Journal of Cycling and Micromobility Research最新文献

Multi-operator free-floating GBFS trip destination prediction in public mobility sharing systems 公共交通共享系统中多算子自由浮动GBFS出行目的地预测

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-31 DOI: 10.1016/j.jcmr.2025.100105

Daniel Kerger, Heiner Stuckenschmidt

Public mobility sharing systems are an important component of sustainable transport, particularly for last-mile travel. However, analysing trip patterns using open standards such as GBFS can be challenging due to vehicles frequently being assigned new identifiers and missing GPS trajectories, preventing a detailed tracking. To overcome this limitation, we present a machine learning pipeline that retrospectively predicts trip destinations within this circumstances—making it possible to partially recover travel patterns for GBFS data.

Our approach involves a three-step prediction pipeline: (1) candidate generation and reduction using spatial–temporal filtering; (2) multi-target regression via XGBoost to estimate destination coordinates; and (3) selection of the best-matching candidate. Our approach achieves an average accuracy of 77% across five German and 74% across five international cities within a tolerance of 500 metres. Compared to existing approaches, our method improves prediction accuracy by an average of 20% over methods that also do not use user-specific or GPS trajectory features.

These results demonstrate the feasibility of accurately predicting destinations in shared mobility despite rotating vehicle identifiers and missing trajectory data, thereby supporting improved system analysis and planning.

公共交通共享系统是可持续交通的重要组成部分，特别是对于最后一英里的出行。然而，使用开放标准（如GBFS）分析行驶模式可能具有挑战性，因为车辆经常被分配新的标识符，并且缺少GPS轨迹，从而无法进行详细跟踪。为了克服这一限制，我们提出了一种机器学习管道，可以在这种情况下回顾性地预测旅行目的地，从而可以部分恢复GBFS数据的旅行模式。我们的方法包括一个三步预测流程：(1)使用时空滤波生成和减少候选数据；(2)利用XGBoost进行多目标回归，估计目的地坐标；(3)选择最匹配的候选人。我们的方法在500米的公差范围内，在五个德国城市实现了77%的平均精度，在五个国际城市实现了74%的平均精度。与现有方法相比，我们的方法比不使用用户特定或GPS轨迹特征的方法平均提高了20%的预测精度。这些结果表明，尽管车辆标识符轮换和轨迹数据缺失，但在共享出行中准确预测目的地的可行性，从而支持改进的系统分析和规划。

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引用次数: 0

Cycling rate trends from Canada’s national volunteer cycling count 骑行率趋势来自加拿大全国志愿者骑行统计

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-29 DOI: 10.1016/j.jcmr.2025.100100

Madeleine Bonsma-Fisher , Moreno Zanotto , Kathryn L. Walker , Samuel Benoit , Sara F.L. Kirk , Meghan Winters

Pedal Poll/Sondo Vélo, Canada’s national volunteer bicycle count, completed its fourth count year in 2024. We analyzed this large, crowdsourced dataset of 204,584 people on bikes counted across 64 Canadian communities over four years to examine trends in cycling rates (people on bikes/hour) and their associations with cycling infrastructure type and accessibility to destinations. We classified the infrastructure at count sites according to the Canadian Bikeway Comfort and Safety (Can-BICS) classification system using Google Street View imagery and linked count sites to accessibility to destinations using national Spatial Access Measures (SAM) data. We used generalized linear mixed models to model the relationship between bicycle counts and the count year, count time of day, infrastructure at count sites, and accessibility to destinations, and included random effects for repeated sampling at the same count sites over time. We found that, relative to sites with no cycling infrastructure, medium and high comfort cycling infrastructure was associated with 55% and 105% higher cycling volumes respectively. Similarly, a 1 interquartile (IQR) increase in accessibility to destinations was associated with 65% percent increase in cycling volume. Relative to weekday morning counts, weekdays from 4–6 pm were associated with 53% higher cycling volumes, and weekends from 12–2 pm were associated with 28% higher cycling volumes. We did not see a change in the rate of people cycling over time at sites with medium or high comfort cycling infrastructure, but for the 112 count sessions at sites with low comfort infrastructure, each successive year was associated with a 12% decrease in cycling volume. These findings show that safe, high-comfort cycling infrastructure and accessibility to destinations are both associated with higher rates of cycling, and they highlight the value of a growing volunteer-collected dataset for advancing evidence on cycling in Canada.

