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@article{aldred_barriers_2017,
author = {Aldred, Rachel and Watson, Tom and Lovelace, Robin and Woodcock, James},
date = {2017-11},
doi = {10.1016/j.tra.2017.11.003},
issn = {09658564},
journaltitle = {Transportation Research Part A: Policy and Practice},
abstract = {Background
Planners and politicians in many countries seek to increase the proportion of trips made by cycling. However, this is often challenging. In England, a national target to double cycling by 2025 is likely to be missed: between 2001 and 2011 the proportion of commutes made by cycling barely grew. One important contributory factor is continued low investment in cycling infrastructure, by comparison to European leaders.
Methods
This paper examines barriers to cycling investment, considering that these need to be better understood to understand failures to increase cycling level. It is based on qualitative data from an online survey of over 400 stakeholders, alongside seven in-depth interviews.
Results
Many respondents reported that change continues to be blocked by chronic barriers including a lack of funding and leadership. Participants provided insights into how challenges develop along the life of a scheme. In authorities with little consideration given to cycling provision, media and public opposition were not reported as a major issue. However, where planning and implementation have begun, this can change quickly; although examples were given of schemes successfully proceeding, despite this. The research points to a growing gap between authorities that have overcome key challenges, and those that have not.},
langid = {english},
shorttitle = {Barriers to Investing in Cycling},
title = {Barriers to Investing in Cycling: Stakeholder Views from England},
url = {http://linkinghub.elsevier.com/retrieve/pii/S096585641730410X},
urldate = {2018-03-15}
}
@article{beecham_framework_2022,
abstract = {Road safety research is a data-rich field with large social impacts. Like in medical research, the ambition is to build knowledge around risk factors that can save lives. Unlike medical research, road safety research generates empirical findings from messy observational datasets. Records of road crashes contain numerous intersecting categorical variables, dominating patterns that are complicated by confounding and, when conditioning on data to make inferences net of this, observed effects that are subject to uncertainty due to diminishing sample sizes. We demonstrate how visual data analysis approaches can inject rigor into exploratory analysis of such datasets. A framework is presented whereby graphics are used to expose, model and evaluate spatial patterns in observational data, as well as protect against false discovery. Evidence for the framework is presented through an applied data analysis of national crash patterns recorded in STATS19, the main source of road crash information in Great Britain. Our framework moves beyond typical depictions of exploratory data analysis and transfers to complex data analysis decision spaces characteristic of modern geographical analysis.},
author = {Beecham, Roger and Lovelace, Robin},
date = {2022},
doi = {10.1111/gean.12338},
file = {/home/robin/Zotero/storage/C8PK67D9/Beecham and Lovelace - 2022 - A Framework for Inserting Visually Supported Infer.pdf},
issn = {1538-4632},
journaltitle = {Geographical Analysis},
langid = {english},
number = {n/a},
shorttitle = {A Framework for Inserting Visually Supported Inferences into Geographical Analysis Workflow},
title = {A Framework for Inserting Visually Supported Inferences into Geographical Analysis Workflow: Application to Road Safety Research},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12338},
urldate = {2022-07-08},
volume = {n/a}
}
@article{biderman_innovation_2023,
author = {Biderman, Ciro and Mello, Patrícia Alencar Silva and Coordinators, Area and Acosta, Claudia and Giannotti, Mariana and Levy, Mariana and Ramos, Frederico Roman and Freiberg, German and Lovelace, Robin and Machado, Hannah},
date = {2023},
file = {/home/robin/Zotero/storage/3LYM9D5J/Biderman et al. - 2023 - Innovation Center in Urban Public Policies–FGV Cid.pdf},
title = {Innovation Center in Urban Public Policies–FGV Cidades},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
url = {https://documents1.worldbank.org/curated/en/099050223201017669/pdf/P1734140dc76b105509b6f074cc8fe0f3a1.pdf},
urldate = {2024-10-02}
}
@article{botta_packaging_2024,
abstract = {The effective and ethical use of data to inform decision-making offers huge value to the public sector, especially when delivered by transparent, reproducible, and robust data processing workflows. One way that governments are unlocking this value is through making their data publicly available, allowing more people and organisations to derive insights. However, open data is not enough in many cases: publicly available datasets need to be accessible in an analysis-ready form from popular data science tools, such as R and Python, for them to realise their full potential. This paper explores ways to maximise the impact of open data with reference to a case study of packaging code to facilitate reproducible analysis. We present the jtstats project, which consists of a main Python package, and a smaller R version, for importing, processing, and visualising large and complex datasets representing journey times, for many transport modes and trip purposes at multiple geographic levels, released by the UK Department for Transport (DfT). jtstats shows how domain specific packages can enable reproducible research within the public sector and beyond, saving duplicated effort and reducing the risks of errors from repeated analyses. We hope that the jtstats project inspires others, particularly those in the public sector, to add value to their data sets by making them more accessible.},
annotation = {0 citations (Crossref) [2024-07-25]},
author = {Botta, Federico and Lovelace, Robin and Gilbert, Laura and Turrell, Arthur},
date = {2024-07-24},
doi = {10.1177/23998083241267331},
issn = {2399-8083},
journaltitle = {Environment and Planning B: Urban Analytics and City Science},
langid = {english},
pages = {23998083241267331},
publisher = {SAGE Publications Ltd STM},
shorttitle = {Packaging Code and Data for Reproducible Research},
title = {Packaging Code and Data for Reproducible Research: A Case Study of Journey Time Statistics},
url = {https://doi.org/10.1177/23998083241267331},
urldate = {2024-07-25}
}
@article{deakin_route_network_2025,
author = {Deakin, Will and Wang, Zhao and Parry, Josiah and Lovelace, Robin},
date = {2025-10},
doi = {10.1177/23998083251387986},
issn = {2399-8083},
journaltitle = {Environment and Planning B: Urban Analytics and City Science},
abstract = {Route network datasets are fundamental to transport models, serving as both inputs for analysis and outputs for visualization and decision-making. The increasing complexity of route network data from sources like OpenStreetMap allows for more detailed modelling of sustainable transport modes such as walking and cycling. However, this level of detail can introduce challenges for the clear visualization and interpretation of model results. A common problem is the representation of single transport corridors by multiple parallel lines, which can create visual clutter and obscure important patterns in transport flows. The purpose of the work presented in this paper is to provide a basis for computationally efficient analysis and visualization of route networks for strategic transport planning, where intricate geometries, such as parallel or ‘braided’ linestrings, are unhelpful. We present and evaluate two distinct methods for simplifying complex route networks that are intended to be used as a ‘pre-processing’ step to speed up and improve the results of strategic transport network analysis, modelling, and visualization workflows. First, we present skeletonization, an approach that uses ‘thinning’ of rasterized network data to extract a simplified representation of the network. Second, we present a Voronoi-based approach using Voronoi diagrams to identify centrelines. We demonstrate the practical application of these methods using the ‘Simplified network’ layer in the Transport for Scotland-funded Network Planning Tool, a publicly accessible resource at https://www.npt.scot. To support reproducible research, we implement the methods in the open-source parenx Python package, enabling their use alongside other open source tools for transport planning, research, and educational applications.},
langid = {english},
pages = {23998083251387986},
title = {Route network simplification for transport planning},
url = {https://doi.org/10.1177/23998083251387986}
}
@book{dorman_geocomputation_2025,
abstract = {Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.Key features: Showcases the integration of vector and raster datasets operations. Provides explanation of each line of code in the book to minimize surprises. Includes example datasets and meaningful operations to illustrate the applied nature of geographic research. Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.},
author = {Dorman, Michael and Graser, Anita and Nowosad, Jakub and Lovelace, Robin},
date = {2025-02-14},
eprint = {Gl03EQAAQBAJ},
eprinttype = {googlebooks},
isbn = {978-1-04-030160-9},
keywords = {Computers / Mathematical & Statistical Software,Mathematics / Probability & Statistics / General,Psychology / Research & Methodology,Science / Earth Sciences / Geology,Science / Life Sciences / Biological Diversity,Science / Life Sciences / Botany,Social Science / Human Geography},
langid = {english},
pagetotal = {309},
publisher = {CRC Press},
title = {Geocomputation with Python},
url = {https://py.geocompx.org/}
}
@article{er_modelling_traffic_2025,
author = {Er, Sebnem and Briz-Redón, Álvaro and Salau, Sulaiman and Lovelace, Robin},
date = {2025-07},
doi = {10.1007/s12061-025-09703-0},
issn = {1874-4621},
journaltitle = {Applied Spatial Analysis and Policy},
abstract = {This paper models road traffic collision counts recorded between 2015 and 2019 in a ward located in the central part of Cape Town in South Africa, using a Bayesian spatio-temporal zero-inflated Negative Binomial approach. The method accounted for the excess zeros present in collision data by separately modeling zero and non-zero collision counts, while also capturing spatial and temporal dependencies through prior distributions. Road-level information was used as fixed-effects covariates, including speed limits, presence of traffic calming measures, traffic signals, road class, number of lanes, whether the intersection is on “Main Road”, and whether a public transport route passes through the intersection. The results reveal that among the covariates included in the selected model, node degree (used as a proxy for traffic flow), the presence of traffic signals, having any major road around the intersection (road class), location along “Main Road”, and the presence of a taxi route at the intersection were all associated with an increase in traffic collision counts at the intersections. The years 2018 and 2019 were associated with higher collision counts compared to the reference year, 2015. For the probability component of the model, the existence of traffic signals at the intersection and location along “Main Road”were both associated with an increase in the chances of at least one collision being observed at the intersection, whereas having any high-speed road around the intersection decreased this chance.},
langid = {english},
pages = {93},
title = {Modelling of Traffic Collisions at Road Intersections in Cape Town, South Africa: A Bayesian Spatio-Temporal Approach},
url = {https://doi.org/10.1007/s12061-025-09703-0},
volume = {18}
}
@misc{farrell_road_user_video_2024,
author = {Farrell, Graham and Lovelace, Robin and O'Hern, Steve},
date = {2024-07},
doi = {10.31235/osf.io/cgjmr},
