London Transport Research Articles

Disparities in public transport accessibility in London from 2011 to 2021

Addressing urban inequalities has become a pressing concern on both the global sustainable development agenda and for local policy. Improving public transport services is seen as an important area where local governments can exert influence and potentially help reduce inequalities. Existing measures of accessibility used to inform decision-making for public transport infrastructure in London show spatial disparities, yet there is a gap in understanding how these disparities vary across demographic groups and how they evolve over time—whether they are improving or worsening. In this study, we investigate the distribution of public transport accessibility based on ethnicity and income deprivation in London over the past decade. We used data from the Census 2011 and 2021 for area-level ethnicity characteristics, English Indices of Deprivation for income deprivation in 2011 and 2019, and public transport accessibility metrics from Transport for London for 2010 and 2023, all at the small area level using lower super output areas (LSOAs) in Greater London. We found that, on average, public transport accessibility in London has increased over the past decade, with 78% of LSOAs experiencing improvements. Public transport accessibility in London showed an unequal distribution in cross-sectional analyses. Lower income neighbourhoods had poorer accessibility to public transportation in 2011 and 2023 after controlling for car-ownership and population density. These disparities were particularly pronounced for underground accessibility. Temporal analyses revealed that existing inequalities with respect to income deprivation and ethnicity are generally not improving. While wealthier groups benefited most from London Underground service improvements; lower income groups benefited more from bus service improvements. We also found that car ownership levels declined in areas with substantial increases to public transport accessibility and major housing developments, but not in those with moderate improvements.

“Open data means business”: Infrastructural and economic implications of opening up data in smart London

Around 2009–2010, opening up public data was a governmental strategy in the UK, as part of the implementation of the Transparency Agenda, based on the assumption that unfettered access to government data would inexorably lead to transparency, accountability and participation. Following this conjecture, and in an attempt to create an alternative to the corporate-driven smart city discourse, the Greater London Authority prioritised open data in its initial smart city plans to facilitate a ‘citizen-centred’ smart city. However, subsumed within the digital economy, open data was eventually promoted and implemented primarily for its lucrative potential to create new businesses, rather than prioritising the aspirations of transparency and participation. In this article, I explore the implications of this shift and the nature of open data- driven smart city making by focusing on a transport app, Citymapper that is built on open data released by Transport for London (TfL). By closely studying the app's product development process to generate profit together with its struggle to raise funding through venture capital and crowdfunding, I arrive at two main arguments. First, I argue that open data driven smart city making in London was a form of experimentation instead of a formal and rigid planning as it saw open data as an end in itself without much understanding of what this process would lead to in practice. As such, the case of Citymapper shows that the contingent process of opening up public transport data meant opening up public infrastructure in the city. Second, by examining the app's unsustainable business models and detailing its struggle to maintain revenue and profitability, I outline how open data-driven products are ultimately subsumed within the logic of platform capitalism rather than creating an alternative digital economy.

Assessing the Long-COVID Impact on Heritage Organisations

The aim of this paper is to understand the long-COVID impact on cultural heritage organisations, and future research needed. COVID-19 was disruptive to cultural heritage socioeconomic activities across the world during 2020 and 2021. Whilst government intervention and changes from physical to digital engagement generally prevailed, the long-COVID impact on cultural heritage organisations, their people and users, buildings, and collections remains unknown. The extent, also, to which financing, curating, visiting, and volunteering patterns have changed is uncertain. Following the pandemic closures and associated support, cultural heritage organisations are facing continuing economic, social, political, environmental, technological, and organisational culture pressures. This research examines the existing academic literature, sector publications, annual reports and associated visitor information to understand whether cultural heritage organisations have long-COVID, whether they can survive another pandemic, and what further research is needed to be better prepared. Four case studies from the UK look at the visitor and financial impacts of COVID-19 on the British Library, the London Transport Museum, The Theatre Royal Drury Lane, and Kensington Palace. This paper contributes to heritage research by providing a deeper understanding of the impact that COVID-19 had on heritage, and how to proactively plan for similar future disruptions. The impact themes show that change did not result in a new normal but in the need for a new space, consisting of blended space (physical and digital), mixed space (indoors and outdoors), and community of practice space (isolated or cross-sector networking space). The literature highlights the significance of the sector coming together during the pandemic to share knowledge and provide support through its networks. It also highlights how important it is for such unity not to be lost but to be harnessed to support ongoing organisational sustainability and better preparedness for future crises. Finally, future research suggestions are proposed grouped into social, digital, financial, and operational research themes.