加拿大全国志愿自行车统计活动Pedal Poll/Sondo vsamio于2024年完成了第四年的统计。我们分析了这个庞大的、众包的数据集，该数据集包括64个加拿大社区的204,584名骑自行车的人，历时四年，研究了骑车率（每小时骑自行车的人数）的趋势，以及它们与自行车基础设施类型和目的地可达性的关系。我们使用谷歌街景图像，根据加拿大自行车道舒适和安全（Can-BICS）分类系统对计数站点的基础设施进行了分类，并使用国家空间访问措施（SAM）数据将计数站点与目的地的可达性联系起来。我们使用广义线性混合模型来模拟自行车数量与统计年份、一天中的统计时间、统计地点的基础设施和目的地可达性之间的关系，并考虑了在同一统计地点随时间重复抽样的随机效应。我们发现，相对于没有自行车基础设施的地点，中等和高度舒适的自行车基础设施分别增加了55%和105%的骑行量。同样，到达目的地的可达性每增加1个四分位数（IQR），骑行量就会增加65%。与工作日早晨相比，工作日下午4点至6点的骑行量增加53%，周末下午12点至2点的骑行量增加28%。我们没有看到在中等或高度舒适的骑行基础设施中，人们的骑行率随着时间的推移而变化，但在舒适度较低的骑行基础设施中，112次骑行次数与连续每年减少12%有关。这些发现表明，安全、高舒适度的自行车基础设施和前往目的地的可达性都与更高的自行车骑行率有关，它们突出了越来越多的志愿者收集的数据集的价值，这些数据集有助于推进加拿大自行车骑行的证据。

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引用次数: 0

Exploring within-and-between differences in cycling travel time: A comparative study of İstanbul, Braga, and Tallinn 探索骑自行车旅行时间的内与间差异：İstanbul、布拉加和塔林的比较研究

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-22 DOI: 10.1016/j.jcmr.2025.100099

Amani Jaafer, Fariya Sharmeen, Anders Karlström

Responding to climate change and sustainability goals, many cities and countries have renewed efforts to upgrade active transportation infrastructure, such as cycling. Supportive built environment conditions, such as dedicated cycling lanes, safe intersections, and low-traffic streetsare a necessary prerequisite to promote cycling and so is the understanding of behavioral variations in travel, with travel time being particularly crucial. Although travel time and value of travel time has been widely studied in transportation research cycling travel time is less explored, particularly how they vary across cities. Moreover, external factors such as wind speed and bike type (e.g., e-bike vs. conventional bike) can significantly influence cycling travel time. This study addresses these gaps by examining the effects of trip characteristics and socio-demographic factors on cycling travel time across three European cities: Tallinn, Braga, and Istanbulwhich differ in cultural and urban contexts but have each recently initiated policies to foster cycling. Using a Latent Class Accelerated Failure Time (LCAFT) model, the analysis reveals that, as expected, distance consistently increases travel time and e-bikes have low to significant effects. However, the influence of trip purpose and bike type varies depending on socio-demographic and cultural contexts. For instance, in Tallinn and Braga, age and gender significantly shape travel time, whereas in Istanbul, age and educational attainment are more influential. These findings highlight the importance of incorporating contextual and demographic differences when assessing cycling behavior across diverse urban settings.