langid = {english},
title = {Road User Video Evidence of Road Traffic Offences: Preliminary Analysis of Operation Snap Data and Suggestions for a Research Agenda},
abstract = {This study uses data from Operation Snap (OpSnap), the UK police’s national system to receive road users’ video evidence of road traffic offences. Data from one police force area for 39 months (January 2021 to March 2024) (N = 20,364 records) is analysed. Half were submitted by vehicle drivers (49.8\%), a third by cyclists (34.7\%), 7.2\% by pedestrians, 2.2\% by horse riders, 0.2\% by motorcyclists, and 5.8\% were unknown. We estimate that, relative to road distance travelled, cyclists were 20 times more likely to submit video evidence than vehicle drivers. The most common offences overall were driving ‘without reasonable consideration to others’ or ‘without due care and attention’. Half (53.5\%) of reported cases resulted in the recommended disposal of an educational course, \% no further action 12.6\% conditional offer, and 1.6\% resulted in court appearance. A research agenda using OpSnap data is outlined that could emerge if national datasets are compiled and responsibly opened-up and made available for research and policy-making: data-driven research should identify hotspot locations and other correlates of dangerous and antisocial road use at regional, and local levels; research projects should investigate disposal-related decision-making, video quality, and the role of supporting evidence; offence concentration (recidivism, repeat submitters of evidence, spatial hotspots) and case progression including court cases should be explored with reference to new video evidence. We conclude that datasets derived from publicly-uploaded video submission portals have the potential to transform evidence-based policy and practice locally, nationally and internationally.},
url = {https://osf.io/cgjmr}
}
@article{felix_reproducible_2025,
abstract = {A high proportion of car trips can be replaced by a combination of public transit and cycling for the first-and-last mile. This paper estimates the potential for cycling combined with public transit as a substitute for car trips in the Lisbon metropolitan area and assesses its socio-environmental impacts using open data and open source tools. A decision support tool that facilitates the design and development of a metropolitan cycling network was developed (biclaR). The social and environmental impacts were assessed using Health World Organization tools. The impacts of shifting car trips to public transport were also estimated and monetized. The results show that 10~% of all trips could be made by cycling in combination with public transport. Shifting to cycling for the shorter first and last mile stages can reduce annual CO2eq emissions from 3000 to 7500 tons/day, while for the public transport leg, the transfer from car avoids of up to 20,500 tons of CO2eq emissions per year. The estimated socio-environmental benefits are of €125 million to €325 million over 10~years. This evidence can support policymakers to prioritize interventions that reduce the reliance on private motor vehicles.},
annotation = {0 citations (Crossref) [2024-12-13]},
author = {Félix, Rosa and Moura, Filipe and Lovelace, Robin},
date = {2025-04-01},
doi = {10.1016/j.compenvurbsys.2024.102230},
file = {/home/robin/Zotero/storage/H8SRRRPU/S0198971524001595.html},
issn = {0198-9715},
journaltitle = {Computers, Environment and Urban Systems},
keywords = {Active transport,Environmental impacts,First and last mile,Health economic assessment,Intermodality,Open data and methods},
pages = {102230},
shortjournal = {Computers, Environment and Urban Systems},
shorttitle = {Reproducible Methods for Modeling Combined Public Transport and Cycling Trips and Associated Benefits},
title = {Reproducible Methods for Modeling Combined Public Transport and Cycling Trips and Associated Benefits: Evidence from the biclaR Tool},
url = {https://www.sciencedirect.com/science/article/pii/S0198971524001595},
urldate = {2024-12-12},
volume = {117}
}
@article{gilardi_multivariate_2022a,
abstract = {Road traffic casualties represent a hidden global epidemic, demanding evidence-based interventions. This paper demonstrates a network lattice approach for identifying road segments of particular concern, based on a case study of a major city (Leeds, UK), in which 5862 crashes of different severities were recorded over an 8-year period (2011–2018). We consider a family of Bayesian hierarchical models that include spatially structured and unstructured random effects to capture the dependencies between the severity levels. Results highlight roads that are more prone to collisions, relative to estimated traffic volumes, in the north-west and south of city centre. We analyse the modifiable areal unit problem (MAUP), proposing a novel procedure to investigate the presence of MAUP on a network lattice. We conclude that our methods enable a reliable estimation of road safety levels to help identify ‘hotspots’ on the road network and to inform effective local interventions.},
author = {Gilardi, Andrea and Mateu, Jorge and Borgoni, Riccardo and Lovelace, Robin},
date = {2022},
doi = {10.1111/rssa.12823},
eprint = {2011.12595},
eprinttype = {arXiv},
file = {/home/robin/Zotero/storage/7Y9BMNPM/Gilardi et al. - 2022 - Multivariate hierarchical analysis of car crashes .pdf;/home/robin/Zotero/storage/97ZREXWP/Gilardi et al. - 2021 - Multivariate hierarchical analysis of car crashes .pdf;/home/robin/Zotero/storage/RP27Q9R9/Gilardi et al. - Multivariate hierarchical analysis of car crashes .pdf;/home/robin/Zotero/storage/M4Q6ZG7V/2011.html;/home/robin/Zotero/storage/Y9QHXG4N/rssa.html},
ids = {gilardi_multivariate_2021},
issn = {1467-985X},
journaltitle = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
keywords = {Bayesian hierarchical models,car crashes data,MAUP,multivariate modelling,network lattice,spatial networks,Statistics - Applications},
langid = {english},
number = {3},
pages = {1150--1177},
title = {Multivariate Hierarchical Analysis of Car Crashes Data Considering a Spatial Network Lattice},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/rssa.12823},
urldate = {2022-11-24},
volume = {185}
}
@article{gilardi_street_2020,
abstract = {The idea of this project is to compare stplanr and dodgr approaches to street networks in R. This is a draft for the paper. Hosted on the Open Science Framework},
annotation = {ZSCC: NoCitationData[s0]},
author = {Gilardi, Andrea and Lovelace, Robin},
date = {2020-05-29},
doi = {10.17605/OSF.IO/WTQAS},
file = {/home/robin/Zotero/storage/WJDZTWSA/wtqas.html},
keywords = {R},
langid = {english},
publisher = {OSF},
title = {Street Networks in R},
url = {https://osf.io/wtqas/},
urldate = {2020-06-26}
}
@book{gillespie_efficient_2016,
author = {Gillespie, Colin and Lovelace, Robin},
date = {2016},
isbn = {978-1-4919-5078-4},
publisher = {O'Reilly Media},
title = {Efficient R Programming: A Practical Guide to Smarter Programming},
abstract = {Learn the fundamentals for R programming and gain the tools needed for doing data science.},
url = {https://csgillespie.github.io/efficientR/}
}
@article{goodman_assessing_2019,
abstract = {Background Cycling to school has large potential health benefits, ensuring children get regular daily exercise. This paper demonstrates and implements a method for estimating the potential for modal switch to cycling for the school commute down to the route network level across England. Methods Input data from the 2011 School Census, provided by the English Department for Education, comprised two main tables: a school-level dataset representing 21,523 educational institutions and an origin-destination (OD) level dataset, containing around 50 desire lines per school. The method focused on the 1.37 million secondary school children (age 11-18) travelling less than 15km to school. For each of the 134,274 OD pairs we route distance and hilliness were estimated using the CycleStreets.net routing service. Current and potential levels of cycling were modeled as a function of distance and hilliness. This included using Dutch National Travel Survey to create a 'Go Dutch' scenario English children cycled as much as children in the Netherlands, accounting for route distance and hilliness. Results Among those travelling less than 15km, the current percentage of children cycling to school in England is 2.7%. Our model of cycling potential highlights areas and routes with particularly high cycling potential, to help prioritize investment in safe routes to school. The scenarios show the scale of transformation possible in school travel patterns: 'Going Dutch' would see over two-thirds of these children cycle to school, approaching the level observed in The Netherlands, higher than the 27% cycle mode share in an equivalent 'Go Dutch' scenario for cycling to work, implying that the potential uptake of cycling for travel to school could be even higher, as a percentage of trips, than the potential for cycling to work. Conclusions This paper highlights the very high potential of school trips to be cycled and suggest it should be a priority target for health-conscious transport policy. To our knowledge, this is the first time that a national database on school travel at the level has been analysed from a 'safe routes to school' perspective at high geographical resolution, down to the route network level. The methods could be deployed in other settings where travel to school data is available at the OD level to inform investments in safe routes to school, where they are most needed.},
author = {Goodman, Anna and Fridman-Rojas, Ilan and Aldred, Rachel and Woodcock, James and Lovelace, Robin},
date = {2019},
doi = {10.1016/j.jth.2017.05.221},
file = {/home/robin/Zotero/storage/8IF4UG9W/Fridman-Rojas et al. - 2017 - 1989 - Assessing the Potential for Uptake of Cycli.pdf;/home/robin/Zotero/storage/RR564R6Q/S2214140517303808.html},
issn = {2214-1405},
journaltitle = {Journal of Transport & Health},
keywords = {Cycling},
pages = {S73},
shortjournal = {Journal of Transport & Health},
shorttitle = {1989 - Assessing the Potential for Uptake of Cycling to School},
title = {Assessing the Potential for Uptake of Cycling to School: A Case Study of England},
url = {http://www.sciencedirect.com/science/article/pii/S2214140517303808},
urldate = {2018-08-15},
volume = {5}
}
@article{goodman_scenarios_2019,
abstract = {Background The Propensity to Cycle Tool (PCT) is a freely available, interactive tool help prioritise cycling initially launched in England in 2017 and based on adult commuting data. This paper applies the method to travel to school data, and assesses health and carbon benefits based on nationwide scenarios of cycling uptake. Methods The 2011 National School Census provides origin-destination data for all state-funded schools in England (N = 7,442,532 children aged 2–18 in 21,443 schools). Using this dataset, we modelled propensity to cycle as a function of route distance and hilliness between home and school. We generated scenarios, including ‘Go Dutch’ – in which English children were as likely to cycle as Dutch children, accounting for trip distance and hilliness. We estimated changes in the level of cycling, walking, and driving, and associated impacts on physical activity and carbon emissions. Results In 2011, 1.8% of children cycled to school (1.0% in primary school, 2.7% in secondary school). If Dutch levels of cycling were reached, under the Go Dutch scenario, this would rise to 41.0%, a 22-fold increase. This is larger than the 6-fold increase in Go Dutch for adult commuting. This would increase total physical activity among pupils by 57%, and reduce transport-related carbon emissions by 81 kilotonnes/year. These impacts would be substantially larger in secondary schools than primary schools (a 96% vs. 9% increase in physical activity, respectively). Conclusion Cycling to school is uncommon in England compared with other Northern European countries. Trip distances and hilliness alone cannot explain the difference, suggesting substantial unmet potential. We show that policies resulting in substantial uptake of cycling to school would have important health and environmental benefits. At the level of road networks, the results can inform local investment in safe routes to school to help realise these potential benefits.},
