Bicycle Network Research Articles

A Spatial-Temporal Aggregated Graph Neural Network for Docked Bike-Sharing Demand Forecasting

Predicting the number of rented and returned bikes at each station is crucial for operators to proactively manage shared bike relocation. Although existing research has proposed spatial-temporal prediction models that significantly advance traffic prediction, these models often neglect the unique characteristics of shared bike systems (BSS). Spatially, the entire bike-sharing system (BSS) experiences peak activity during morning and evening rush hours, whereas, during other periods, activity is localized to local stations, with some recording no rides, highlighting the need to distinguish between global and local spatial information across different times. Temporally, the historical riding records for each station exhibit non-stationary patterns, necessitating the analysis of both global trends and local fluctuations. Existing Graph Neural Network (GNN) approaches to predicting shared bike demand primarily capture static spatial-temporal data and fail to account for the dynamic nature of bike flows. Moreover, these studies focus on global spatial-temporal information without considering local nuances, making it challenging to capture spatiotemporal dynamics in fluctuating BSS. To address these challenges, we introduce the Spatial-Temporal Aggregated Graph Neural Network (STAGNN). Our model first constructs a dynamic adjacent matrix to describe the evolving connections between stations, followed by local and global information layers to capture spatial-temporal information from large-scale shared bike networks accurately. Our methodology has been validated through experiments on four real-world datasets, comparing it against benchmark models to demonstrate superior prediction accuracy. Additionally, we conduct extended experiments on four datasets during the morning and evening rush hours, and the results also affirm the efficacy of the STAGNN in enhancing prediction performance.

The effects of built environments on bicycle accidents around bike-sharing program stations using street view images and deep learning techniques: The moderating role of streetscape features

With the global rise of bike-sharing programs (BSP), planners and traffic experts have raised concerns as to whether the rapid growth of BSP ensures cycling safety. Despite numerous studies on built environments encouraging bike usage, there is limited knowledge whether streetscape environments around BSP stations affect bicycle accidents. We address this gap by investigating the relationships between various built environments and bicycle accidents around BSP stations, with a particular focus on the moderating effects of comprehensive streetscapes. Streetscape environments, estimated through semantic segmentation and k-means clustering, were used in two-level negative binomial regression models to clarify how street- and station-level environments affect different types of bicycle accidents. The findings indicate increased crash likelihoods on higher-speed roads, streets with traffic facilities, in proximity to public transportation infrastructure, and specific streetscape types. In particular, streetscape features like green oasis streets and open-sky roadways positively contribute to mitigating the negative effects of traffic facilities, such as bike networks and crosswalks, on cycling safety. This study aids in developing comprehensive strategies and guidelines to retrofit built environments for better traffic safety and thereby promote urban cycling.

An ontology-based approach for harmonizing metrics in bike network evaluations

The urgency to decarbonize the transportation sector has accelerated the adoption of micro-mobility solutions, with cycling network development witnessing remarkable growth. Robust and quantitative evaluation frameworks are needed to evaluate the quality of such developments. While a plethora of bike network evaluation approaches exist, their diversity creates issues of interpretability and comparability due to varying metrics and domain-specific terms. We present three contributions to address these challenges. First, we construct a formal ontology, VeloNEMO, that captures key attributes of evaluation metrics for harmonizing bike network evaluation metrics. Second, we generate a machine-readable knowledge base containing these metrics, enabling meta-analyses and resolving some of the existing terminological discrepancies. Third, we propose recommendations for transparent and comparable metric descriptions across various evaluation approaches, illustrated by exploratory metric selection scenarios for a forthcoming bike network evaluation tool. In summary, our research addresses the need for a structured and shared vocabulary for bike network evaluations. This ontology-based approach aims to improve the coherence of evaluation methods as the field of bike network planning continues to evolve, ultimately supporting decision-making for sustainable transportation planning.

