau and Goodwin, 1998). It was being referred to frequently in Twitter by both sides in the argument to support their approval or opposition to the LTN initiatives in local areas. This study was originally commissioned by London Transport and the (at that time combined) Departments of Transport and the Environment, to find out whether when road capacity was reduced, the total volume of traffic remained the same (with consequent increased congestion) or reduced.
I have started to engage on a study not only of the core issue of low traffic neighbourhoods themselves but also of the way in which Twitter has shifted the arguments, and the evidence used. [On Twitter] People go succinctly on the record in a way that is very suitable for analysis of the discourses of transport policy.
This issue is sharply relevant when considering whether a low traffic neighbourhood would result in an increase in traffic on neighbouring roads. Opponents claim that LTNs favour relatively well-off people in pleasant back-street neighbourhoods, and result in additional traffic nuisance suffered by poorer people who live next to main roads. (Incidentally, this claim is made sometimes by poorer people living on main roads, and sometimes by other people who simply do not want any restrictions on car use. It is important to accept that this observation does not invalidate the claim, though it does reduce the credibility of the claimant).
But if it is true, the question arises what to do about it? One solution is that there should be associated measures to reduce traffic nuisance on the main roads also, feasible since these are the areas where reallocation of capacity to bus and cycle lanes, and enforcement of restrictions on pavement parking, often have the greatest potential. The opposite solution offered is to reverse the direction of change, encouraging rat-runs (for example by satnav systems) rather than discouraging them, in order to reduce traffic congestion on main roads and enable cars to make greater use of the more favourable conditions in residential neighbourhoods.
Thus on both sides of the argument in relation to a specific scheme one can find joint cause by people whose motives may be quite different. Supporters and opponents of an LTN each include those who are in favour, or against, extension to nearby streets. There are therefore four policy positions, not two, and all may justify their position by arguments of equity and social justice.
Here three quite different issues interweave. One is the empirical question of what does in fact happen to the traffic, the second, also suitable for empirical analysis, is which groups of people and individuals are affected by that traffic, and the third is what to do about it.
Concerning the facts about traffic, one of the reasons why people can draw different conclusions is that the 1998 study had very many different results from different places. In nearly (but not quite) all cases there was some degree of reduction in the total volume of traffic observed: this was a crucial result and got most attention, because the standard traffic modelling practice at the time was to assume that the total volume of traffic was fixed and therefore any reduction in traffic on one part of the network had to be associated with an equal and opposite increase somewhere else. The reduction in traffic found was enough in many cases to enable the other advantages that pedestrianisation or bus priority could give. But its extent and location of the traffic reduction varied hugely, depending (as one would expect) on the scale and ambition and care of the intervention, associated measures implemented at the same time (or shortly before or after), pre-publicity, availability of alternatives, the existing levels of congestion on the treated and alternative roads, and the distinction between short and longer term effects that could differ not only in size, but in direction.
Thus the headline result was “the average reduction in traffic on treated roads was 41 per cent, of which less than half reappears as extra traffic on alternative roads or different times of the day”, with a median reduction, excluding exceptional cases, of more than 16 per cent). But these “exceptional” cases were extreme, and important. The biggest traffic reduction observed was 147 per cent (ie traffic went down both on the treated road and the alternative roads as well) in the case of a very large-scale pedestrianisation scheme in Nurnberg, and at the opposite extreme six towns where pedestrianised high streets were accompanied by new bypasses showed an overall increase in traffic in the whole area of nine per cent, because the bypasses induced more traffic than the modest pedestrianisation reduced.
Between these extremes there were cases of every amount of change. So it was indeed possible to find examples of many different outcomes.
Our conclusion at the time was that we should confidently reject the use of modelling based on the assumption that the total volume of traffic was fixed. But the amount of reduction depended on the situation and the supporting measures. Generally there were benefits to be gained – sometimes very large benefits – but you had to work for them.
Into this mix enters a collection of issues that have always been important, but have recently gained much more traction, namely considerations of social justice and equity. This takes the spotlight away from the ‘total net benefits’ of a scheme, and puts more focus on the question of who gets those benefits, and who bears the costs. Transport opportunities are distributed very unevenly among the population, and that unevenness is not csptured by a simple pattern of the average income in side streets and main roads. Differences can be more important at a more granular level, when considering sex, age, geographical location, housing tenure, occupation, family size, and access to different opportunities of places to go and transport to get there.
The total distributional effect of a transport project has to be considered by including both who pays and who gets the impacts, so that (for example) a road pricing scheme paid in proportion to mileage travelled or carbon used, etc, with the revenue spent on public transport improvements and public realm, would have a completely different distributional impact to one paid for in proportion to congestion and the revenue then used to build roads in the congested areas.
Recently I saw on Twitter, unattributed, “If all you’ve ever known is privilege, equality starts to look like oppression.” It’s elegant, but it’s also a research hypothesis, rather than an axiom, and a very useful one. So I’ll continue to engage in the arguments, but I’ll do so with a more conscious appreciation of how the arguments are constructed, and to what end.
Phil Goodwin is emeritus professor of transport policy at both the Centre for Transport and Society, University of the West of England, Bristol, and University College London. Email: email@example.com
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