author = {Goodman, Anna and Rojas, Ilan Fridman and Woodcock, James and Aldred, Rachel and Berkoff, Nikolai and Morgan, Malcolm and Abbas, Ali and Lovelace, Robin},
date = {2019-03-01},
doi = {10.1016/j.jth.2019.01.008},
file = {/home/robin/Zotero/storage/JR56F4C4/Goodman et al. - 2019 - Scenarios of cycling to school in England, and ass.pdf;/home/robin/Zotero/storage/EQ8SHGTZ/S2214140518301257.html},
issn = {2214-1405},
journaltitle = {Journal of Transport & Health},
keywords = {Active travel,Carbon emissions,Cycling,Modelling,Physical activity,School},
pages = {263--278},
shortjournal = {Journal of Transport & Health},
shorttitle = {Scenarios of Cycling to School in England, and Associated Health and Carbon Impacts},
title = {Scenarios of Cycling to School in England, and Associated Health and Carbon Impacts: Application of the ‘Propensity to Cycle Tool’},
url = {http://www.sciencedirect.com/science/article/pii/S2214140518301257},
urldate = {2019-03-04},
volume = {12}
}
@article{ito_where_2023,
abstract = {A lack of cycle parking is a known barrier to promoting the uptake of cycling in urban areas. Unlike cars that can be parked on the roadside with little additional infrastructure, bikes usually require dedicated parking facilities. The existing research and guidance on where cycle parking should be provided primarily focuses on key destinations such as train stations or schools. Thus, there is a gap in knowledge about the amount of general-purpose cycle parking required and how it should be distributed across a city. This paper presents a novel method for analysing and prioritising the spatial distribution of cycle parking. The method draws on established portfolio management techniques but applies them in a spatial context. Using the case study of London, we demonstrate that it is possible to identify areas that have a deficit of cycle parking as well as locations that have the most significant potential for increasing cycling uptake by providing additional cycle parking.},
annotation = {0 citations (Crossref) [2023-12-31]},
author = {Ito, Yuhei and Morgan, Malcolm and Lovelace, Robin},
date = {2023-07-01},
doi = {10.1177/23998083221138575},
file = {/home/robin/Zotero/storage/5CL47NPH/Ito et al. - 2022 - Where to invest in cycle parking A portfolio mana.pdf;/home/robin/Zotero/storage/UQDU2BR3/Ito et al. - 2023 - Where to invest in cycle parking A portfolio mana.pdf},
issn = {2399-8083},
journaltitle = {Environment and Planning B: Urban Analytics and City Science},
langid = {english},
number = {6},
pages = {1438--1454},
publisher = {SAGE Publications Ltd STM},
shorttitle = {Where to Invest in Cycle Parking},
title = {Where to Invest in Cycle Parking: A Portfolio Management Approach to Spatial Transport Planning},
url = {https://doi.org/10.1177/23998083221138575},
urldate = {2023-12-31},
volume = {50}
}
@article{kotov_spanishoddata_2026,
author = {Kotov, Egor and Vidal-Tortosa, Eugeni and Cantú-Ros, Oliva G. and Burrieza-Galán, Javier and Herranz, Ricardo and Gullón Muñoz-Repiso, Tania and Lovelace, Robin},
date = {2026-01},
doi = {10.1177/23998083251415040},
issn = {2399-8083},
journaltitle = {Environment and Planning B: Urban Analytics and City Science},
abstract = {We present spanishoddata, an R package that enables fast and efficient access to Spain’s open, high-resolution origin-destination human mobility datasets, derived from anonymised mobile-phone records and released by the Ministry of Transport and Sustainable Mobility. The package directly addresses challenges of data accessibility, reproducibility, and efficient processing identified in prior studies. spanishoddata automates retrieval from the official source, performs file and schema validation, and converts the data to efficient, analysis-ready formats (DuckDB and Parquet) that enable multi-month and multi-year analysis on consumer-grade hardware. The interface handles complexities associated with these datasets, enabling a wide range of people – from data science beginners to experienced practitioners with domain expertise – to start using the data with just a few lines of code. We demonstrate the utility of the package with example applications in urban transport planning, such as assessing cycling potential or understanding mobility patterns by activity type. By simplifying data access and promoting reproducible workflows, spanishoddata lowers the barrier to entry for researchers, policymakers, transport planners or anyone seeking to leverage mobility datasets.},
langid = {english},
pages = {23998083251415040},
title = {spanishoddata: A package for accessing and working with Spanish Open Mobility Big Data},
url = {https://doi.org/10.1177/23998083251415040}
}
@article{lovelace_assessing_2011,
author = {Lovelace, Robin and Beck, S.B.M. B M and Watson, M. and Wild, A.},
date = {2011-02},
doi = {10.1016/j.enpol.2011.01.051},
file = {/home/robin/Zotero/storage/L2I4EZTU/1-s2.0-S0301421511000620-main.pdf},
issn = {03014215},
journaltitle = {Energy Policy},
abstract = {Origin-destination (OD) datasets are widely available but transport interventions require network level data. OD-‘desire line’-route-‘route network’ conversion techniques are typically based on lines between zone centroids. This approach fails to show the diffuse nature of travel patterns. This paper presents ‘jittering’ methods to overcome these limitations and seeks to assess them. We find that jittered OD datasets result in a closer fit between observed and estimated flow in a reproducible case study using open data in Edinburgh. We conclude that jittering can add value to OD but work is needed to parameteterise them in the context of route network generation techniques},
keywords = {Modal shift,Replacement ratio},
number = {4},
pages = {2075--2087},
title = {Assessing the Energy Implications of Replacing Car Trips with Bicycle Trips in Sheffield, UK},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0301421511000620},
volume = {39}
}
@unpublished{lovelace_assessing_2022,
abstract = {Origin-destination (OD) datasets are widely available but transport interventions require network level data. OD-‘desire line’-route-‘route network’ conversion techniques are typically based on lines between zone centroids. This approach fails to show the diffuse nature of travel patterns. This paper presents ‘jittering’ methods to overcome these limitations and seeks to assess them. We find that jittered OD datasets result in a closer fit between observed and estimated flow in a reproducible case study using open data in Edinburgh. We conclude that jittering can add value to OD but work is needed to parameteterise them in the context of route network generation techniques},
author = {Lovelace, Robin and Félix, Rosa and Carlin, Dustin and Beecham, Roger},
date = {2022-03-29},
doi = {10.5281/zenodo.6410196},
eventtitle = {30th Annual Geographical Information Science Research UK (GISRUK)},
file = {/home/robin/Zotero/storage/83XYIBJK/Lovelace et al. - 2022 - Assessing methods for generating route networks fr.pdf},
publisher = {Zenodo},
shorttitle = {Assessing Methods for Generating Route Networks from Origin-Destionation Data},
title = {Assessing Methods for Generating Route Networks from Origin-Destionation Data: Jittering, Routing, and Visualisation},
url = {https://zenodo.org/record/6410196},
urldate = {2022-06-27},
venue = {Liverpool, United Kingdom}
}
@article{lovelace_big_2016,
abstract = {There has been much excitement among quantitative geographers about newly available data sets, characterized by high volume, velocity, and variety. This phenomenon is often labeled as “Big Data” and has contributed to methodological and empirical advances, particularly in the areas of visualization and analysis of social networks. However, a fourth v—veracity (or lack thereof)—has been conspicuously lacking from the literature. This article sets out to test the potential for verifying large data sets. It does this by cross-comparing three unrelated estimates of retail flows—human movements from home locations to shopping centers—derived from the following geo-coded sources: (1) a major mobile telephone service provider; (2) a commercial consumer survey; and (3) geotagged Twitter messages. Three spatial interaction models also provided estimates of flow: constrained and unconstrained versions of the “gravity model” and the recently developed “radiation model.” We found positive relationships between all data-based and theoretical sources of estimated retail flows. Based on the analysis, the mobile telephone data fitted the modeled flows and consumer survey data closely, while flows obtained directly from the Twitter data diverged from other sources. The research highlights the importance of verification in flow data derived from new sources and demonstrates methods for achieving this.},
author = {Lovelace, Robin and Birkin, Mark and Cross, Philip and Clarke, Martin},
date = {2016-01-01},
doi = {10.1111/gean.12081},
file = {/home/robin/Zotero/storage/BWWWRJFA/Lovelace et al. - 2016 - From Big Noise to Big Data Toward the Verificatio.pdf;/home/robin/Zotero/storage/VWRM3P8H/abstract.html},
issn = {1538-4632},
journaltitle = {Geographical Analysis},
keywords = {geographical analysis},
langid = {english},
number = {1},
pages = {59--81},
shortjournal = {Geogr Anal},
shorttitle = {From Big Noise to Big Data},
title = {From Big Noise to Big Data: Toward the Verification of Large Data Sets for Understanding Regional Retail Flows},
url = {http://onlinelibrary.wiley.com/doi/10.1111/gean.12081/abstract},
urldate = {2016-03-15},
volume = {48}
}
@article{lovelace_bike_2011,
author = {Lovelace, Robin},
date = {2011-09},
entrysubtype = {magazine},
journaltitle = {Now Then},
abstract = {Zones are the building blocks of urban analysis. Fields ranging from demographics to transport planning routinely use zones { extemdash} spatially contiguous areal units that break-up continuous space into discrete chunks { extemdash} as the foundation for diverse analysis techniques. Key methods such as origin-destination analysis and choropleth mapping rely on zones with appropriate sizes, shapes and coverage. However, existing zoning systems are sub-optimal in many urban analysis contexts, for three main reasons: 1) available administrative zoning systems are often based on somewhat arbitrary factors; 2) evidence-based zoning systems are often highly variable in size and shape, reducing their utility for inter-city comparison; and 3) official zoning systems are non-existent, not publicly available, or are too coarse, hindering urban analysis in many places, especially in low income nations. To tackle these three key issues we developed a flexible, open and scalable solution: the ClockBoard zoning system. ClockBoard consists of 12 segments divided by concentric rings of increasing distance, creating a consistent visual frame of reference for cities that is reminiscent of a clock and a dartboard. This paper outlines the design, potential uses and merits of the ClockBoard zoning system and discusses future avenues for research and development of new zoning systems based on the experience.},
pages = {20--22},
title = {Bike Trailers},
url = {http://nowthenmagazine.com/issue-42/bike-trailers/}
}
@article{lovelace_carbon_2012,
author = {Lovelace, Robin and Temple, Luke},
date = {2012},
issue = {September 2012},
journaltitle = {Metis},
