Correlates of bicycling trip flows in Hamilton, Ontario: fastest, quietest, or balanced routes?

Desjardins, Élise; Higgins, Christopher D.; Scott, Darren M.; Apatu, Emma; Páez, Antonio

doi:10.1007/s11116-021-10197-1

Cited by 16 publications

(9 citation statements)

References 62 publications

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“…Google Maps does not provide such profile options for bicycle routing. In this research we compared CycleStreets' "quietest" and "fastest" modes, and LTS 2 and 4 (Desjardins et al, 2022;Mekuria et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

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Exploring Jittering and Routing Options for Converting Origin-Destination Data Into Route Networks: Towards Accurate Estimates of Movement at the Street Level

Lovelace

Félix

Carlino

2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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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.

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Section: Methodsmentioning

confidence: 99%

“…with the open source cyclestreets R package (Desjardins et al, 2022). • Local knowledge, which was used to visually inspect the resulting networks and identify key 'severance' points in the network (Mindell and Anciaes, 2020).…”

Section: • Estimates Of Quietness Of Links On the Network Computedmentioning

confidence: 99%

Exploring Jittering and Routing Options for Converting Origin-Destination Data Into Route Networks: Towards Accurate Estimates of Movement at the Street Level

Lovelace

Félix

Carlino

2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…We computed three route types for each disaggregated ('jittered') OD pair: 'Fastest', 'Balanced' and 'Quietest', based on the observation that different cyclists have different preferences for route types and the fastest or shortest path may not be the most heavily used 43 . As outlined on the CycleStreets' website, the fastest routes minimize journey time, accounting for traffic lights and surface type.…”

Section: Routingmentioning

confidence: 99%

Cycle Route Uptake and Scenario Estimation (CRUSE): an approach for developing strategic cycle network planning tools

Lovelace,

Talbot,

Vidal-Tortosa

et al. 2024

Preprint

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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, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that has been tested and used by practitioners. Commissioned and used by 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) in addition to using official origin-destination data; 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 and unstructured interviews with stakeholders show that the tool is already being used in practice to inform urban, inter-urban, and rural network planning. The approach is flexible and open-source, allowing the underlying ideas and code to be adapted, supporting effective cycling policies and interventions internationally.

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“…As the paper shows, there are many open source alternatives that offer options not available even a decade ago. Their application, in conjunction with traditional and emerging sources of data, can greatly improve the way we research, teach, and practice transportation planning in the twenty-first century-as recent examples in the literature demonstrate (e.g., Boeing 2021; Desjardins et al 2021).…”

Section: Trends In Tools and Applicationsmentioning

confidence: 99%

Open spatial sciences: an introduction

Páez

2021

J Geogr Syst

Self Cite

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Correlates of bicycling trip flows in Hamilton, Ontario: fastest, quietest, or balanced routes?

Cited by 16 publications

References 62 publications

Exploring Jittering and Routing Options for Converting Origin-Destination Data Into Route Networks: Towards Accurate Estimates of Movement at the Street Level

Exploring Jittering and Routing Options for Converting Origin-Destination Data Into Route Networks: Towards Accurate Estimates of Movement at the Street Level

Cycle Route Uptake and Scenario Estimation (CRUSE): an approach for developing strategic cycle network planning tools

Open spatial sciences: an introduction

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