为应对气候变化和可持续发展目标，许多城市和国家重新努力升级主动交通基础设施，如自行车。支持性的建筑环境条件，如专用的自行车道、安全的十字路口和低流量街道，是促进骑自行车的必要先决条件，对旅行行为变化的理解也是如此，其中旅行时间尤为重要。尽管出行时间和出行时间的价值在交通研究中得到了广泛的研究，但对自行车出行时间的探索却很少，尤其是它们在不同城市之间的差异。此外，风速和自行车类型（如电动自行车与传统自行车）等外部因素会显著影响骑行时间。本研究通过考察塔林、布拉加和伊斯坦布尔三个欧洲城市的出行特征和社会人口因素对骑行时间的影响来解决这些差距，这三个城市的文化和城市背景不同，但最近都出台了促进骑行的政策。利用潜在类加速失效时间（Latent Class Accelerated Failure Time， LCAFT）模型，分析表明，正如预期的那样，距离持续增加了行驶时间，而电动自行车的影响从低到显著。然而，出行目的和自行车类型的影响取决于社会人口和文化背景。例如，在塔林和布拉加，年龄和性别在很大程度上决定了旅行时间，而在伊斯坦布尔，年龄和受教育程度的影响更大。这些发现强调了在评估不同城市环境下的骑车行为时，结合环境和人口差异的重要性。

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引用次数: 0

Validation of a bike simulator for ADAS impact analysis: Road projection communication system with reversing scenario case study 用于ADAS影响分析的自行车模拟器的验证：道路投影通信系统与倒车场景案例研究

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-18 DOI: 10.1016/j.jcmr.2025.100104

Meysam Imanipour, Bertrand Barbedette, Sébastien Saudrais

Cycling is an eco-friendly mode of transportation with social and environmental benefits. However, cyclist fatality rates in Europe have not shown improvement, with most fatalities occurring during car-cyclist interactions. The Communication-Oriented Advanced Driver Assistance System (CO-ADAS) introduces a light-based visual communication, projecting patterns onto the ground to indicate the vehicle's intended movement, enhancing cyclists' anticipation. Evaluating CO-ADAS in on-road experiments is constrained by safety and controllability. Virtual reality (VR) bike simulators offer a safer and controlled alternative, yet the validity of simulator-based evaluation is little discussed, especially for novel interactions like CO-ADAS, which is an unfamiliar interaction type and may elicit surprising effects. This study addresses the validation of simulator-based evaluations for an unfamiliar interaction type (CO-ADAS) and highlights the challenges of simulator validation via statistical analysis. It also emphasizes the importance of video data for action recognition and for capturing complex behavior. To this end, cyclist interactions with the CO-ADAS projection were compared between on-road and VR experiments across three levels: trajectory and speed measurements, cyclists’ reactions, and perception of CO-ADAS. Comparison results showed that while average lateral position differed between experiments, variations in lateral position and average speed showed no significant differences. Reaction comparison via video observation showed higher safety reactions in the on-road experiment, yet both experiments exhibited a consistent increase in safety reactions with CO-ADAS compared to reverse lights alone. Cyclists’ perceptions were also positive across both experiments. Overall, the results support simulator-based evaluation for assessing the safety impact of novel interactions like CO-ADAS on cyclists.

骑自行车是一种生态友好的交通方式，具有社会效益和环境效益。然而，欧洲骑自行车的人的死亡率并没有显示出改善，大多数死亡事件发生在骑汽车的人之间。以通信为导向的高级驾驶辅助系统（CO-ADAS）引入了一种基于光的视觉通信，将模式投射到地面上，指示车辆的预期运动，提高骑自行车者的预期。在道路试验中对CO-ADAS进行评估受到安全性和可控性的制约。虚拟现实（VR）自行车模拟器提供了一种更安全、可控的替代方案，但基于模拟器的评估的有效性却很少被讨论，特别是对于像CO-ADAS这样的新型交互，这是一种不熟悉的交互类型，可能会产生意想不到的效果。本研究针对一种不熟悉的交互类型（CO-ADAS）进行了基于模拟器的评估验证，并强调了通过统计分析进行模拟器验证的挑战。它还强调了视频数据对动作识别和捕捉复杂行为的重要性。为此，在道路和VR实验中，骑车者与CO-ADAS投影的互动在三个层面上进行了比较：轨迹和速度测量、骑车者的反应和对CO-ADAS的感知。对比结果表明，各实验间平均侧位存在差异，但侧位和平均速度变化无显著差异。通过视频观察的反应对比显示，道路实验中的安全反应更高，但两个实验都显示，与单独倒车灯相比，CO-ADAS的安全反应一致增加。在两个实验中，骑自行车的人的看法也都是积极的。总的来说，研究结果支持基于模拟器的评估，以评估CO-ADAS等新型相互作用对骑自行车者的安全影响。