abstract = {This paper presents a new density-based clustering algorithm, ST-DBSCAN, which is based on DBSCAN. We propose three marginal extensions to DBSCAN related with the identification of (i) core objects, (ii) noise objects, and (iii) adjacent clusters. In contrast to the existing density-based clustering algorithms, our algorithm has the ability of discovering clusters according to non-spatial, spatial and temporal values of the objects. In this paper, we also present a spatial–temporal data warehouse system designed for storing and clustering a wide range of spatial–temporal data. We show an implementation of our algorithm by using this data warehouse and present the data mining results.},
pages = {20--26},
title = {Carbon Capture and Storage: Bury the Myth and Focus on Alternatives},
url = {http://www.ippr.org/publication/55/9674/metis-volume-3},
volume = {3}
}
@article{lovelace_clockboard_2022,
abstract = {Zones are the building blocks of urban analysis. Fields ranging from demographics to transport planning routinely use zones - spatially contiguous areal units that break-up continuous space into discrete chunks - as the foundation for diverse analysis techniques. Key methods such as origin-destination analysis and choropleth mapping rely on zones with appropriate sizes, shapes and coverage. However, existing zoning systems are sub-optimal in many urban analysis contexts, for three main reasons: 1) administrative zoning systems are often based on somewhat arbitrary factors; 2) zoning systems that are evidence-based (e.g., based on equal population size) are often highly variable in size and shape, reducing their utility for inter-city comparison; and 3) official zoning systems in many places simply do not exist or are unavailable. We set out to develop a flexible, open and scalable solution to these problems. The result is the zonebuilder project (with R, Rust and Python implementations), which was used to create the ClockBoard zoning system. ClockBoard consists of 12 segments emanating from a central place and divided by concentric rings with radii that increase in line with the triangular number sequence (1, 3, 6 km etc). 'ClockBoards' thus create a consistent visual frame of reference for monocentric cities that is reminiscent of clocks and a dartboard. This paper outlines the design and potential uses of the ClockBoard zoning system in the historical context, and discusses future avenues for research into the design and assessment of zoning systems.},
author = {Lovelace, Robin and Tennekes, Martijn and Carlino, Dustin},
date = {2022-06-20},
doi = {10.5311/JOSIS.2022.24.172},
file = {/home/robin/Zotero/storage/QRQDMJSH/Lovelace et al. - 2022 - ClockBoard A zoning system for urban analysis.pdf},
issn = {1948-660X},
issue = {24},
journaltitle = {Journal of Spatial Information Science},
keywords = {modifiable area unit problem},
langid = {english},
number = {24},
pages = {63--85},
shorttitle = {ClockBoard},
title = {ClockBoard: A Zoning System for Urban Analysis},
url = {https://josis.org/index.php/josis/article/view/172},
urldate = {2022-07-02}
}
@inproceedings{lovelace_crowd_2015,
author = {Lovelace, Robin},
booktitle = {GIS Research UK(GISRUK). Leeds. http://leeds. Gisruk. Org/Abstracts/GISRUK2015_submission_71. Pdf},
abstract = {The Propensity to Cycle Tool (PCT) has revolutionised strategic cycle planning in England and Wales. This evidence-based tool quantifies cycling potential at national, city and street scales, leading to the creation of joined-up networks available to millions of people. The PCT has been used by {$>$}35,000 transport planners, consultants, advocates and members of the public, directly influencing the design and construction of cost-effective cycle networks worth {$>$}GBP500,000,000. The tool informed the majority of UK local authority applications to the GBP250,000,000 government COVID-19 Emergency Active Travel Fund. Planners across Europe, USA, Australia and New Zealand have adopted the approach internationally.},
date = {2015},
title = {Crowd Sourced vs Centralised Data for Transport Planning: A Case Study of Bicycle Path Data in the UK}
}
@report{lovelace_cycle_2023,
abstract = {The Propensity to Cycle Tool (PCT) has revolutionised strategic cycle planning in England and Wales. This evidence-based tool quantifies cycling potential at national, city and street scales, leading to the creation of joined-up networks available to millions of people. The PCT has been used by $>$35,000 transport planners, consultants, advocates and members of the public, directly influencing the design and construction of cost-effective cycle networks worth $>$GBP500,000,000. The tool informed the majority of UK local authority applications to the GBP250,000,000 government COVID-19 Emergency Active Travel Fund. Planners across Europe, USA, Australia and New Zealand have adopted the approach internationally.},
author = {Lovelace, Robin and Birkin, M and Talbot, Joseph and Morgan, Malcolm},
date = {2023},
institution = {Research Excellence Framework},
title = {Cycle Network Policy, Planning and Investment Transformed by the Propensity to Cycle Tool},
type = {Impact Case Study},
url = {https://results2021.ref.ac.uk/impact/847d1191-7f25-46ba-a399-b481125edc8f?page=1}
}
@article{lovelace_cycle_2024,
abstract = {This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.},
author = {Lovelace, Robin and Talbot, Joey and Vidal-Tortosa, Eugeni and Mahfouz, Hussein and Brick, Elaine and Wright, Peter and O’Toole, Gary and Brennan, Dan and Meade, Suzanne},
date = {2024-09-30},
doi = {10.1186/s12544-024-00668-8},
file = {/home/robin/Zotero/storage/PMDMD7I3/s12544-024-00668-8.html},
issn = {1866-8887},
journaltitle = {European Transport Research Review},
keywords = {Active travel,Collaborative planning,Cycling,Open source,Road safety,Transport planning},
number = {1},
pages = {55},
shortjournal = {European Transport Research Review},
shorttitle = {Cycle Route Uptake and Scenario Estimation (CRUSE)},
title = {Cycle Route Uptake and Scenario Estimation (CRUSE): An Approach for Developing Strategic Cycle Network Planning Tools},
url = {https://doi.org/10.1186/s12544-024-00668-8},
urldate = {2024-09-30},
volume = {16}
}
@article{lovelace_david_2017,
author = {Lovelace, Robin},
date = {2017},
file = {/home/robin/Zotero/storage/XQNXRS3B/urban-travel-rl.pdf},
journaltitle = {Environment and Planning B: Planning and Design},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
keywords = {Book review},
number = {1},
pages = {184--186},
title = {David Boyce and Huw Williams, Forecasting Urban Travel: Past, Present and Future},
volume = {44}
}
@article{lovelace_doctoral_2013,
author = {Lovelace, Robin},
date = {2013-03},
entrysubtype = {magazine},
journaltitle = {Doctoral Times},
abstract = {More captivating than any sci-fi book I''ve ever read.},
pages = {6},
title = {Doctoral Students Who Publish},
url = {http://www.sheffield.ac.uk/polopoly_fs/1.271737!/file/DoctoralTimes-Spring2013.pdf}
}
@article{lovelace_energy_2008,
author = {Lovelace, Robin},
date = {2008-09},
entrysubtype = {magazine},
issn = {1476-4687},
journaltitle = {Nature},
abstract = {Sustainability in Sheffield and beyond},
number = {7212},
pages = {460},
shorttitle = {Nature},
title = {Energy: Efficiency Gains Alone Won't Reduce Emissions.},
url = {http://dx.doi.org/10.1038/455461a},
volume = {455}
}
@thesis{lovelace_energy_2014,
author = {Lovelace, Robin},
date = {2014},
institution = {University of Sheffield},
title = {The Energy Costs of Commuting: A Spatial Microsimulation Approach},
abstract = {Sustainability in Sheffield and beyond},
type = {Thesis},
url = {http://etheses.whiterose.ac.uk/5027/}
}
@book{lovelace_engineering_2015,
author = {Lovelace, Robin and Mcloughlin, Andy},
date = {2015},
location = {London},
pagetotal = {135},
publisher = {Engineers Without Borders UK},
title = {Engineering in Development: Transport}
}
@article{lovelace_evaluating_2015,
abstract = {Iterative Proportional Fitting (IPF), also known as biproportional fitting, ‘raking’ or the RAS algorithm, is an established procedure used in a variety of applications across the social sciences. Primary amongst these for urban modelling has been its use in static spatial microsimulation to generate small area microdata — individual level data allocated to administrative zones. The technique is mature, widely used and relatively straight-forward. Although IPF is well described mathematically, accessible examples of the algorithm written in modern programming languages are rare. There is a tendency for researchers to ‘start from scratch’, resulting in a variety of ad hoc implementations and little evidence about the relative merits of differing approaches. These knowledge gaps mean that answers to certain methodological questions must be guessed: How can ‘empty cells’ be identified and how do they influence model fit? Can IPF be made more computationally efficient? This paper tackles these questions and more using a systematic methodology with publicly available code and data. The results demonstrate the sensitivity of the results to initial conditions, notably the presence of ‘empty cells’, and the dramatic impact of software decisions on computational efficiency. The paper concludes by proposing an agenda for robust and transparent future tests in the field.},
author = {Lovelace, Robin and Ballas, Dimitris and Birkin, Mark M.H. and family=Leeuwen, given=Eveline, prefix=van, useprefix=true and Ballas, Dimitris and family=Leeuwen, given=Eveline, prefix=van, useprefix=true and Birkin, Mark M.H.},
date = {2015-03},
issn = {1460-7425},
journaltitle = {Journal of Artificial Societies and Social Simulation},
keywords = {Deterministic Reweighting,Model Testing,Population Synthesis,Validation},
number = {2},
pages = {21},
title = {Evaluating the Performance of Iterative Proportional Fitting for Spatial Microsimulation: New Tests for an Established Technique},
url = {http://jasss.soc.surrey.ac.uk/18/2/21.html https://www.dropbox.com/s/szexnh80exjv3ov/ipfinr-jasss.pdf?dl=0},
volume = {18}
}
@article{lovelace_exploring_2022,
abstract = {Origin-Destination (OD) datasets provide vital information on how people travel between areas in many cities, regions and countries worldwide. OD datasets are usually represented geographically with straight lines or routes between zone centroids. For active travel, this geographic representation has substantial limitations, especially when zone origins and centroids are large: only using a single centroid origin/destination for each large zone results in sparse route networks covering only a small fraction of likely walking and cycling routes. This paper implements and explores the use of jittering and different routing options to overcome this limitation, thereby adding value to aggregate OD data to support investment in sustainable transport infrastructure. The route network results --- generated from on an open dataset representing cycling trips in Lisbon, Portugal --- were compared with a ground-truth dataset from 67 count locations distributed throughout the city. This approach enabled exploration of which jittering parameters and routing options lead to the most accurate route network results approximating the real geographic distribution of cycling trips in the study area. We found that jittering and disaggregating OD data, combined with routing using low level of traffic stress (quieter) preferences resulted in the most accurate route networks. We conclude that a combined approach involving 1) jittering with intermediate levels of disaggregation and 2) careful selection of routing options can lead to much more realistic route networks than using established OD processing techniques. The methods can be deployed to support evidence-based investment in strategic cycling and other sustainable transport networks in cities worldwide.},
author = {Lovelace, Robin and Félix, Rosa and Carlino, Dustin},
date = {2022-06-27T14:16:19},
doi = {10.5194/isprs-archives-XLVIII-4-W1-2022-279-2022},