Accessibility to the winter cycling network in Montréal: A transport equity diagnosis

Recent studies have demonstrated the importance of a well-maintained and safe bicycle network to increase winter cycling. However, inequities in the access to cycling infrastructure in winter have not been documented yet. Based on the concept of equity in transport, this research aims to fill the gap and assess whether inequities are exacerbated during winter in the city of Montréal, Canada. The distance to the nearest cycling network section and kilometres of cycling network with 2.5 km and 5 km were computed in GIS. Two types of statistical analysis were then conducted to assess potential inequities for four population groups: weighted t-tests and seemingly unrelated regression (SUR) models. Our results demonstrate that the winter cycling network is more concentrated in central neighbourhoods and that accessibility issues are increasing in winter. Visible minorities face the most lack of accessibility, compared to the rest of the population. People under the age of 15 and over the age of 65 years old are also in unequal situations, while the low-income population has better access to winter cycling infrastructure than other groups. Our results innovate by incorporating measures of accessibility to the winter cycling network into the assessment of transport inequities.

Riding smooth: A cost-benefit assessment of surface quality on Copenhagen’s bicycle network

A growing body of research acknowledges the substantial societal benefits of improved bicycle infrastructure, with recent studies highlighting the significant impact of road surface quality on comfort, safety, and accessibility of cycling. In this paper, we present a cost-benefit assessment of improved surface quality for the City of Copenhagen. The study focuses solely on improved accessibility through higher travel speed, where two large-scale crowdsourced bicycle trajectory datasets from Copenhagen are used, along with link-specific data for the network. It is found that travel time savings that result from investments in better surface, render a benefit-cost ratio of 2 to 4 and correspond to an absolute yearly recurrent welfare gain of around 20 mill. DKK for Copenhagen. Hence, from a societal welfare perspective, careful monitoring and maintenance of surface quality is indeed a good investment. It is also demonstrated that such monitoring can be achieved in a cost-effective manner by equipping cyclists who travel in a specific area with affordable accelerometer sensors.

Building CapaCITY/É for sustainable transportation: protocol for an implementation science research program in healthy cities

IntroductionImproving sustainable transportation options will help cities tackle growing challenges related to population health, congestion, climate change and inequity. Interventions supporting active transportation face many practical and political hurdles. Implementation...

How Good Is Open Bicycle Network Data? A Countrywide Case Study of Denmark

Cycling is a key ingredient for a sustainability shift of Denmark's transportation system. To increase cycling rates, better bicycle infrastructure networks are required. Planning such networks requires high‐quality infrastructure data, yet the quality of bicycle infrastructure data is understudied. Here, we compare the two largest open data sets on dedicated bicycle infrastructure in Denmark, OpenStreetMap (OSM) and GeoDanmark, in a countrywide data quality assessment, asking whether the data are good enough for network‐based analysis of cycling conditions. We find that neither of the data sets is of sufficient quality, and that data conflation is necessary to obtain a more complete data set. Our analysis of the spatial variation of data quality suggests that rural areas are more prone to incomplete data. We demonstrate that the prevalent method of using infrastructure density as a proxy for data completeness is not suitable for bicycle infrastructure data, and that matching of corresponding features is thus necessary to assess data completeness. Based on our data quality assessment, we recommend strategic mapping efforts toward data completeness, consistent standards to support comparability between different data sources, and increased focus on data topology to ensure high‐quality bicycle network data.

Research on User Data Protection for Electric-driven Bicycle

Under the fast growth of new industries such as the Internet of Things, cloud computing, and artificial intelligence, the shared electric-driven bicycle has proved its great market competitiveness as a product of the era of mobile internet and sharing economy. However, the frequent interaction of large-scale data and the cross-fertilization of massively stored information have exposed a series of problems such as user privacy leakage, data island, imperfect credit systems, etc. For this objective, a data security protection model for shared electric-driven bicycles has been developed. To replace the centralized update mechanism and Blockchain technology, the model uses SM2 and Blockchain identity authentication protocols, decentralized cryptographic storage and multi-factor authentication, asynchronous federated learning mechanism, and distributed end-to-end parameter update mechanism. The experimental results show that the adoption of this data protection model can effectively resist replay attacks and prevent attackers from decrypting user identity information offline. It can also mitigate the risk of parameter leakage caused by centralized servers and establish a secure and trustworthy distributed data sharing mechanism for users of the shared electric-driven bicycle network.