Consuming Royalty

Consuming Royalty

Urban Green Systems for Improving Pedestrian Thermal Comfort and Walkability in Future Climate Scenarios in London

The purpose of this research is to investigate the thermal impact of urban green systems (UGS) (trees and living facades) and high albedo pavements on reducing the urban heat island (UHI) effect in London at the pedestrian street level. The research assesses the impact of UGS by suggesting practicable urban greenery-covering densities (25% and 50%) and using high albedo pavement in current and future climatic scenarios (2050 and 2080). This approach is intended to encourage pedestrians to walk longer distances for longer durations during the warmer months, following the Transport for London’s (TfL) 2017 Healthy Streets initiative. The research seeks to measure the advantages and assess the possible impact on the comfort and activities within urban streets. The study adopts a quantitative research design using ENVI-met modelling and questionnaires. Simulation results, the subject of this paper, confirmed that, across three climatic scenarios, the optimal UGS for thermal comfort is 50% trees followed by 25% trees, dependent on street orientation and solar access. Living facades (LF) with 25% and 50% covering had no discernible effect on the comfort of pedestrians, whereas high albedo pavement increases heat stress.

Method of comparative assessment of urban agglomeration transportation connectivity and ways to improve it in the context of sustainable development goals

Aim. To conduct a comparative assessment of the capacity of bridge and tunnel crossings across the Neva River in St. Petersburg and across the Thames in London, and to present proposals for improving transport connectivity in large cities on the basis of its results.Objectives. To determine the parameters of bridge and tunnel crossings (number, length, number of traffic lanes, traffic light regulation, speed limits, etc.); to calculate the capacity of bridge and tunnel crossings for public and private transport; to compare the results obtained; to present specific proposals and conclusions.Methods. The method of modeling channels and interaction constraints between blocks (subgraphs, clusters, regions, etc.) separated by some obstacle, in this case — a river, is used. The characteristics of such channels are compared, in this case — the capacity of bridges and tunnels. Throughput capacity for motor transport is calculated according to SP 396.1325800.2018 “Streets and roads of settlements. Rules of urban planning design”, for public transport — by multiplying the number of trips by the passenger capacity of vehicles. The cost of construction of pedestrian bridges is calculated according to the standards specified in the order of the Ministry of Construction of the Russian Federation № 113, with the application of an increasing coefficient.Results. Calculations have shown that the total capacity of bridges over the Neva River in St. Petersburg exceeds the same indicator for London. At the same time, the difference in population and status of the city suggests that the load on London’s transportation infrastructure should be higher. Three possible explanations for this finding are given, one of which is the availability of alternative infrastructure in London to provide transportation connectivity between the banks of the Thames, in particular pedestrian bridges. Four sites for the construction of such bridges in St. Petersburg are suggested. The calculations indicate that the socio-economic effect will allow to recoup the cost of creating the bridges within 50 years, if each bridge will have 17.5 thousand crossings per day. In addition, a new formulation of the definition of transportation connectivity is proposed.Conclusions. The existing bridge infrastructure of St. Petersburg exceeds the London bridge infrastructure in terms of capacity for passenger cars. At the same time, the London transport system serves a much larger agglomeration and therefore seems more efficient to the author of the article. The author sees the reasons for this as the spread of dedicated lanes for public transport in London, insufficient use of the potential of the streetcar in St. Petersburg and the spread of alternative ways of crossing the Thames in London. Of these alternatives, the construction of bicycle-pedestrian bridges seems to be the best for St. Petersburg. Eight additional conclusions, observations and recommendations regarding traffic management and public transport are presented.