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引用次数: 0

Fast-lane for planning cycling infrastructure: On the effectiveness and efficiency of cycling infrastructure planning processes 自行车基础设施规划的快车道：关于自行车基础设施规划过程的有效性和效率

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-16 DOI: 10.1016/j.jcmr.2025.100103

Arnor Elvarsson , David Zani , Bryan T. Adey

Timely development of cycling infrastructure is essential to achieving societal goals such as decarbonisation and cyclist traffic safety. However, delays in infrastructure project completion persist across many planning contexts, partly due to the infrastructure planning processes. This paper addresses the lack of academic research on infrastructure planning process improvement, specifically for cycling infrastructure, by applying a structured, three-step methodology—process mapping, process analysis and improvement proposal—to the case of Canton Zürich, Switzerland. The paper includes mapping the existing cycling infrastructure planning process, identifying process-related challenges using three decision-making criteria (technical readiness, societal consensus, and political-financial prioritisation), and proposing targeted improvements. Key findings highlight the need for timely planning mandates, early-stage cost overviews, and systematic treatment of uncertainty to enhance planning process efficiency. It is argued that these process modifications can accelerate the realisation of cycling infrastructure projects and improve alignment with long-term strategic goals such as achieving net-zero carbon emissions by 2050. By bridging the gap between planning process design and infrastructure outcomes, this study contributes an approach for analysing and improving planning processes. The findings are relevant for infrastructure planners, policymakers, and researchers seeking to support more effective and efficient cycling infrastructure development.

及时发展自行车基础设施对于实现诸如脱碳和自行车交通安全等社会目标至关重要。然而，在许多规划背景下，基础设施项目完成的延迟仍然存在，部分原因是基础设施规划过程。本文以瑞士z里奇州为例，采用结构化的三步方法——过程映射、过程分析和改进建议，解决了基础设施规划过程改进（特别是循环基础设施）的学术研究不足的问题。本文包括绘制现有的自行车基础设施规划过程，使用三个决策标准（技术准备程度、社会共识和政治财政优先级）确定与过程相关的挑战，并提出有针对性的改进建议。主要调查结果强调了及时规划授权、早期成本概述和系统处理不确定性以提高规划过程效率的必要性。有人认为，这些流程修改可以加速循环基础设施项目的实现，并改善与长期战略目标的一致性，例如到2050年实现净零碳排放。通过弥合规划过程设计和基础设施成果之间的差距，本研究为分析和改进规划过程提供了一种方法。这些发现对于基础设施规划者、政策制定者和研究人员来说是有意义的，他们正在寻求支持更有效和高效的自行车基础设施发展。

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引用次数: 0

Factors steering use behaviour of shared micro-mobility services (SMSs) in Norway: Extended UTAUT 2 with intrinsic motivation 挪威共享微移动服务（sms）使用行为的控制因素：具有内在动机的扩展UTAUT 2

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-13 DOI: 10.1016/j.jcmr.2025.100098