Efficient bicycle networks and expansion strategies


 
 
 This article explains some of the key attributes and factors relating to efficient bicycle networks and their expansion strategies. Varying from a network scale to brief discussion about the streetscape design, many scientific publications are referenced to explain the crucial aspects which must be taken into consideration when planning an attractive cycling network. Modal switch from other transport modes, especially from cars is one of the goals of this cycling promotion. Various methods such as building new bicycle facilities, improving the quality of existing ones and increasing the comfort and safety of the connections were found to improve the attractiveness of cycling in urban context. Additionally, this article analyses the reasons behind cyclists’ route choice as well as the metrics such as connectedness, directedness and coverage which can be used to measure the level of network functionality. Lastly, network growth under limited resources is considered and an equitable distribution of cycleways across the city is found to be important in preventing neighbourhood segregation while not being too far from a utilitarian kind of distribution in terms of return to investment. 
 
 

Comparing different methods for connecting bike lanes to generate a complete bike network and identify potential complete streets in Atlanta

This study compares two different strategies for connecting bike networks – traditional design-based and algorithm-supported – to investigate how their results differ along metrics such as proportion of bike lanes along simulated routes and the resulting cycling stress. The objective is to find optimal strategies for connecting isolated existing cycling infrastructure to form complete networks that improve both active mobility and public transit ridership. By aligning the bike network with transit and activity locations, this research develops an algorithmic framework for generating a skeleton of multimodal networks best suited to become "complete streets." The network generated through an algorithm is compared with a proposed traditionally designed network to determine their relative network performance. The findings suggest that a judicious combination of traditionally designed, and algorithm-supported networks offer better cycling infrastructure than either strategy alone. In addition, algorithms can also be developed to indicate the potential for street segments to be complete streets.

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

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. We conducted a retrospective analysis of household travel survey data and bicycle infrastructure in the Greater Melbourne region, Australia. Seven network metrics were calculated (length of the bicycle network, betweenness centrality, degree centrality, network density, network coverage, intersection density and average weighted slope) and Bayesian spatial models were used to explore associations between these network characteristics and bicycle ridership. 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. These findings challenge the utility of approaches based on spatially modeling network characteristics and bicycle ridership when informing the monitoring and evaluation of bicycle networks. Further efforts are required to be able to quantify network characteristics that reflect the myriad of factors that influence comfort and safety for people of all ages and abilities.

A Street-Specific Analysis of Level of Traffic Stress Trends in Strava Bicycle Ridership and its Implications for Low-Stress Bicycling Routes in Toronto

This study uses Strava bicycling data to investigate network level patterns of bicycle ridership in Toronto, Canada based on Level of Traffic Stress (LTS). We found that most bicycling occurred on a small fraction of the network, with just 10% of all roads and paths accounting for 75% of all bicycle kilometres travelled in 2022. Low-stress routes (LTS 1 and LTS 2) were more popular than high-stress routes for the top 80% most popular streets. The majority of bicycle kilometres travelled (84%) in LTS 2 occurred on routes with no bicycle infrastructure, highlighting the importance of quiet residential streets in forming a low-stress bike network. Despite high-stress conditions, some LTS 3 and LTS 4 streets were heavily used, suggesting infrastructure gaps in Toronto’s bicycle network.

Analysing access to parks and other green spaces on walking, biking, and driving networks through a socioeconomic lens

ABSTRACT Green spaces are important elements of cities due to their benefits to residents’ physical health, mental health and development, and social connections. Residents are more likely to experience green space benefits when they use them frequently and usage increases when amenities are accessible. Because lower-income households often have less reliable access to automobiles, examining access solely on the road network is inadequate. Do households across the socioeconomic spectrum have access to green space on pedestrian and bicycle networks? After estimating residential locations (origins) from U.S. Census data and park and other green space locations (destinations) from the City of Albuquerque data, we connect the two using service area network analyses in a geographic information system (GIS). Findings suggest that overall green space access is a concern since less than 50% of Albuquerque residents have access to a green space within 400 m, indicating levels below those recommended by the World Health Organization. Park accessibility is relatively equally distributed for low-, middle-, and high-income households across both pedestrian and road networks. Access to other green space is a source of possible inequity with high-income households having more than five times the access to non-park green spaces than low-income households. The bike network presents another source of possible inequity as 39% of high-income households have access to the bike network versus only 30% of low-income households and an expansion of the bike network is a primary recommendation for increasing access in an equitable fashion.