Re-defining Transport for London’s strategic neighbourhoods from spatial and social perspectives

Neighbourhoods are fundamental spatial units to present social phenomena in urban studies. Many studies use administrative boundaries such as census tracts as representations of neighbourhoods, but such boundaries may poorly represent the underlying social structures and physical attributes which might help define more vernacular conceptions and dialectical evolution of these zones. In this paper, using the goal of creating a new set of ‘Strategic Neighbourhoods’ for Transport for London (TfL) as vehicle for analysis, we evaluate two contrasting spatially and socially focused methodologies of neighbourhood generation. In comparing the outputs of a tertiary-communities (T-Communities) method and a combined Principal Component Analysis (PCA) and Minimum Spanning Tree (MST) cluster analysis method with an earlier iteration of Strategic Neighbourhoods defined by TfL, indices including neighbourhood size, intra-class correlation coefficient (ICC), and the number of community centres are calculated to evaluate their relative performance which demonstrate that both methods create neighbourhood boundaries that can better capture intra-group social homogeneity and are more suitable for analysis than the original SNA boundaries. These results are discussed in the context of the dialectic relationship between neighbourhood outcomes, spatial structures, and social characteristics, leading to more widely relevant conclusions that neighbourhood boundary delineation should combine spatial structure, social attributes, and experimental knowledge to effectively sub-divide urban activity.

Multi-agent reinforcement learning for electric vehicle decarbonized routing and scheduling

Low-carbon transitions require joint efforts from electricity grid and transport network, where electric vehicles (EVs) play a key role. Particularly, EVs can reduce the carbon emissions of transport networks through eco-routing while providing the carbon intensity service for power networks via vehicle-to-grid technique. Distinguishing from previous research that focused on EV routing and scheduling problems separately, this paper studies their coordinated effect with the objective of carbon emission reduction on both sides. To solve this problem, we propose a multi-agent reinforcement learning method that does not rely on prior knowledge of the system and can adapt to various uncertainties and dynamics. The proposed method learns a hierarchical structure for the mutually exclusive discrete routing and continuous scheduling decisions via a hybrid policy. Extensive case studies based on a virtual 7-node 10-edge transport and 15-bus power network as well as a coupled real-world central London transport and 33-bus power network are developed to demonstrate the effectiveness of the proposed MARL method on reducing carbon emissions in transport network and providing carbon intensity service in power network.

Mind the Map: Redesigning the London Underground Map

ABSTRACT In May 2022, ahead of the 90th anniversary of Beck’s original London Underground map, Transport for London opened the new Elizabeth Line, and added it to the already-congested map. But is the map still fit for purpose? This paper references critiques of the recent iterations of the map, and undertakes a cartographic review that assesses its form and function. It includes new designs of the map, created by the author, that attempt to deal with the issues identified, as well as providing a wider critique. In exploring why cartographers and designers offer alternative, often unrequested, new designs of such classic maps, the paper will reflect upon the issue of whether holding on to an iconic map, with its flaws, is preferable to letting go of the past and designing a completely new map. Changing the map would be a brave move, but is one that this author, among others, feels is too pertinent an issue to continue to ignore.

How does the dominant stakeholder strategically manage an innovative public policy? Evidence from the London congestion charge

AbstractPrior studies have examined various economic, environmental, and social impacts of the London congestion charge (LCC). However, few studies have investigated how the Transport for London (TfL) managed the LCC in all stages of its policy. Without active, strategic management of policies, stakeholders affected may doubt the policies’ legitimacy and reduce policy effectiveness. Thus, examining the means utilized to achieve effective policy management is critical and can potentially influence the development and management of future policies. This study adapts Mitchell et al.’s stakeholder typology to study how the TfL, as part of the management of, and as the dominant stakeholder in, environmental regulations in London, strategically managed the LCC via their own efforts to exert power, establish legitimacy, and claim urgency. Relying on Yin, we analyze publicly available data to show how the TfL actively managed the LCC to ensure its sustainability as policy. The TfL primarily used tactics to maintain and enhance the LCC's legitimacy with authoritative power and fears of unproven urgency to influence other stakeholders. Results have practical implications for policymakers contemplating policy reforms and shed additional light on less‐discussed latent factors regarding policy management. This study contributes to the literature by applying stakeholder theory to the domain of policy reform, administration, and management. Our findings have policy implications as policymakers may benefit from learning the tactics examined in this study to assess their policy management and administration. Lastly, through our discussion and conclusions, we reflect on our findings to encourage research on policy management.