file = {/home/robin/Zotero/storage/KRA32765/Lovelace et al. - 2022 - EXPLORING JITTERING AND ROUTING OPTIONS FOR CONVER.pdf;/home/robin/Zotero/storage/MRR6WBLA/Lovelace et al. - 2022 - Exploring jittering and routing options for conver.pdf;/home/robin/Zotero/storage/KQN9PINM/2022.html},
keywords = {Civil and Environmental Engineering,cycle networks,Education,Engineering,origin-destination data,route networks,routing,transport modelling,transport planning,Transportation Engineering},
langid = {american},
shorttitle = {Exploring Jittering and Routing Options for Converting Origin-Destination Data into Route Networks},
title = {Exploring Jittering and Routing Options for Converting Origin-Destination Data into Route Networks: Towards Accurate Estimates of Movement at the Street Level},
url = {https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-279-2022},
urldate = {2022-08-21}
}
@book{lovelace_geocomputation_2019,
abstract = {Book on geographic data with R.},
author = {Lovelace, Robin and Nowosad, Jakub and Muenchow, Jannes},
date = {2019},
isbn = {1-138-30451-4},
publisher = {CRC Press},
title = {Geocomputation with R},
url = {https://r.geocompx.org},
urldate = {2017-10-05}
}
@article{lovelace_geotagged_2014,
author = {Lovelace, Robin and Malleson, Nick and Harland, Kirk and Birkin, Mark},
date = {2014},
journaltitle = {Arxiv working paper},
abstract = {Information on the marginal external costs method in transport modelling and appraisal.},
title = {Geotagged Tweets to Inform a Spatial Interaction Model: A Case Study of Museums}
}
@online{lovelace_hint_2014,
abstract = {The parliamentary debate on cycling was a wake-up call to the government on cycling. The coalition government has been floundering, with a botched timeline for release of their Walking and Cycling Delivery\ ldots},
author = {Lovelace, Robin},
date = {2014-10},
title = {Hint of Proper Funding for Cycling, but We Must Fight for It – with Evidence},
url = {http://theconversation.com/hint-of-proper-funding-for-cycling-but-we-must-fight-for-it-with-evidence-33152 https://theconversation.com/hint-of-proper-funding-for-cycling-but-we-must-fight-for-it-with-evidence-33152}
}
@online{lovelace_how_2010,
author = {Lovelace, Robin},
date = {2010},
title = {How to Set Up and Run a Bicycle Repair Company},
abstract = {This tutorial is an introduction to spatial data in R and map making with R''s `base'' graphics and the popular graphics package ggplot2. It assumes no prior knowledge of spatial data analysis but prior understanding of the R command line would be beneficial. For people new to R, we recommend working through an `Introduction to R'' type tutorial, such as "A (very) short introduction to R" (Torfs and Brauer, 2012) or the more geographically inclined "Short introduction to R" (Harris, 2012). Building on such background material, the following set of exercises is concerned with specific functions for spatial data and visualisation. It is divided into five parts: *Introduction, which provides a guide to R''s syntax and preparing for the tutorial *Spatial data in R, which describes basic spatial functions in R *Manipulating spatial data, which includes changing projection, clipping and spatial joins *Map making with ggplot2, a recent graphics package for producing beautiful maps quickly *Taking spatial analysis in R further, a compilation of resources for furthering your skills An up-to-date version of this tutorial is maintained at https://github.com/Robinlovelace/Creating-maps-in-R and the entire tutorial, including the input data can be downloaded as a zip file, as described below. The entire tutorialwas written in RMarkdown, which allows R code to run as the document compiles. Thus all the examples are entirely reproducible. Suggested improvements welcome - please fork, improve and push this document to its original home to ensure its longevity. The tutorial was developed for a series of Short Courses put on by the National Centre for Research Methods, via the TALISMAN node (see geotalisman.org).},
url = {http://campfire.theoildrum.com/node/5976}
}
@article{lovelace_introducing_2014,
author = {Lovelace, Robin},
date = {2014},
entrysubtype = {magazine},
journaltitle = {National Centre for Research Methods},
abstract = {Creating and maintaining large spatial address datasets to an exceptional standard of currency and accuracy requires specialist skills and expertise.},
number = {14},
title = {Introducing Spatial Microsimulation with R: A Practical},
url = {http://eprints.ncrm.ac.uk/3348/},
volume = {08}
}
@article{lovelace_jittering_2022b,
abstract = {Origin-destination (OD) datasets are often represented as ‘desire lines’ between zone centroids. This paper presents a ‘jittering’ approach to pre-processing and conversion of OD data into geographic desire lines that (1) samples unique origin and destination locations for each OD pair, and (2) splits ‘large’ OD pairs into ‘sub-OD’ pairs. Reproducible findings, based on the open source _odjitter_ Rust crate, show that route networks generated from jittered desire lines are more geographically diffuse than route networks generated by ‘unjittered’ data. We conclude that the approach is a computationally efficient and flexible way to simulate transport patterns, particularly relevant for modelling active modes. Further work is needed to validate the approach and to find optimal settings for sampling and disaggregation.},
author = {Lovelace, Robin and Félix, Rosa and Carlino, Dustin},
date = {2022-04-08},
doi = {10.32866/001c.33873},
file = {/home/robin/Zotero/storage/MW7B8GVG/Lovelace et al. - 2022 - Jittering A Computationally Efficient Method for .pdf;/home/robin/Zotero/storage/QZU3J666/33873-jittering-a-computationally-efficient-method-for-generating-realistic-route-networks-from.html},
journaltitle = {Findings},
langid = {english},
pages = {33873},
publisher = {Findings Press},
shortjournal = {Findings},
shorttitle = {Jittering},
title = {Jittering: A Computationally Efficient Method for Generating Realistic Route Networks from Origin-Destination Data},
url = {https://findingspress.org/article/33873-jittering-a-computationally-efficient-method-for-generating-realistic-route-networks-from-origin-destination-data},
urldate = {2022-05-05}
}
@article{lovelace_jornadas_2014,
author = {Lovelace, Robin},
date = {2014},
entrysubtype = {magazine},
journaltitle = {Geoinformatics},
abstract = {Pro-cycling interventions, and cycle hire schemes in particular, are often assumed to primarily benefit the privileged. This framing has played-out in academic research, with many papers exploring the relationship between cycling and existing inequalities. A growing body of evidence suggests that cycle hire schemes tend to serve wealthy areas and young, high income groups, mirroring inequalities in other types of cycling uptake, yet there has been little research into the `direction of travel'' and whether such inequalities are growing or `levelling up'' over time. This paper explores the uptake of the London Cycle Hire Scheme (LCHS), a large, early and prominent scheme that had the explicit aim of `normalising'' cycling. The method involved reproducible analysis (with code documented in the GitHub repo Robinlovelace/cycle-hire-inclusive) of 73.4 million cycle high records spanning 8~years from January 2012 to December 2019, using the geographic location of docking stations alongside official statistics to assess social and spatial inequalities in uptake. The method involved analysis of 73.4 million cycle high records spanning 8~years from January 2012 to December 2019, using the geographic location of docking stations alongside official statistics to assess social and spatial inequalities in uptake. We found that, contrary to the trend for increasing segregation and geographic inequalities, the usage of the LCHS have become increasingly geographically distributed across London over time, with AM peak usage in comparatively low-income areas seeing high levels of growth. Our study shows that cycle hire schemes can be designed and expanded in ways that benefit a wide range of people, including those from low income areas, and that new cycle hire docking stations in poorer areas can succeed.},
number = {4},
pages = {12--12},
title = {Jornadas de SIG Libre: A European Digital Mapping Conference},
url = {http://fluidbook.geoinformatics.com/GEO-Informatics_4_2014/#/12/},
volume = {17}
}
@article{lovelace_london_2020,
abstract = {Pro-cycling interventions, and cycle hire schemes in particular, are often assumed to primarily benefit the privileged. This framing has played-out in academic research, with many papers exploring the relationship between cycling and existing inequalities. A growing body of evidence suggests that cycle hire schemes tend to serve wealthy areas and young, high income groups, mirroring inequalities in other types of cycling uptake, yet there has been little research into the ‘direction of travel’ and whether such inequalities are growing or ‘levelling up’ over time. This paper explores the uptake of the London Cycle Hire Scheme (LCHS), a large, early and prominent scheme that had the explicit aim of ‘normalising’ cycling. The method involved reproducible analysis (with code documented in the GitHub repo Robinlovelace/cycle-hire-inclusive) of 73.4 million cycle high records spanning 8~years from January 2012 to December 2019, using the geographic location of docking stations alongside official statistics to assess social and spatial inequalities in uptake. The method involved analysis of 73.4 million cycle high records spanning 8~years from January 2012 to December 2019, using the geographic location of docking stations alongside official statistics to assess social and spatial inequalities in uptake. We found that, contrary to the trend for increasing segregation and geographic inequalities, the usage of the LCHS have become increasingly geographically distributed across London over time, with AM peak usage in comparatively low-income areas seeing high levels of growth. Our study shows that cycle hire schemes can be designed and expanded in ways that benefit a wide range of people, including those from low income areas, and that new cycle hire docking stations in poorer areas can succeed.},
author = {Lovelace, Robin and Beecham, Roger and Heinen, Eva and Vidal Tortosa, Eugeni and Yang, Yuanxuan and Slade, Chris and Roberts, Antonia},
date = {2020-10-01},
doi = {10.1016/j.tra.2020.07.017},
file = {/home/robin/Zotero/storage/37HJ9EUF/Lovelace et al. - 2020 - Is the London Cycle Hire Scheme becoming more incl.pdf;/home/robin/Zotero/storage/JU8GR8MI/S0965856420306728.html},
issn = {0965-8564},
journaltitle = {Transportation Research Part A: Policy and Practice},
keywords = {Big data,Bikeshare,Cycle hire,Reproducible data science,Transport equity},
langid = {english},
pages = {1--15},
shortjournal = {Transportation Research Part A: Policy and Practice},
shorttitle = {Is the London Cycle Hire Scheme Becoming More Inclusive?},
title = {Is the London Cycle Hire Scheme Becoming More Inclusive? An Evaluation of the Shifting Spatial Distribution of Uptake Based on 70 Million Trips},
url = {http://www.sciencedirect.com/science/article/pii/S0965856420306728},
urldate = {2020-09-14},
volume = {140}
}
@article{lovelace_mapping_2016,
author = {Lovelace, Robin},
date = {2016},
file = {/home/robin/Zotero/storage/84X46AAD/Get_Britain_Cycling_2016_PCT.pdf},
journaltitle = {Get Britain Cycling},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
pages = {22--24},
title = {Mapping out the Future of Cycling},
url = {http://eprints.whiterose.ac.uk/100080/},
urldate = {2016-06-08},
volume = {5}
}
@article{lovelace_methods_2020,
abstract = {In the context of reduced public transport capacity in the wake of the COVID-19 pandemic, governments are scrambling to enable walking and cycling while adhering to physical distancing guidelines. Many pop-up options exist. Of these, road space reallocation represents a ‘quick win’ for cities with ‘spare space’ along continuous road sections that have high latent cycling potential. We developed methods to condense the complexity of city networks down to the most promising roads for road space reallocation schemes. The resulting Rapid Cycleway Prioritisation Tool has been deployed for all cities in England to help prioritise emergency funds for new cycleways nationwide. The methods and concepts could be used to support investment in pop-up infrastructure in cities worldwide.},
