Quantifying changes in bicycle volumes using crowdsourced data

Most cities in the United States lack comprehensive or connected bicycle infrastructure; therefore, inexpensive and easy-to-implement solutions for connecting existing bicycle infrastructure are increasingly being employed. Signage is one of the promising solutions. However, the necessary data for evaluating its effect on cycling ridership is lacking. To overcome this challenge, this study tests the potential of using readily-available crowdsourced data in concert with machine-learning methods to provide insight into signage intervention effectiveness. We do this by assessing a natural experiment to identify the potential effects of adding or replacing signage within existing bicycle infrastructure in 2019 in the city of Omaha, Nebraska. Specifically, we first visually compare cycling traffic changes in 2019 to those from the previous two years (2017–2018) using data extracted from the Strava fitness app. Then, we use a new three-step machine-learning approach to quantify the impact of signage while controlling for weather, demographics, and street characteristics. The steps are as follows: Step 1 (modeling and validation) build and train a model from the available 2017 crowdsourced data (i.e., Strava, Census, and weather) that accurately predicts the cycling traffic data for any street within the study area in 2018; Step 2 (prediction) use the model from Step 1 to predict bicycle traffic in 2019 while assuming new signage was not added; Step 3 (impact evaluation) use the difference in prediction from actual traffic in 2019 as evidence of the likely impact of signage. While our work does not demonstrate causality, it does demonstrate an inexpensive method, using readily-available data, to identify changing trends in bicycling over the same time that new infrastructure investments are being added.

The relationship between bicycle traffic and the development of bicycle infrastructure on the example of Warsaw

The article presents the relationship between the intensity of bicycle traffic volume and the development of bicycle infrastructure on the example of Warsaw. There has been a big increase in cycling over the last decade. At the same time, the linear and point bicycle infrastructure developed very strongly. Similar trends are also observed in other cities in Poland. The article presents the types of infrastructure available to cyclists. Then, the method of assessing the bicycle infrastructure is presented, taking into account the five features of good bicycle infrastructure: cohesion, directness, attractiveness, safety and comfort. In terms of coherence, the analysis covered the bicycle infrastructure network in the vicinity of the measurement site. The directness was tested by checking the accessibility of several dozen of the most important nodal points of the city's communication network. The attractiveness was examined by checking the availability of public bike stations, bicycle racks and bike-sharing stations. The infrastructure adjusted to the technical class of the road was adopted as a measure of safety. The comfort was checked by analyzing the quality of the road surface, which affects the driving comfort and energy expenditure. All the factors presented impact the cyclist's assessment of the infrastructure. To standardize the assessment rules, an aggregate index of the development of bicycle infrastructure was determined. The analysis was carried out for 10 sample points for four consecutive years. The points were characterized by different bicycle infrastructure, location in the city road network and different results of bicycle traffic measurements. The analysis showed a strong positive relationship between traffic and cycling infrastructure for most of the analyzed places. There was a negative dependence in the case of the construction of alternative routes in relation to the place of traffic measurements. The obtained results are the same as in the works of other authors. However, the effects of work do not allow to determine which of the examined factors is the cause and which is the effect but only show the existing relationship.

Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters

To create a safe bicycle infrastructure system, this article develops an intelligent embedded learning system using a combination of deep neural networks. The learning system is used as a case study in the Northumbria region in England’s northeast. It is made up of three components: (a) input data unit, (b) knowledge processing unit, and (c) output unit. It is demonstrated that various infrastructure characteristics influence bikers’ safe interactions, which is used to estimate the riskiest age and gender rider groups. Two accurate prediction models are built, with a male accuracy of 88 per cent and a female accuracy of 95 per cent. The findings concluded that different infrastructures pose varying levels of risk to users of different ages and genders. Certain aspects of the infrastructure are hazardous to all bikers. However, the cyclist’s characteristics determine the level of risk that any infrastructure feature presents. Following validation, the built learning system is interoperable under various scenarios, including current heterogeneous and future semi-autonomous and autonomous transportation systems. The results contribute towards understanding the risk variation of various infrastructure types. The study’s findings will help to improve safety and lead to the construction of a sustainable integrated cycling transportation system.