Danielle Teh, Özlem Simsekoglu

Shared micro-mobility services (SMSs), such as shared bikes and shared e-scooters, have emerged as a viable, sustainable transportation option that contribute towards the transition of a more sustainable mobility ecosystem. Both digital and transportation technologies play crucial roles in ensuring the success and adoption of SMSs. Therefore, this study applied the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) to investigate the actual use behaviour of SMSs in Norway. In addition, the study framework included intrinsic motivation from the Self-Determination Theory (SDT) as an exploratory exogenous variable. Age, gender and education level served as control variables. A total of 208 valid responses from both users and non-users of SMSs were gathered via online survey. Results were analysed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. The modelling results indicated that facilitating conditions, social influence, performance expectancy, habit, and intrinsic motivation positively influenced SMS use intention, which subsequently predicted the actual use behaviour of SMSs. Moreover, age was a meaningful control variable while gender and education level did not show any significance. The study also revealed that most users utilised SMSs less than 1 day per week and primarily used them on leisure trips, while the most cited reason for non-use was the lack of safety features. Based on these discoveries, practical recommendations such as improving road infrastructure, enhancing micro-mobility on-road visibility, and further optimising the mobile application may encourage a greater adoption and higher utilisation of SMSs among Norwegians.

共享的微型交通服务（sms），如共享自行车和共享电动滑板车，已经成为一种可行的、可持续的交通选择，有助于向更可持续的交通生态系统过渡。数字和运输技术在确保sms的成功和采用方面发挥着至关重要的作用。因此，本研究采用技术接受和使用统一理论2 （UTAUT 2）来调查挪威短信的实际使用行为。此外，研究框架还将来自自我决定理论（SDT）的内在动机作为探索性外生变量。控制变量为年龄、性别和受教育程度。通过在线调查，共收集了短信用户和非短信用户的208份有效回复。使用偏最小二乘结构方程建模（PLS-SEM）技术对结果进行分析。模型结果表明，便利条件、社会影响、绩效期望、习惯和内在动机正向影响短信使用意愿，进而预测短信实际使用行为。年龄是有意义的控制变量，性别和文化程度无显著性。该研究还显示，大多数用户每周使用短信的时间不到1次 ，主要是在休闲旅行时使用，而不使用短信的最主要原因是缺乏安全功能。基于这些发现，一些实用的建议，如改善道路基础设施，提高微移动在道路上的能见度，以及进一步优化移动应用程序，可能会鼓励挪威人更多地采用和利用短信。

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引用次数: 0

Surveying e-scooter accident risk among teenagers: The case of Norway 调查青少年电动滑板车事故风险：挪威的案例

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-11 DOI: 10.1016/j.jcmr.2025.100101

Siri Hegna Berge, Vibeke Milch Uhlving, Aslak Fyhri

This study investigates accident risks associated with e-scooter use among Norwegian teenagers, focusing on trends over time, gender differences, and the role of e-scooter type. Using data from 21 205 participants aged 12–22 across two survey sets (2021/2022 and 2023), we examined the influence of gender, age, e-scooter ownership, and rental availability on accident risks, applying Generalized Linear Models with a negative binomial distribution. The findings reveal a 22 % increase in the likelihood of reporting injuries and a 57 % increase in injuries requiring medical attention in 2023 compared to 2021/2022. A follow-up survey in 2024 was issued to clarify the timing of earlier accidents, aiming to distinguish between accumulation effects and actual increases in risk. The results indicated that accident accumulation effects from earlier years inflated the reported risk among older teenagers, whereas the rise among 12–15-year-olds appears genuine. Females had a higher overall risk of accidents, while males were more likely to experience severe injuries requiring medical attention. Privately owned e-scooters were consistently associated with a higher risk of accidents than shared e-scooters, with this disparity more pronounced in 2023. While the introduction of stricter regulations, such as helmet mandates, nighttime bans, and alcohol limits, showed a potential trend towards reduced injury severity for shared e-scooters, this effect was not statistically significant. In contrast, the persistent high risk among privately owned e-scooter users and older teenagers highlights the need for additional safety measures. The study’s large sample size strengthens the reliability of the findings and their potential implications for policy and research.