author = {Lovelace, Robin and Talbot, Joseph and Morgan, Malcolm and Lucas-Smith, Martin},
date = {2020-07-08},
doi = {10.32866/001c.13421},
file = {/home/robin/Zotero/storage/LUTQ95M3/Lovelace et al. - 2020 - Methods to Prioritise Pop-up Active Transport Infr.pdf;/home/robin/Zotero/storage/PQ9Y4INZ/13421-methods-to-prioritise-pop-up-active-transport-infrastructure.html},
ids = {Lovelace2020Methods},
journaltitle = {Transport Findings},
langid = {english},
pages = {13421},
publisher = {Network Design Lab},
shortjournal = {Transport Findings},
title = {Methods to Prioritise Pop-up Active Transport Infrastructure},
url = {https://transportfindings.org/article/13421-methods-to-prioritise-pop-up-active-transport-infrastructure},
urldate = {2020-07-08}
}
@article{lovelace_mystery_2012,
author = {Lovelace, Robin},
date = {2012-02},
entrysubtype = {magazine},
journaltitle = {Now Then},
abstract = {This paper explores the potential for emerging methods Machine Learning and Directed Acyclic Graphs (DAGs) to be applied to transport modelling at the origin-destination (OD) level. OD data is inherently spatial and is complex, due to the multitude of ways of allocating geographic attributes to the OD pairs (e.g. buffers and intersections with geographic representations of OD data generated using straight desire lines, shortest path algorithms or probabilistic routing). This makes their analysis an interesting geocomputational challenge, seldom tackled by geographers. The application of Machine Learning and DAG methods, developed in other fields, to this geographical data holds great potential to improve the ability to infer causality in mode split from OD data. However, there are also pitfalls to using these methods which can be black boxes, even if the code is open source, if the analyst does not understand what they are doing with the data. Based on the work we discuss ways to ensure new methods in the field are used wisely and set-out next steps for our own research.},
title = {The Mystery of Sheffield's Steepest Hill},
url = {http://nowthenmagazine.com/issue-47/hills/}
}
@article{lovelace_oil_2014,
author = {Lovelace, Robin and Philips, Ian},
date = {2014-01},
doi = {http://dx.doi.org/10.1016/j.geoforum.2013.11.005},
issn = {0016-7185},
journaltitle = {Geoforum},
abstract = {This paper reviews research traditions of vulnerability to environmental change and the challenges for present vulnerability research in integrating with the domains of resilience and adaptation. Vulnerability is the state of susceptibility to harm from exposure to stresses associated with environmental and social change and from the absence of capacity to adapt. Antecedent traditions include theories of vulnerability as entitlement failure and theories of hazard. Each of these areas has contributed to present formulations of vulnerability to environmental change as a characteristic of social-ecological systems linked to resilience. Research on vulnerability to the impacts of climate change spans all the antecedent and successor traditions. The challenges for vulnerability research are to develop robust and credible measures, to incorporate diverse methods that include perceptions of risk and vulnerability, and to incorporate governance research on the mechanisms that mediate vulnerability and promote adaptive action and resilience. These challenges are common to the domains of vulnerability, adaptation and resilience and form common ground for consilience and integration. © 2006 Elsevier Ltd. All rights reserved.},
keywords = {Oil vulnerability,Peak oil,resilience,vulnerability},
number = {0},
pages = {169--182},
title = {The ‘Oil Vulnerability’ of Commuter Patterns: A Case Study from Yorkshire and the Humber, UK},
url = {http://www.sciencedirect.com/science/article/pii/S0016718513002480},
volume = {51}
}
@article{lovelace_open_2020,
abstract = {A large and growing body of evidence suggests fundamental changes are needed in transport systems, to tackle issues such as air pollution, physical inactivity and climate change. Transport models can play a major role in tackling these issues through the transport planning process, but they have historically been focussed on motorised modes (especially cars) and available only to professional transport planners working within the existing paradigm. Building on the principles of open access software, first developed in the context of geographic information systems, this paper develops and discusses the concept of open access transport models, which we define as models that are both developed using open source software and are available to be used by the public without the need for specialist training or the purchase of software licences. We explore the future potential of open access transport models to support the transition away from fossil fuels in the transport sector. We do this with reference to the literature on the use of tools in the planning process, and by exploring an example that is already in use: the ‘Propensity to Cycle Tool’. We conclude that open access transport models can be a leverage point in the planning process due to their ability to provide robust, transparent and actionable evidence that is available to a range of stakeholders, not just professional transport planners. Open access transport models represent a disruptive technology deserving further research and development, by planners, researchers and citizen scientists, including open source software developers and advocacy groups but, in order to fulfil their potential, they will require both financial and policy support from government bodies.},
author = {Lovelace, Robin and Parkin, John and Cohen, Tom},
date = {2020-10-01},
doi = {10.1016/j.tranpol.2020.06.015},
file = {/home/robin/Zotero/storage/MNB2VCS6/Lovelace et al. - 2020 - Open access transport models A leverage point in .pdf;/home/robin/Zotero/storage/VPTJXKA6/Lovelace et al. - 2020 - Open access transport models A leverage point in .pdf;/home/robin/Zotero/storage/9TKN7ZXD/S0967070X19302781.html;/home/robin/Zotero/storage/MJ3A6X2A/S0967070X19302781.html},
ids = {lovelace_open_2020a},
issn = {0967-070X},
journaltitle = {Transport Policy},
keywords = {Accessible models,Cycling,Demand modelling,Open access data,Open access models,Open access software,Sustainable transport,Transport planning},
langid = {english},
pages = {47--54},
shortjournal = {Transport Policy},
shorttitle = {Open Access Transport Models},
title = {Open Access Transport Models: A Leverage Point in Sustainable Transport Planning},
url = {http://www.sciencedirect.com/science/article/pii/S0967070X19302781},
urldate = {2020-08-04},
volume = {97}
}
@article{lovelace_open_2021,
abstract = {Geographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent ‘tools of the trade’ are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques—such as route analysis, network editing, localised impact assessment and interactive map visualisation—have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ‘ecosystem’ tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid ‘reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street https://github.com/dabreegster/abstreet/#abstreetsimulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at https://github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.},
annotation = {31 citations (Crossref) [2024-10-06]},
author = {Lovelace, Robin},
date = {2021-10-01},
doi = {10.1007/s10109-020-00342-2},
file = {/home/robin/Zotero/storage/N8T7PAQF/Lovelace - 2021 - Open source tools for geographic analysis in trans.pdf},
issn = {1435-5949},
journaltitle = {Journal of Geographical Systems},
keywords = {Artificial Intelligence,C6,Geographic data,Geographic data analysis,Open source,R41,Software,Transport modelling,Transport planning},
langid = {english},
number = {4},
pages = {547--578},
shortjournal = {J Geogr Syst},
title = {Open Source Tools for Geographic Analysis in Transport Planning},
url = {https://doi.org/10.1007/s10109-020-00342-2},
urldate = {2024-10-06},
volume = {23}
}
@article{lovelace_overcoming_2014,
author = {Lovelace, Robin},
date = {2014},
entrysubtype = {magazine},
issn = {0265-8135},
journaltitle = {Environment and Planning B-Planning and Design},
abstract = {In this podcast, ICE''s Adam Kirkup interviews~Dr. Robin Lovelace, University of Leeds, discussing the development of the Propensity to Cycle Toolkit (PCT), and how it can be used to prioritise investments and interventions which promote cycling.},
keywords = {Book review},
number = {5},
pages = {948--949},
title = {Overcoming Car Dependence: Review of “The Car Dependent Society–a European Perspective”},
volume = {41}
}
@article{lovelace_propensity_2017,
abstract = {Getting people cycling is an increasingly common objective in transport planning institutions worldwide. A growing evidence base indicates that high quality infrastructure can boost local cycling rates. Yet for infrastructure and other cycling measures to be effective, it is important to intervene in the right places, such as along ‘desire lines’ of high latent demand. This creates the need for tools and methods to help answer the question ‘where to build?’. Following a brief review of the policy and research context related to this question, this paper describes the design, features and potential applications of such a tool. The Propensity to Cycle Tool (PCT) is an online, interactive planning support system that was initially developed to explore and map cycling potential across England (see www.pct.bike). Based on origin-destination data it models cycling levels at area, desire line, route and route network levels, for current levels of cycling, and for scenario-based ‘cycling futures.’ Four scenarios are presented, including ‘Go Dutch’ and ‘Ebikes,’ which explore what would happen if English people had the same propensity to cycle as Dutch people and the potential impact of electric cycles on cycling uptake. The cost effectiveness of investment depends not only on the number of additional trips cycled, but on wider impacts such as health and carbon benefits. The PCT reports these at area, desire line, and route level for each scenario. The PCT is open source, facilitating the creation of scenarios and deployment in new contexts. We conclude that the PCT illustrates the potential of online tools to inform transport decisions and raises the wider issue of how models should be used in transport planning.},
author = {Lovelace, Robin and Goodman, Anna and Aldred, Rachel and Berkoff, Nikolai and Abbas, Ali and Woodcock, James},
date = {2017-01-01},
doi = {10.5198/jtlu.2016.862},
file = {/home/robin/Zotero/storage/M9Y6T54T/Lovelace et al. - 2017 - The Propensity to Cycle Tool An open source onlin.pdf},
issn = {1938-7849},
journaltitle = {Journal of Transport and Land Use},
keywords = {Cycling,Participatory,Planning},
langid = {english},
number = {1},
shorttitle = {The Propensity to Cycle Tool},
title = {The Propensity to Cycle Tool: An Open Source Online System for Sustainable Transport Planning},
url = {https://doi.org/10.5198/jtlu.2016.862},
urldate = {2017-06-01},
volume = {10}
}
@report{lovelace_reproducible_2020,
author = {Lovelace, Robin},
date = {2020},
file = {/home/robin/Zotero/storage/4F5XH3KS/Lovelace - Reproducible road safety research with R.pdf;/home/robin/Zotero/storage/56B6K334/Lovelace - Reproducible road safety research with R.pdf},
ids = {lovelace_reproducible_2020a},
institution = {Royal Automotive Club Foundation},
langid = {english},
pages = {102},
title = {Reproducible Road Safety Research with R},