Designing Maps for Bicycling Simulator Studies – three practical Approaches

Bicycle simulator studies result from attempts of solving various novel problem statements of modern transportation-related research questions. Examples imply the evaluation of novel traffic control strategies for prioritizing urban bicycle traffic, novel bicycle infrastructure (such as bicycle highways) and the interaction and communication of vulnerable road users with automated or autonomous vehicles. As one of classical disciplines of transportation research, namely traffic engineering, and less related to human factors research, automotive research, geography, urban planning or citizen science, we want to point out those bicycle simulator studies design approaches, which are more related to testing novel traffic control strategies for cyclists, experiencing changing traffic-efficiency and –safety-related parameters in ongoing interfaced microscopic traffic flow simulations. We believe that this is a key factor in experiencing various traffic situations and the evaluation of thereof. In this research, we introduce three practical approaches of how to design maps for bicycling simulator studies. This is mainly resulting from manifold practical experiences from already conducted simulator studies beginning from the year 2018.

Movement Patterns of Electric Cargo Bike Commuters – First Insights from Field Experiments and Trajectory Analyses

In addition to and parallel to the SERVUS project, the requirements for a new, agile, urban cargo bicycle with electric drive are identified through a targeted, scientific application potential analysis in the project "E-Cargo Bike - Accompanying Research" described here. These findings are then implemented in the SERVUS project in an agile development and production process. Several prototypes are built in the process. The new e-cargo bicycles should be able to be used both privately and commercially. They will be presented to users for the first time at events (IAA 2021) and rated by them. In addition, the longer-term allocation of the bikes to selected users enables a cross-comparison with existing e-cargo bicycle models. Finally, the substitution potential of journeys in motorized individual transport is estimated and projected using the example of Munich. A key for gathering further information on the abilities of specific electric cargo bike types is tracking experiments with various sensor setups of which the first attempts are presented in this research. Additionally, and by enabling a certain spatial accuracy of gathered GNSS data, we are able to match selected maneuvers of these vehicle types to selected types of the Munich transportation infrastructure. Besides trajectory shapes of maneuvers, we are able to incorporate travel time and delay variations depending on investigation areas and times of the day at selected urban locations for every inspected maneuver (at for examples differing intersection geometries with and without traffic light signals). Another aspect is the presence of bicycle infrastructure and its relation to the option of using mixed traffic modes.

Developing Participatory Analytics Techniques to Inform the Prioritization of Cycling Infrastructure

The planning of bicycle infrastructure across our cities remains is a complex task involving many key stakeholders including the community, who traditionally have had limited involvement in the planning process. This research develops an interactive bicycle prioritisation index tool which includes participatory spatial and textual citizen feedback. The research involves three components. Firstly, a survey of current cyclists in Sydney, their current level of participation, priorities in investment in cycling, and preferred locations for cycling infrastructure. Secondly, it documents the development of an interactive digital bicycle planning tool which is informed through citizen feedback. Thirdly, it evaluates the approach in conversation with potential end-users, including government, planning practitioners, and advocacy group members. The research proposes the combination of multiple passive and active data traces with end-user evaluation to legitimise the citizen co-design of bicycle investment prioritisation initiatives. A case study approach has been taken, focusing on the city of Sydney, Australia. The bicycle planning support system can be used by cities when engaging in cycle prioritisation initiatives, particularly with a focus on integrating citizen feedback and navigating new and complex data landscapes introduced through recent, passively collected big data sets.