本研究调查了挪威青少年中与电动滑板车使用相关的事故风险，重点关注随着时间的推移，性别差异和电动滑板车类型的作用。研究人员利用两组调查（2021/2022和2023）中21205名年龄在12-22岁之间的参与者的数据，运用负二项分布的广义线性模型，研究了性别、年龄、电动滑板车拥有量和租赁可用性对事故风险的影响。研究结果显示，与2021/2022年相比，2023年报告受伤的可能性增加了22% %，需要医疗护理的受伤增加了57% %。2024年发布了一项后续调查，以澄清早期事故的时间，旨在区分累积效应和实际风险增加。结果表明，早年的事故积累效应夸大了年龄较大的青少年报告的风险，而12 - 15岁青少年的风险上升似乎是真实的。女性发生事故的总体风险更高，而男性更有可能遭受严重伤害，需要就医。与共享电动滑板车相比，私人拥有的电动滑板车发生事故的风险一直更高，这种差距在2023年更为明显。虽然引入了更严格的法规，如头盔要求、夜间禁令和酒精限制，显示了降低共享电动滑板车伤害严重程度的潜在趋势，但这种影响在统计上并不显著。相比之下，私人电动滑板车使用者和年龄较大的青少年中持续存在的高风险突出了采取额外安全措施的必要性。该研究的大样本量加强了研究结果的可靠性及其对政策和研究的潜在影响。

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引用次数: 0

Do minimum passing distance laws for cyclists change driver behaviour? 骑自行车者的最小通过距离法规会改变司机的行为吗？

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-11 DOI: 10.1016/j.jcmr.2025.100102

James Sinclair, Jonathan Nolan

This study investigates the effect of minimum passing distance laws (also called ‘1-metre laws’ or ‘3-foot laws’) on driver behaviour. Passing distances were recorded for 70 cyclists in Perth, Western Australia before and after the introduction of a minimum passing distance law, which coincided with an advertising campaign promoting cyclist safety. The results show only a marginal reduction in the share of passes that were very close to the cyclist on roads with lower speed limits. On these roads, the closest 5% of passes were 10 cm (95% CI [2, 19] cm) further from cyclists after the law and advertising campaign. For higher speed roads, there was no effect. The very small improvement found, limited to slower roads, is considerably smaller than that of other interventions to improve cyclist safety. For instance, protected bicycle lanes have been associated with a 73 cm increase in passing distance — an effect approximately seven times greater than that of the minimum passing distance law.

这项研究调查了最小通过距离法规（也称为“1米法规”或“3英尺法规”）对驾驶员行为的影响。在引入最低通过距离法之前和之后，西澳大利亚州珀斯的70名骑自行车者的通过距离被记录下来，这与宣传骑自行车者安全的广告活动相吻合。研究结果显示，在限速较低的道路上，离骑车人很近的通道所占的比例只有轻微的减少。在这些道路上，经过法律和广告宣传后，最近的5%的通道距离骑自行车的人远了10厘米（95% CI[2,19]厘米）。对于高速公路，没有影响。发现的非常小的改善，仅限于较慢的道路，比其他改善骑自行车者安全的干预措施要小得多。例如，保护自行车道与通过距离增加73厘米有关，其效果大约是最小通过距离法的7倍。

引用次数: 0

Evaluating the effects of data sparsity on the link-level bicycling volume estimation: A Graph Convolutional Neural Network approach 评估数据稀疏度对链路级自行车体积估计的影响：一种图卷积神经网络方法

