Jamie Furlong

Low Traffic Neighbourhoods (LTNs) restrict through-traffic in residential areas. One concern is that LTNs may displace motor traffic onto nearby boundary roads, increasing journey times and congestion.,We explored this using Google Directions API data to assess how five LTNs in London affected boundary road journey times and heavy congestion. We found that journey times increased in the first year on the boundary roads of all five LTNs, with an average relative increase of 8.6% (95%CI 2.6% to 15.0%). Heavy congestion showed a similar trend, although the pooled increase was not statistically significant. Both effects reduced substantially from year 2 onwards, with average journey times and congestion typically returning to pre-LTN levels. We conclude that LTNs do not cause persistent boundary-road delays on average, although short-term disruption is likely. Policymakers should monitor outcomes over extended periods and consider targeted mitigation measures on the minority of boundary roads where long-term effects persist.

Background: Reducing private car use and increasing active travel is essential for transport decarbonisation and addressing public health crises of road traffic injuries, physical inactivity and air pollution. Low Traffic Neighbourhoods have emerged as a key intervention, particularly in London, United Kingdom, to create better environments for walking, wheeling and cycling by restricting through traffic on residential streets. While evidence suggests that Low Traffic Neighbourhoods reduce car use, increase walking and cycling, and improve road safety, their implementation has been politically contentious and has elicited a wide range of public reactions. Methods: This paper presents findings from the qualitative strand of a wider 3.5-year mixed-methods study of Low Traffic Neighbourhoods in London. Qualitative data were collected to explore the lived experiences of Low Traffic Neighbourhood residents, with a focus on how residents – including disabled residents – perceive and navigate the schemes. Participants were selected from among those living in or on the road adjacent to four selected Low Traffic Neighbourhoods, to ensure a diversity of views on the schemes, and diverse demographic characteristics were represented. Using 61 go-along interviews and 7 focus groups, we explore how Low Traffic Neighbourhoods influence residents’ experiences and perceptions of travel. Results: Our findings show that residents’ attitudes towards Low Traffic Neighbourhoods often shape their reported experiences: those who are initially supportive tend to notice and highlight positive impacts, while opponents are more likely to report no change or negative impacts. Overall, participants observed increased walking and cycling, improved perceptions of road safety, and reduced noise and air pollution within Low Traffic Neighbourhoods. However, concerns were raised by some disabled residents about longer journey times and accessibility problems. Notably, many residents living on boundary roads perceived an increase in traffic and pollution, although quantitative data on the impacts of Low Traffic Neighborhoods on boundary roads remain mixed. Conclusions: Our findings highlight the importance of considering residents’ lived experiences in scheme evaluations. While Low Traffic Neighbourhoods contribute to climate and health objectives, their implementation should be guided by a just transition framework to ensure benefits are equitably distributed. Limitations and future work: Our study’s main limitation is that it contributes to an evidence body of research on Low Traffic Neighbourhoods being predominantly from London. Future research should extend beyond London, explore a wider range of schemes and attend to experiences of further marginalised population groups. Funding: This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme as award number NIHR135020.

We tested the hypothesis that road safety improves at junctions between minor roads and major roads if the minor roads are modally filtered to remove through traffic. We did this by using police-reported casualty data (2012–2024) to examine the effects of 113 Low Traffic Neighbourhoods (LTNs) implemented in London between 2015 and 2024. Our findings supported our hypothesis: LTN implementation was associated with a 14% reduction in total numbers of casualties at junctions between newly filtered minor roads and surrounding major roads (95% CI: -21% to -8%). This effect was generally consistent across casualty injury severity, casualty travel mode, and the presence of traffic-light controlled signals.

Background Between 2015 and 2024, 113 Low Traffic Neighbourhoods (LTNs) were implemented across Greater London, with 27 subsequently removed. We investigated their impacts on road traffic injuries inside LTNs and on ‘boundary roads’ immediately surrounding the LTNs. Methods We matched police-recorded injuries from STATS19 data to Ordnance Survey road links that were spatially intersected with LTNs/boundary roads. Conditional fixed-effects Poisson regression models used the number of injuries per road link per quarter of each year (January 2012 to June 2024) to test whether LTN implementation was associated with changes in injury rates. Results LTN implementation was associated with a 35% (95% CI 29% to 40%; pConclusion LTNs in London reduced road traffic injuries among all road users inside the LTN areas, with no evidence of overall impact (and for cyclists and motorcyclists a benefit) on boundary roads.

An online survey polled a socio-demographically representative sample of approximately 2,000 UK residents concerning their attitudes to traffic restrictions that lead to longer car trips. Specifically, to what extent would respondents accept delays to everyday local car journeys if these were offset by reductions in NO₂, greenhouse gas emissions or vehicular traffic, or by increases in active travel? Responses suggested high levels of acceptance of delay but this varied by nature of impact (less openness to increased active travel) and socio-demographic attribute (gender, educational attainment, car ownership, ethnicity, housing tenure, prior presence of local traffic restrictions). In particular, there were lower levels of delay acceptance amongst men, respondents without degree-level qualifications, and those in households with two or more cars. These findings are relevant to those communicating about traffic restrictions, in terms of which audiences they target and how they present impacts.