Developing urban biking typologies: quantifying the complex interactions of bicycle ridership, bicycle network and built environment characteristics

Background: Extensive research has been conducted exploring associations of built environment characteristics and biking. However, these approaches have often lacked the ability to understanding the interactions of built environment, population and bicycle ridership. To overcome these limitations, this study aimed to develop novel urban biking typologies using unsupervised machine learning methods.Methods: We conducted a retrospective analysis of travel surveys, bicycle infrastructure and population and land use characteristics in the Greater Melbourne region, Australia. To develop the urban biking typology, we used a k-medoids clustering method.Results: Analyses revealed 5 clusters. We highlight areas with high bicycle network density and a high proportion of trips made by bike (Cluster 1; reflecting 12% of the population of Greater Melbourne, but 57% of all bike trips) and areas with high off-road and on-road bicycle network length, but a low proportion of trips made by bike (Cluster 4, reflecting 23% of the population of Greater Melbourne and 13% of all bike trips).Conclusion: Our novel approach to developing an urban biking typology enabled the exploration of the interaction of bicycle ridership, bicycle network, population and land use characteristics. Such approaches are important in advancing our understanding of bicycling behaviour, but further research is required to understand the generalisability of these findings to other settings.

Association between network characteristics and bicycle ridership across a large metropolitan region

Background: Numerous studies have explored associations between bicycle network characteristics and bicycle ridership. However, the majority of these studies have been conducted in inner metropolitan regions and as such, there is limited knowledge on how various characteristics of bicycle networks relate to bicycle trips within and across entire metropolitan regions, and how the size and composition of study regions impact on the association between bicycle network characteristics and bicycle ridership.Methods: We conducted a retrospective analysis of household travel survey data and bicycle infrastructure in the Greater Melbourne region, Australia. Seven network metrics were calculated and Bayesian spatial models were used to explore the association between these network characteristics and bicycle ridership (measured as counts of the number of trips, and the proportion of all trips that were made by bike). Results: We demonstrated that bicycle ridership was associated with several network characteristics, and that these characteristics varied according to the outcome (count of the number of trips made by bike or the proportion of trips made by bike) and the size and characteristics of the study region.Conclusions: These findings challenge the utility of approaches based on spatially modelling network characteristics and bicycle ridership when informing the monitoring and evaluation of bicycle networks. There is a need to progress the science of measuring safe and connected bicycle networks for people of all ages and abilities.

From Cycleway to Urbanism: Planning for Coastal Cycleway

<p>A strategic use of cycling to create liveable and healthier cities is increasingly common in cities across the globe and among forward-thinking urban designers, policy makers or political entities who often improve bicycle infrastructure and install bicycle supporting policies to augment urban cycling (Pucher & Buehler 2012). Yet, cycling can do more than improving urban mobility and health. As pedal-powered vehicles are also means for cultural and artistic expression, subcultural social interaction (Fincham 2007), economic opportunity and urban servicing (Lorenz & Bufton 2011) which is reflected in geographically distinct bicycle cultures (Pelzer 2010). There is an increasing focus on cycle planning by local and regional governments throughout New Zealand. However there is a tendency to design cycle route in isolation, not approaching it as an urbanistic issue. In August 2014, Prime Minister John Key has announced $100 million in new funding that will be made available over the next four years to accelerate cycleways in urban centres. There is strong growth in cycling trails internationally, and in New Zealand there is also strong demand for family based cycling activities and products. Should more cycleways be provided and improved, and if so, how should they be planned? My project will attempt to go beyond the set aims to create more urbanistic approach to cycleway. This research draws upon an idea of the Great Harbour Way (GHW) - Te Aranui o Poneke, initiated by group of walkers and cyclists being a concept to develop and market a 75km shared pedestrian and cycle path around the shoreline of Wellington Harbour. The project aims to promote a walkway and cycleway as an enjoyable and convenient form of travelling around the harbour of Wellington, New Zealand. However, the way it has been conceived, the GHW undermines its possibilities. Our cycling infrastructure needs to evolve not only from transport or engineering perspective but also with architecture perspective to respond to those changing demands on the issues of cycleway planning. This aim of this study is to provide a greater ambition towards GHW by planning orientated research which could increase the numbers, activity of and engagement of cyclists with a particular focus on the Great Harbour Way cycle route. Firstly, the thesis briefly goes over the current status of cycling, addressing the increasing popularity and role of utilitarian cycling in Wellington. Secondly, the study will review and discusses previous cycling planning theories and discuss different models of cycle route planning. In this part, it will also take the project of New Plymouth Coastal Walkway, and Norwegian National Tourist Routes as a case study, discussing the planning strategy of how to implement cycling in our city. The case studies show that the entire visitor experience is important, not just the cycling aspect. This is particularly true for those markets whose primary motivation is not cycling. Accommodation, services, information, scenic values and other activities combine to make the experience more appealing to a broader range of visitors. Thirdly, the thesis proposes a cycling supportive architectural interventions at three different sites and scales to catalyse the GHW project. Last part of the study tried to resolves the complex access problems of the site through integrated planning/landscape architecture thereby creating a usable, functional and adaptable plan for the Wellington to Petone link. Conclusions of the design proposals and future suggestions are included in the last chapter.</p>