abstract = {Route network datasets, crucial to transport models, have grown complex, leading to visualization issues and potential misinterpretations. We address this by presenting two methods for simplifying these datasets: image skeletonization and Voronoi diagram-centreline identification. We have developed two packages, the ‘parenx’ Python package (available on pip) and the ‘rnetmatch’ R package (available on GitHub) to implement these methods. The approach has applications in transportation, demonstrated by their use in the publicly available Network Planning Tool funded by Transport for Scotland.},
type = {Tutorial},
url = {https://www.racfoundation.org/wp-content/uploads/Reproducible_road_safety_research_with_R_Lovelace_December_2020.pdf}
}
@inproceedings{lovelace_reproducible_2024,
abstract = {Route network datasets, crucial to transport models, have grown complex, leading to visualization issues and potential misinterpretations. We address this by presenting two methods for simplifying these datasets: image skeletonization and Voronoi diagram-centreline identification. We have developed two packages, the ‘parenx’ Python package (available on pip) and the ‘rnetmatch’ R package (available on GitHub) to implement these methods. The approach has applications in transportation, demonstrated by their use in the publicly available Network Planning Tool funded by Transport for Scotland.},
author = {Lovelace, Robin and Wang, Zhao and Deakin, Will and Parry, Josiah},
booktitle = {32nd GISRUK Conference 2024},
date = {2024-04-11},
doi = {10.5281/zenodo.11077553},
eventtitle = {GISRUK},
file = {/home/robin/Zotero/storage/EZ475BRU/Lovelace et al. - 2024 - Reproducible methods for network simplification fo.pdf},
location = {Leeds},
publisher = {Zenodo},
title = {Reproducible Methods for Network Simplification for Data Visualisation and Transport Planning},
url = {https://zenodo.org/records/11077553},
urldate = {2024-05-02}
}
@article{lovelace_review_2014,
author = {Lovelace, Robin},
date = {2014-05},
doi = {10.1016/j.jtrangeo.2014.05.002},
file = {/home/robin/Zotero/storage/7ARD2ADQ/Review-Sage-Handbook-transport-studies-RL-Final.pdf},
issn = {09666923},
journaltitle = {Journal of Transport Geography},
abstract = {This paper presents a new density-based clustering algorithm, ST-DBSCAN, which is based on DBSCAN. We propose three marginal extensions to DBSCAN related with the identification of (i) core objects, (ii) noise objects, and (iii) adjacent clusters. In contrast to the existing density-based clustering algorithms, our algorithm has the ability of discovering clusters according to non-spatial, spatial and temporal values of the objects. In this paper, we also present a spatial–temporal data warehouse system designed for storing and clustering a wide range of spatial–temporal data. We show an implementation of our algorithm by using this data warehouse and present the data mining results.},
keywords = {Book review,Review},
pages = {2013--2014},
title = {Review: Sage Handbook of Transport Studies, Jean-Paul Rodrigue, Theo Notteboom, Jon Shaw (Eds.). Sage, London (2013). £95, Hardback, ISBN: 978-1-84920-789-8},
url = {http://linkinghub.elsevier.com/retrieve/pii/S096669231400088X}
}
@article{lovelace_sacred_2013,
author = {Lovelace, Robin},
date = {2013-02},
entrysubtype = {magazine},
journaltitle = {Now Then},
keywords = {Book review,degrowth},
title = {Sacred Economics},
url = {http://nowthenmagazine.com/issue-59/sacred-economics/}
}
@article{lovelace_spatial_2013,
author = {Lovelace, Robin and Ballas, Dimitris and Watson, Matt},
date = {2013-08},
doi = {10.1016/j.jtrangeo.2013.07.008},
file = {/home/robin/Zotero/storage/47F7WWV5/Lovelace et al. - 2014 - A spatial microsimulation approach for the analysi.pdf;/home/robin/Zotero/storage/9IM82VC6/Lovelace et al. - 2013 - A spatial microsimulation approach for the analysi.pdf;/home/robin/Zotero/storage/2U5995WL/S0966692313001361.html;/home/robin/Zotero/storage/LHE7TBZG/S0966692313001361.html},
ids = {lovelace_spatial_2014},
issn = {09666923},
journaltitle = {Journal of Transport Geography},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
keywords = {Commuting,Policy evaluation,Spatial microsimulation},
publisher = {Elsevier},
title = {A Spatial Microsimulation Approach for the Analysis of Commuter Patterns: From Individual to Regional Levels},
url = {http://dx.doi.org/10.1016/j.jtrangeo.2013.07.008},
volume = {34}
}
@book{lovelace_spatial_2016,
author = {Lovelace, Robin and Dumont, Morgane},
date = {2016},
file = {/home/robin/Zotero/storage/G4IGUB3X/books.html},
publisher = {CRC Press},
title = {Spatial Microsimulation with R},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
url = {https://spatial-microsim-book.robinlovelace.net/}
}
@article{lovelace_stats19_2019,
author = {Lovelace, Robin and Morgan, Malcolm and Hama, Layik and Padgham, Mark},
date = {2019},
doi = {10.21105/joss.01181},
ids = {stats192019},
journaltitle = {Journal of Open Source Software},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
number = {33},
pages = {1181},
publisher = {[object Object]},
title = {Stats19 A Package for Working with Open Road Crash Data},
url = {http://doi.org/10.21105/joss.01181},
volume = {4}
}
@article{lovelace_stplanr_2018,
abstract = {stplanr - R package providing functions and data access for transport research},
author = {Lovelace, Robin and Ellison, Richard},
date = {2018},
doi = {10.32614/RJ-2018-053},
file = {/home/robin/Zotero/storage/Y7KU3RMP/Lovelace and Ellison - 2018 - stplanr A Package for Transport Planning.pdf;/home/robin/Zotero/storage/AEGWQPFR/stplanr-paper.html},
journaltitle = {The R Journal},
number = {2},
pages = {7--23},
title = {Stplanr: A Package for Transport Planning},
url = {https://doi.org/10.32614/RJ-2018-053},
urldate = {2016-11-24},
volume = {10}
}
@article{lovelace_truncate_2013,
author = {Lovelace, Robin and Ballas, Dimitris},
date = {2013-09},
issn = {01989715},
journaltitle = {Computers, Environment and Urban Systems},
abstract = {Estimates of the volume of travel between zones or locations is often a necessary step in transportation studies. This paper suggests a method of estimating origin/destination volumes, using a direct demand function and incomplete, aggregate data. Most attention is devoted to demand functions which are linear in their parameters. With such demand functions, volume estimates are obtained from a quadratic programming problem, which minimizes the sum of squared errors from a direct demand function, subject to constraints derived from observations of some travel volumes. A decomposition algorithm is suggested for solving the programming problem and is proven to converge. The method may also be used in the trip distribution phase of the conventional urban transportation model systems (UTMS).},
pages = {1--11},
title = {‘Truncate, Replicate, Sample’: A Method for Creating Integer Weights for Spatial Microsimulation},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0198971513000240},
volume = {41}
}
@article{lovelace_who_2016,
author = {Lovelace, Robin and Roberts, Hannah and Kellar, Ian},
date = {2016},
doi = {10.1016/j.trf.2015.02.010},
file = {/home/robin/Zotero/storage/8GIWK5II/Lovelace et al. - 2016 - Who, where, when the demographic and geographic d.pdf},
issn = {13698478},
journaltitle = {Transportation Research Part F: Traffic Psychology and Behaviour},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
keywords = {Cycling,Exposure,Geographical factors,Risk,Safety},
series = {Bicycling and Bicycle Safety},
title = {Who, Where, When: The Demographic and Geographic Distribution of Bicycle Crashes in West Yorkshire},
url = {http://eprints.whiterose.ac.uk/83930/},
volume = {41, Part B}
}
@article{lovelace_yer_2012,
author = {Lovelace, Robin},
date = {2012-12},
entrysubtype = {magazine},
journaltitle = {Now Then},
abstract = {This paper presents a new density-based clustering algorithm, ST-DBSCAN, which is based on DBSCAN. We propose three marginal extensions to DBSCAN related with the identification of (i) core objects, (ii) noise objects, and (iii) adjacent clusters. In contrast to the existing density-based clustering algorithms, our algorithm has the ability of discovering clusters according to non-spatial, spatial and temporal values of the objects. In this paper, we also present a spatial–temporal data warehouse system designed for storing and clustering a wide range of spatial–temporal data. We show an implementation of our algorithm by using this data warehouse and present the data mining results.},
keywords = {bicycle},
pages = {23--24},
title = {On Yer Bike: Joining the Sustainable Transport Revolution},
url = {http://nowthenmagazine.com/issue-57/on-yer-bike/}
}
@article{mahfouz_drt_operating_2025,
author = {Mahfouz, Hussein and Morgan, Malcolm and Heinen, Eva and Lovelace, Robin},
date = {2025-12},
doi = {10.1016/j.urbmob.2025.100135},
issn = {2667-0917},
journaltitle = {Journal of Urban Mobility},
abstract = {Investment in Demand-Responsive Transport (DRT) has emerged as a sustainable transport intervention option for areas that are traditionally hard to serve by high frequency public transport. When used as a first- and last-mile feeder, DRT has the potential to reduce car dependency and enhance access to the wider network. However, many DRT schemes fail—often due to overly flexible, poorly targeted service areas that do not align with actual travel patterns, making efficient pooling difficult. While planners may already have a general sense of where DRT might be useful, there is limited guidance on how to identify precise operating zones based on spatiotemporal demand. This paper presents a method for identifying potential DRT service areas using spatial clustering of origin–destination (OD) flows. We apply the method in Leeds, UK, focusing on OD pairs with poor public transport supply and low potential demand. The approach identifies spatial clusters where demand is both underserved and sufficiently concentrated to support DRT operation. By narrowing service areas to zones where pooling is more likely and where DRT complements rather than competes with fixed-route services, the method helps address two key challenges in DRT planning. The results offer a reproducible, data-driven input for delineating preliminary DRT service areas—supporting strategic planning, integration with downstream agent-based models, and further refinement through local knowledge. The method provides a foundation for future work on designing DRT services that complement the public transport network, particularly in low-density urban peripheries.},
langid = {english},
pages = {100135},
title = {Delineating potential DRT operating areas: An origin–destination clustering approach},
url = {https://www.sciencedirect.com/science/article/pii/S2667091725000378},
volume = {8}
}
@manual{mahfouz_flowcluster_2025,
author = {Mahfouz, Hussein and Lovelace, Robin},
date = {2025},
doi = {10.32614/CRAN.package.flowcluster},
langid = {english},
title = {flowcluster: Cluster origin-destination flow data},
abstract = {This paper presents a new density-based clustering algorithm, ST-DBSCAN, which is based on DBSCAN. We propose three marginal extensions to DBSCAN related with the identification of (i) core objects, (ii) noise objects, and (iii) adjacent clusters. In contrast to the existing density-based clustering algorithms, our algorithm has the ability of discovering clusters according to non-spatial, spatial and temporal values of the objects. In this paper, we also present a spatial–temporal data warehouse system designed for storing and clustering a wide range of spatial–temporal data. We show an implementation of our algorithm by using this data warehouse and present the data mining results.},
url = {https://CRAN.R-project.org/package=flowcluster}
}
@article{mahfouz_road_2023,