Development of Public Transportation and the Real Estate Market in London: Stylized Facts and Prospect

This paper aims to assess how further developments in London's public transport sector could affect the housing market and suggest potential improvements. It begins with a brief introduction to both public transport and the real estate sector in London, then discusses the potential benefit and negative effects that different ways of development can bring. The study will analyze the current state of public transport in London and its impact on the property market, as well as identify areas for improvement. Options for further development will be explored, with findings providing insights into how improving public transport infrastructure can lead to increased property values in the London residential market, as well as social welfare. Recommendations for potential improvements are expected to be made based on these findings.

Causal analysis at extreme quantiles with application to London traffic flow data

Abstract Transport engineers employ various interventions to enhance traffic-network performance. Quantifying the impacts of Cycle Superhighways is complicated due to the non-random assignment of such an intervention over the transport network. Treatment effects on asymmetric and heavy-tailed distributions are better reflected at extreme tails rather than at the median. We propose a novel method to estimate the treatment effect at extreme tails incorporating heavy-tailed features in the outcome distribution. The analysis of London transport data using the proposed method indicates that the extreme traffic flow increased substantially after Cycle Superhighways came into operation.

Fire incident data for England road tunnels

<p>This paper presents a study carried out to estimate the fire rate in England road tunnels. The result is a dataset of 28 road tunnels and 59 fire incidents. All tunnels studied in this project are continuously monitored by the National Highways, Transport for London, and Fire and Rescue Services. The work presents a hitherto unavailable dataset demonstrating the fire safety rate of these tunnels. The average fire rate was estimated by a safety analysis and the findings indicate that the average fire rate in England’s road tunnels is 1.481 per billion veh-km. There is an obvious difference between the number of fire incidents in England road tunnels and the number of fire incidents on England roads. It is also found that the fire rate in England’s road tunnels is less than in other European countries considered in this study.<strong></strong></p>

Passengers, citizens, customers: London transport transformed 1977–1987

This paper examines a transformation in the corporate control of London’s transport between 1977 and 1987. We offer a detailed case study explaining how a corporatist consensus broke down, what replaced it, and why. By 1977, London Transport was a centralised monopoly captured by its producer groups while passengers were treated as passive recipients. Two alternatives presented themselves: a utility maximising perspective, empowering passengers as citizens, or a cost-minimising perspective construing passengers as customers. After a period of conflict, central government intervened to disaggregate London Transport as an organisation while keeping its monopoly of provision intact. We assess this complicated transformation, arguing that there was a pivot from enterprise-level to product-level orientated logics visible in the day-to-day operations, interactions, and reporting systems. Using techniques later characterised as New Public Management, senior officials re-configured London Transport’s dynamic capabilities towards commercial imperatives, successfully transforming its business model.

Framework for constructing multimodal transport networks and routing using a graph database: A case study in London

AbstractMost prior multimodal transport networks have been organized as relational databases with multilayer structures to support transport management and routing; however, database expandability and update efficiency in new networks and timetables are low due to the strict database schemas. This study aimed to develop multimodal transport networks using a graph database that can accommodate efficient updates and extensions, high relation‐based query performance, and flexible integration in multimodal routing. As a case study, a database was constructed for London transport networks, and routing tests were performed under various conditions. The constructed multimodal graph database showed stable performance in processing iterative queries, and efficient multi‐stop routing was particularly enhanced. By applying the proposed framework, databases for multimodal routing can be readily constructed for other regions, while enabling responses to diversified routings, such as personalized routing through integration with various unstructured information, due to the flexible schema of the graph database.

Multimodal Public Transit Network Design Method Based on Hub-and-Spoke Infrastructure

This paper presents a two-phase method for generating a hub-and-spoke network for a multimodal public transit network (MPTN). The first phase addresses the problem of clustering in MPTNs, which is a key operation in solving the hub location problem (HLP) in MPTN design. However, previous work often oversimplifies or neglects the clustering phase, so this study presents a spatial clustering algorithm that can process real urban MPTNs without reducing their size or dividing them into zones. The algorithm is tested on four large city datasets and compared with popular spatial clustering algorithms. In the second phase, a heuristic algorithm is presented that aims to maximize network coverage. The proposed method is tested using the MPTN of Greater London and the resulting hub-and-spoke network is compared with the Journey API provided by Transport for London. The results show that the total travel time is improved by 16.9% with a strict hubbing policy. Transportation planners can adapt the proposed method to their specific needs by changing the size and number of clusters using the cluster scaling factor ([Formula: see text]) parameter and including or excluding any criteria in the decision equations.