From Cycleway to Urbanism: Planning for Coastal Cycleway

<p>A strategic use of cycling to create liveable and healthier cities is increasingly common in cities across the globe and among forward-thinking urban designers, policy makers or political entities who often improve bicycle infrastructure and install bicycle supporting policies to augment urban cycling (Pucher & Buehler 2012). Yet, cycling can do more than improving urban mobility and health. As pedal-powered vehicles are also means for cultural and artistic expression, subcultural social interaction (Fincham 2007), economic opportunity and urban servicing (Lorenz & Bufton 2011) which is reflected in geographically distinct bicycle cultures (Pelzer 2010). There is an increasing focus on cycle planning by local and regional governments throughout New Zealand. However there is a tendency to design cycle route in isolation, not approaching it as an urbanistic issue. In August 2014, Prime Minister John Key has announced $100 million in new funding that will be made available over the next four years to accelerate cycleways in urban centres. There is strong growth in cycling trails internationally, and in New Zealand there is also strong demand for family based cycling activities and products. Should more cycleways be provided and improved, and if so, how should they be planned? My project will attempt to go beyond the set aims to create more urbanistic approach to cycleway. This research draws upon an idea of the Great Harbour Way (GHW) - Te Aranui o Poneke, initiated by group of walkers and cyclists being a concept to develop and market a 75km shared pedestrian and cycle path around the shoreline of Wellington Harbour. The project aims to promote a walkway and cycleway as an enjoyable and convenient form of travelling around the harbour of Wellington, New Zealand. However, the way it has been conceived, the GHW undermines its possibilities. Our cycling infrastructure needs to evolve not only from transport or engineering perspective but also with architecture perspective to respond to those changing demands on the issues of cycleway planning. This aim of this study is to provide a greater ambition towards GHW by planning orientated research which could increase the numbers, activity of and engagement of cyclists with a particular focus on the Great Harbour Way cycle route. Firstly, the thesis briefly goes over the current status of cycling, addressing the increasing popularity and role of utilitarian cycling in Wellington. Secondly, the study will review and discusses previous cycling planning theories and discuss different models of cycle route planning. In this part, it will also take the project of New Plymouth Coastal Walkway, and Norwegian National Tourist Routes as a case study, discussing the planning strategy of how to implement cycling in our city. The case studies show that the entire visitor experience is important, not just the cycling aspect. This is particularly true for those markets whose primary motivation is not cycling. Accommodation, services, information, scenic values and other activities combine to make the experience more appealing to a broader range of visitors. Thirdly, the thesis proposes a cycling supportive architectural interventions at three different sites and scales to catalyse the GHW project. Last part of the study tried to resolves the complex access problems of the site through integrated planning/landscape architecture thereby creating a usable, functional and adaptable plan for the Wellington to Petone link. Conclusions of the design proposals and future suggestions are included in the last chapter.</p>