abstract = {Understanding the motivators and deterrents to cycling is essential for creating infrastructure that gets more people to adopt cycling as a mode of transport. This paper demonstrates a new approach to support the prioritization of cycling infrastructure and cycling network design, accounting for cyclist preferences and the growing emphasis on ‘filtered permeability’ and ‘Low Traffic Neighborhood’ interventions internationally. The approach combines distance decay, route calculation, and network analysis methods to examine where future cycling demand is most likely to arise, how such demand could be accommodated within existing street networks, and how to ensure a fair distribution of investment. Although each of these methods has been applied to cycling infrastructure prioritization in previous research, this is the first time that they have been combined, creating an integrated road segment prioritization approach. The approach, which can be applied to other cities, is demonstrated in a case study of Manchester, resulting in cycling networks that balance directness against the need for safe and stress-free routes under different investment scenarios. A key benefit of the approach from a policy perspective is its ability to support egalitarian and cost-effective strategic cycle network planning.},
annotation = {0 citations (Crossref) [2023-11-17]},
author = {Mahfouz, Hussein and Lovelace, Robin and Arcaute, Elsa},
date = {2023-12-01},
doi = {10.1016/j.jtrangeo.2023.103715},
file = {/home/robin/Zotero/storage/IPFGXV4F/Mahfouz et al. - 2023 - A road segment prioritization approach for cycling.pdf;/home/robin/Zotero/storage/JHMA5IH2/S0966692323001874.html},
issn = {0966-6923},
journaltitle = {Journal of Transport Geography},
keywords = {Cycling networks,Low-traffic neighborhoods,Routing,Transport equity},
pages = {103715},
shortjournal = {Journal of Transport Geography},
title = {A Road Segment Prioritization Approach for Cycling Infrastructure},
url = {https://www.sciencedirect.com/science/article/pii/S0966692323001874},
urldate = {2023-11-17},
volume = {113}
}
@article{mason-jones_severe_2022,
abstract = {Pedal cycling is advocated for increasing physical activity and promoting health and wellbeing. However, whilst some countries have achieved zero cyclist deaths on their roads, this is not the case for Great Britain (GB). A retrospective cross-sectional analysis was conducted of STATS19 cyclist crash data, a dataset of all police-reported traffic crashes in GB. Information about crash location, casualty, driver and vehicles involved were included as predictors of casualty severity (fatal or severe vs. slight). Sixteen thousand one hundred seventy pedal cycle crashes were reported during 2018. Severe or fatal cyclist crash injury was associated with increasing age of the cyclist (35–39~years, OR 1.38, 95% CI 1.11 to 1.73; 55–59~years, OR 1.73, 95% CI 1.35 to 2.2; 70~years and over, OR 2.87, 95% CI 2.12 to 3.87), higher road speed limits (50 MPH OR 2.10, 95% CI 1.43 to 3.07; 70 MPH OR 4.12, 95% CI 2.12 to 8.03), the involvement of goods vehicles (OR 2.08, 95% CI 1.30 to 3.33) and the months of May and June (OR 1.34 to 1.36, 95% CI 1.06 to 1.73). Urban planning that includes physical separation of pedal cyclists from other road users, raising awareness around the risks from goods vehicles and reducing road speed should be the urgent focus of interventions to increase the benefits and safety of cycling.},
author = {Mason-Jones, Amanda J. and Turrell, Stephen and Gomez, Gerardo Zavala and Tait, Caroline and Lovelace, Robin},
date = {2022-04-01},
doi = {10.1007/s11524-022-00617-7},
file = {/home/robin/Zotero/storage/NLL6MP2B/Mason-Jones et al. - 2022 - Severe and Fatal Cycling Crash Injury in Britain .pdf},
issn = {1468-2869},
journaltitle = {Journal of Urban Health},
keywords = {Cycling,Epidemiology,Injury,Prevention,Road safety,Urban planning},
langid = {english},
number = {2},
pages = {334--343},
shortjournal = {J Urban Health},
shorttitle = {Severe and Fatal Cycling Crash Injury in Britain},
title = {Severe and Fatal Cycling Crash Injury in Britain: Time to Make Urban Cycling Safer},
url = {https://doi.org/10.1007/s11524-022-00617-7},
urldate = {2022-05-05},
volume = {99}
}
@article{moreno-monroy_public_2017,
abstract = {In many large Latin American urban areas such as the São Paulo Metropolitan Region (SPMR), growing social and economic inequalities are embedded through high spatial inequality in the provision of state schools and affordable public transport to these schools. This paper sheds light on the transport-education inequality nexus with reference to school accessibility by public transport in the SPMR. To assess school accessibility, we develop an accessibility index which combines information on the spatial distribution of adolescents, the location of existing schools, and the public transport provision serving the school catchment area into a single measure. The index is used to measure school accessibility locally across 633 areas within the SPMR. We use the index to simulate the impact of a policy aiming at increasing the centralisation of public secondary education provision, and find that it negatively affects public transport accessibility for students with the lowest levels of accessibility. These results illustrate how existing inequalities can be amplified by variable accessibility to schools across income groups and geographical space. The research suggests that educational inequality impacts of school agglomeration policies should be considered before centralisation takes place.},
author = {Moreno-Monroy, Ana I. and Lovelace, Robin and Ramos, Frederico R.},
date = {2017-09-15},
doi = {10.1016/j.jtrangeo.2017.08.012},
file = {/home/robin/Zotero/storage/ZPMN72EA/Moreno-Monroy et al. - 2018 - Public transport and school location impacts on ed.pdf;/home/robin/Zotero/storage/FCEI6MKH/S0966692316303453.html},
issn = {0966-6923},
journaltitle = {Journal of Transport Geography},
keywords = {Accessibility,Inequality,Latin America,Public transport,Schools},
shortjournal = {Journal of Transport Geography},
shorttitle = {Public Transport and School Location Impacts on Educational Inequalities},
title = {Public Transport and School Location Impacts on Educational Inequalities: Insights from São Paulo},
url = {http://www.sciencedirect.com/science/article/pii/S0966692316303453},
urldate = {2017-10-15},
volume = {67}
}
@article{morgan_opentripplanner_2019,
abstract = {Morgan et al., (2019). OpenTripPlanner for R. Journal of Open Source Software, 4(44), 1926, https://doi.org/10.21105/joss.01926},
annotation = {ZSCC: 0000000},
author = {Morgan, Malcolm and Young, Marcus and Lovelace, Robin and Hama, Layik},
date = {2019-12-02},
doi = {10.21105/joss.01926},
file = {/home/robin/Zotero/storage/4SLLZ5YE/Morgan et al. - 2019 - OpenTripPlanner for R.pdf},
issn = {2475-9066},
journaltitle = {Journal of Open Source Software},
langid = {english},
number = {44},
pages = {1926},
title = {OpenTripPlanner for R},
url = {https://joss.theoj.org/papers/10.21105/joss.01926},
urldate = {2020-01-29},
volume = {4}
}
@article{morgan_travel_2020,
author = {Morgan, Malcolm and Lovelace, Robin},
date = {2020-07},
doi = {10.1177/2399808320942779},
file = {/home/robin/Zotero/storage/PFJBTCV8/Morgan and Lovelace - 2020 - Travel flow aggregation Nationally scalable metho.pdf;/home/robin/Zotero/storage/3MAT8X6H/2399808320942779.html},
ids = {morgan_travel_2020a},
journaltitle = {Environment & Planning B: Planning & Design},
abstract = {'
# Summary. An optional shortened abstract.
summary:},
publisher = {SAGE PublicationsSage UK: London, England},
title = {Travel Flow Aggregation: Nationally Scalable Methods for Interactive and Online Visualisation of Transport Behaviour at the Road Network Level},
url = {https://doi.org/10.1177/2399808320942779}
}
@article{morton_exploring_2017,
abstract = {The London Congestion Charge (LCC) is a transport policy with a precise spatial footprint. As such, its impact on the transport system can be expected to vary over space, providing an opportunity to explore the geographical reach of local transport interventions. This paper assesses whether the exemption of Hybrid Electric Vehicles (HEVs) from the LCC affected the registration rate of these vehicles in Greater London and the surrounding areas. The analysis uses official data on the number of HEVs registered across the local authorities of the United Kingdom. This dataset is assessed using [1] exploratory spatial analysis to determine the degree of spatial variation in HEV registrations, [2] area classifications to consider if HEV registrations diminish as nearness to the LCC recedes, and [3] spatial regression models to evaluate the association between distance to the LCC and HEV registrations, controlling for other area characteristics (i.e. socioeconomic, household, and transport system variables). The results clearly show that nearness to the LCC is positively associated with HEV registrations, implying that this form of transport policy is effective at promoting the adoption of low emission vehicles.},
author = {Morton, Craig and Lovelace, Robin and Anable, Jillian},
date = {2017-11-01},
doi = {10.1016/j.tranpol.2017.08.007},
file = {/home/robin/Zotero/storage/ISFKK8BM/S0967070X1730080X.html},
issn = {0967-070X},
issue = {Supplement C},
journaltitle = {Transport Policy},
keywords = {Congestion charging,Hybrid Electric Vehicle demand,Local transport policy,Spatial diffusion},
pages = {34--46},
shortjournal = {Transport Policy},
shorttitle = {Exploring the Effect of Local Transport Policies on the Adoption of Low Emission Vehicles},
title = {Exploring the Effect of Local Transport Policies on the Adoption of Low Emission Vehicles: Evidence from the London Congestion Charge and Hybrid Electric Vehicles},
url = {http://www.sciencedirect.com/science/article/pii/S0967070X1730080X},
urldate = {2017-10-11},
volume = {60}
}
@article{morton_fuel_2018a,
abstract = {Car fleets across much of Europe have undergone a process of dieselisation over the past 20\,years. Understanding the factors driving this process is therefore important for sustainable transport policy, with implications for how governments steer their national car fleets towards ultra-low emission vehicles in the future. At a general level, this paper contributes to this wider body of work which aims to understand the factors which led to the transition from petrol to diesel. Specifically, the paper investigates whether the availability of relatively cheap diesel fuel in the Republic of Ireland affected the rate of diesel car ownership in Northern Ireland. A geographic approach is used, which involves generating spatial variables measuring nearness to the Republic of Ireland and comparing these with the proportion of the local car stock that is fuelled by diesel. A series of spatial regression models are specified to determine if this association between nearness to the Republic and diesel ownership persists after accounting for the effect of socioeconomic, travel, and household characteristics. The results support the hypothesis that the availability of cheaper fuel in the Republic of Ireland is not only generating fuel-tourism, but is also affecting the structure of the car fleet registered in Northern Ireland. The findings are relevant beyond the case study and imply that the structure of a country’s car fleet is not only dependent on domestic policies, but is also affected by the policies of neighbouring countries.},
author = {Morton, Craig and Lovelace, Robin and Philips, Ian and Anable, Jillian},
date = {2018-08-01},
doi = {10.1016/j.trd.2018.07.008},
file = {/home/robin/Zotero/storage/TFJFYJCG/Morton et al. - 2018 - Fuel price differentials and car ownership A spat.pdf;/home/robin/Zotero/storage/I6ET48E4/S1361920918303468.html},
issn = {1361-9209},
journaltitle = {Transportation Research Part D: Transport and Environment},
keywords = {Car ownership,Diesel,Fuel tourism,Spatial arbitrage,Vehicle stock model},
pages = {755--768},
shortjournal = {Transportation Research Part D: Transport and Environment},