Near Real-Time Social Distance Estimation In London

Abstract To mitigate the current COVID-19 pandemic, policy makers at the Greater London Authority, the regional governance body of London, UK, are reliant upon prompt, accurate and actionable estimations of lockdown and social distancing policy adherence. Transport for London, the local transportation department, reports they implemented over 700 interventions such as greater signage and expansion of pedestrian zoning at the height of the pandemic’s first wave with our platform providing key data for those decisions. Large well-defined heterogeneous compositions of pedestrian footfall and physical proximity are difficult to acquire, yet necessary to monitor city-wide activity (busyness) and consequently discern actionable policy decisions. To meet this challenge, we leverage our existing large-scale data processing urban air quality machine learning infrastructure to process over 900 camera feeds in near real-time to generate new estimates of social distancing adherence, group detection and camera stability. In this work, we describe our development and deployment of a computer vision and machine learning pipeline. It provides near immediate sampling and contextualization of activity and physical distancing on the streets of London via live traffic camera feeds. We introduce a platform for inspecting, calibrating and improving upon existing methods, describe the active deployment on real-time feeds and provide analysis over an 18 month period.

Performance and acceptability of the TfL Urban Bus Sound (AVAS)

Transport for London's quiet-running bus fleet is required to include an Acoustic Vehicle Alerting System (AVAS) compliant with UNECE Regulation 138 and as part of a wider series of safety measures as set out in their Bus Safety Standard towards the London Mayor's 'Vision Zero' objectives. As a public body, TfL must ensure that the Urban Bus Sound AVAS implementation is fit-for-purpose from a safety standpoint, is considerate of driver working conditions and is consistently implemented across a number of vehicle types, manufacturers and fleet operators. Additionally, as quiet-running vehicles increase across the London bus network, it must consider the impact on the urban soundscape. Over the course of two years, Phase 2 of the project addressed practical implementation and quality assurance challenges, bringing together soundscape and acoustic testing, on-street public and key stakeholder surveys, workshops with multiple vehicle manufacturers and operators as well as engagement with bus drivers. The project concludes by providing an optimised AVAS solution with specification and vehicle checks documentation to ensure successful roll-out. The project provides an important view on considerations for how AVAS can be implemented on public transport vehicle fleets, to consider and work with a wide range of public and stakeholder requirements.

The effect of an unconventional fare decrease on the demand for bus journeys: A regression discontinuity approach

We analyse the effect of a change in the fare structure for bus journeys in London on different demand measures using a regression discontinuity design. We utilise data obtained from Transport for London following the implementation of a new bus fare policy in September 2016, in which a follow-up journey made within the hour of an initial journey became free. Drawing on millions of individual paid and unpaid journeys between June and December 2016 – thus covering the period just before and after the introduction of the new fare – we estimate the effect of this price policy on the number of paid bus journeys, follow-up journeys and bus passenger numbers. We find that the policy significantly increased the number of bus trips by 5% and follow-up journeys by 8%. Passenger numbers increased by 4%. We also find that the increase in demand was not only driven by new customers, but also by more intensive demand by existing customers.

A transaction platform for microservices-based big data systems

Microservices architecture has increasingly been adopted for building distributed and scalable applications. The premise is that microservices are designed as smaller software components which are easier to be preserved and which enable separation between different components. This paper proposes a new transaction platform for microservices architecture to manage processing of big data stored in a cluster of NoSQL databases. New asynchronous protocols are designed to execute database operations as transactions, and to maintain their correctness and consistency. A prototype system has been developed that simulates London bus service across bus routes. It is evaluated through simulation experiments using big data from ‘Transport for London’ data service in order to analyse effects of transaction processing on response time and throughput in microservices architecture. The transaction platform reliably processes database operations, and enables data availability and consistency in failure-free and failure-prone environments.