ЕКОЛОГІЗАЦІЯ ТРАНСПОРТНОЇ СИСТЕМИ МІСТ УКРАЇНИ

One of the obstacles to the development of ecological transport in Ukraine is the insufficient number of specialized bicycle paths and associated bicycle infrastructure, the insufficient number of electric cars (both cars and trucks), the slow transition of public transport to environmentally friendly means of transportation. Therefore, the further greening of the transport system of Ukrainian cities is a very urgent issue. Therefore, the purpose of this article was to highlight the advantages and justify the urgent need to transfer the foreign experience of sustainable urban mobility and greening of transport to the existing conditions of Ukrainian society. The article discusses priority directions for the development of ecological types of transport, obstacles that stand in the way of greening the transport system of Ukrainian cities, and proposes an action plan aimed at avoiding various types of risks associated with the greening of transport. The relationship between the availability of certain types of transport, the state of the environment and the health of the population is recognized all over the world. It has been proven that it affects the economic indicators of the country’s development. Therefore, European countries calculate the economic effect of expanding the existing bicycle infrastructure based on this relationship. Cities with positive experience in this matter should share their experiences of creating sustainable, comfortable and healthy urban areas, and a single unified action mechanism for promoting such an eco-approach should be developed for decision-makers. Similar transformations are fully available to Ukrainian cities. They are relatively inexpensive. The article proves that in the post-war period it will be necessary to apply a comprehensive approach to the development of sustainable urban mobility (necessarily taking into account the specifics of each city), which should satisfy the needs of the population for high-quality, comfortable, easy and safe movement, complete the integration of the bicycle network into the general transport system of Ukrainian cities.

Prioritizing Areas for Development of an 8,000-mi Bicycle Network throughout the State of Texas

In response to the Texas Bicycle Tourism Trails Act (Texas Transportation Code § 201.9025), the Texas Department of Transportation collaborated with its Bicycle Advisory Committee to investigate the development of a statewide bicycle tourism trails (BTT) network. The conceptual bicycle network is over 8,000 mi long and crosses cultural highlights including historic monuments and national parks throughout Texas. The current bicycle network offers varying levels of service to cyclists and there are substantial gaps in existing bicycle facilities. The development of a statewide BTT network in Texas is envisioned to be a long-term collaborative process built incrementally over many years with many different partners. Geographic information system (GIS)-based visualizations help make the task of planning such a feat easier. High Street Consulting was contracted to develop a visual GIS-based tool that scores segments of the bicycle network based on data-informed criteria pertaining to existing conditions throughout the network. The corridor prioritization tool helps planners select where to target next with regard to developing facilities on the BTT. It allows users to do the following: (a) view planned highway projects and assess where bicycle trail improvements could be coordinated with other construction activities; (b) view parks, historic sites, and other cultural locations in relation to the BTT; (c) upload a locally preferred route; and (d) review reports about cyclist crash history and level of traffic stress for cyclists. The tool is powered by an SQL database in which the data used for scoring are stored and can be updated, and was deployed to a web server using a cluster of Docker containers.

ЗАКОРДОННИЙ ДОСВІД ФОРМУВАННЯ ВЕЛОСИПЕДНОЇ МЕРЕЖІ ТА ЙОГО ВПЛИВ НА СТВОРЕННЯ ВЕЛОЦЕНТРІВ В УКРАЇНІ

In recent years, the number of residents of Ukraine choosing to travel by bicycle has been steadily growing, as has the number of activities held on bicycles, but a significant proportion of the population is still unsure of the possibility of safe bicycle use due to the lack of an appropriate bicycle network, safe conditions of movement and lack of parking in cities and the corresponding infrastructure. In this regard, there is a need to create an extensive bicycle infrastructure in the cities of Ukraine for safe urban mobility, reducing the number of motor vehicles and replacing them with bicycles. This will provide an opportunity to improve the ecology of cities and attract residents to an active and healthy lifestyle and include Ukraine in the global cycling community. Riding a bicycle helps to maintain good physical shape, prolongs life, promotes the production of the "hormone of happiness" and allows you to receive new emotions and an incredible charge of energy every day, gives the opportunity to freely move through city streets (which is especially relevant for residents of megacities). But this requires an appropriate infrastructure, which includes bike lanes, bike parking, bike services, relevant legislation and general municipal support. This study began before the full-scale invasion of Russia and analyzed the situation that developed in peacetime, as well as the development of cities in Ukraine designed for peacetime. The article analyzes the municipal policy of cities in which significant attention is paid to bicycle infrastructure, cycling and objects of this infrastructure are promoted. An attempt was made to formulate the factors that contribute to the emergence of bicycle networks in cities and the functional filling of the bicycle center as one of the important elements of these networks.

Optimizing bike network design: A cost-effective methodology for heterogeneous travel demands using continuous approximation techniques

Optimizing bike network design: A cost-effective methodology for heterogeneous travel demands using continuous approximation techniques

Integrating link count data for enhanced estimation of deterrence functions: A case study of short-term bicycle network interventions

Owing to the lack of demand-related data from interim timespans between consecutive household surveys, it is difficult to assess short-term interventions in the bicycling network and their impact on potential accessibility. In this study, we propose a novel method that incorporates easier and cheaper demand-related data for estimating the parameters of deterrence functions of gravity-based distribution models. In particular, an origin-destination (OD) matrix-updating procedure that uses bicycle count data was incorporated into a two-step line-search algorithm for estimating a two-parameter deterrence function. The method was applied to a case study in the city of São Paulo, where potential accessibility was calculated during the years 2014–2017, which was a period interim to the two most recent household surveys. Three different models were used to estimate the generalized costs of the network links. This method proved useful for capturing accessibility variations over short timespans. Results show how demand is affected by the bicycling network and provide insights into how short-term assessments can benefit decision-making such as providing well-connected and continuous bicycling infrastructure positively influences accessibility. However, they fail as a unique solution apart from land-use policies. Finally, our proposed method can become a valuable tool for decision-making from an accessibility perspective in the short term.

Slope stress criteria as a complement to traffic stress criteria, and impact on high comfort bicycle accessibility

A high-comfort bike network that connects people's homes with their destinations is crucial to attracting more people to cycling. While avoiding high traffic stress is one critical dimension of comfort, another is avoiding steep climbs. In this study, we propose “Steepness Level” criteria that can complement Level of Traffic Stress criteria for evaluating bike networks, drawing from best-practice guidelines and behavioral studies that show tradeoffs cyclists make between steep grades and additional distance. We then apply these criteria to Montreal's bike network, along with Level of Traffic Stress criteria, to determine the impact of considering steepness limitations on bike accessibility. For some situations, adding steepness limitations has a small impact on accessibility while in others, it makes many neighborhoods inaccessible that, based on traffic stress alone, would be considered accessible. And where the topography creates a natural barrier (a ridge) with a single gently sloped corridor passing through, we demonstrate that applying low-traffic-stress treatments in this corridor would increase the fraction of central Montreal that is accessible by bike from 33% to 50%.

Identifying and Modeling the Factors That Affect Bicycle Users’ Satisfaction

The parameters that affect bicyclists’ satisfaction are of vital importance when it comes to determining the reasons that endure bicycle usage in an urban environment. This research refers to the factors that affect bicycle users’ satisfaction with the existing infrastructure in the Municipality of Thessaloniki, Greece. Bicycle dependence in Thessaloniki is relatively limited when it is compared to other European cities with similar topological and demographic characteristics. This article aims to determine the most suitable measures that policymakers should implement to enhance bicycle infrastructure. The data collection process was realized through an online questionnaire survey addressed to the bicycle organizations and groups that are situated in Thessaloniki. Inferential statistical analysis investigated the dependency between the perceived satisfaction and the perceived level of safety of cyclists. Ordinal and multinomial logistic regressions were applied to identify the significant problems that influenced cyclists’ satisfaction, as well as the most important improvement measures suggested by the survey participants. The findings revealed that the lack of safety and urban integration of bicycle infrastructures were the statistically significant issues affecting users’ satisfaction. The development of a safe, integrated, and interconnected bicycle network area emerges as a priority to increase cyclists’ satisfaction and daily bicycle trips in cities with low bicycle culture.