Journal of Cycling and Micromobility Research

Pub Date : 2025-12-01 DOI: 10.1016/j.jcmr.2025.100086

Mohit Gupta , Debjit Bhowmick , Meead Saberi , Shirui Pan , Ben Beck

Accurate bicycling volume estimation is crucial for making informed decisions and planning about future investments in bicycling infrastructure. However, traditional link-level volume estimation models are effective for motorized traffic but face significant challenges when applied to the bicycling context because of sparse data and the intricate nature of bicycling mobility patterns. To the best of our knowledge, we present the first study to utilize a Graph Convolutional Network (GCN) architecture to model link-level bicycling volumes and systematically investigate the impact of varying levels of data sparsity (0%–99%) on model performance, simulating real-world scenarios. We have leveraged Strava Metro data as the primary source of bicycling counts across 15,933 road segments/links in the City of Melbourne, Australia. To evaluate the effectiveness of the GCN model, we benchmark it against traditional machine learning models – linear regression, support vector machines, and random forest and deep learning models – multilayer perceptron (MLP) and convolutional neural network (CNN). Our results show that the GCN model outperforms these traditional models in predicting Annual Average Daily Bicycle (AADB) counts, demonstrating its ability to capture the spatial dependencies inherent in bicycle traffic network. While GCN remains robust up to 80% sparsity, its performance declines sharply beyond this threshold, highlighting the challenges of extreme data sparsity. These findings underscore the potential of GCNs in enhancing bicycling volume estimation, while also emphasizing the need for further research on methods to improve model resilience under high-sparsity conditions. Our findings offer valuable insights for city planners aiming to improve bicycling infrastructure and promote sustainable transportation.

准确的自行车数量估算对于做出明智的决策和规划未来的自行车基础设施投资至关重要。然而，传统的链路级体积估计模型对机动交通是有效的，但由于数据的稀疏性和自行车出行模式的复杂性，在应用于自行车出行环境时面临着巨大的挑战。据我们所知，我们提出了第一个利用图卷积网络（GCN）架构来建模链路级自行车量的研究，并系统地研究了不同级别的数据稀疏度（0%-99%）对模型性能的影响，模拟了现实世界的场景。我们利用Strava Metro数据作为澳大利亚墨尔本市15,933个路段/连接的自行车数量的主要来源。为了评估GCN模型的有效性，我们将其与传统的机器学习模型——线性回归、支持向量机、随机森林和深度学习模型——多层感知器（MLP）和卷积神经网络（CNN）——进行基准测试。研究结果表明，GCN模型在预测年平均每日自行车（AADB）数量方面优于传统模型，表明其能够捕捉自行车交通网络固有的空间依赖性。虽然GCN在80%的稀疏度下仍然保持健壮性，但超过这个阈值后，其性能急剧下降，突出了极端数据稀疏性的挑战。这些发现强调了GCNs在增强自行车体积估计方面的潜力，同时也强调了需要进一步研究在高稀疏条件下提高模型弹性的方法。我们的研究结果为旨在改善自行车基础设施和促进可持续交通的城市规划者提供了有价值的见解。

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引用次数: 0

Identification of plausible low traffic neighbourhoods using open data 利用开放数据确定可行的低交通流量街区

Journal of Cycling and Micromobility Research

Pub Date : 2025-10-23 DOI: 10.1016/j.jcmr.2025.100097

Chris Larkin , Craig Robson , Alistair Ford

Low Traffic Neighbourhoods (LTNs) form an important component of urban active travel infrastructure and policy in the United Kingdom. These zones aim to prioritise street space for cycling and walking by reducing motorised traffic within the neighbourhood. While the impacts of these zones have been studied at a local scale, research often relies on bespoke datasets provided by local councils, which are frequently unavailable or do not exist for many urban areas. To examine LTNs at a larger scale, there is a need for tools and methods to identify their locations. This study develops an open, data-driven approach to identify and evaluate plausible LTNs for any Local Authority District in the UK, creating the foundations for a national LTN dataset. The methods are applied to Newcastle Upon Tyne to demonstrate the tool. First, we separate the city into neighbourhoods based on areas where people can cycle or walk comfortably before encountering a severance, such as major roads. For each neighbourhood, three metrics are produced using OpenStreetMap data to measure the transport characteristics of the zone: the density of modal filtering, the presence of traffic through-routes, and permeability difference between active modes and vehicle modes passing through a neighbourhood. Across Newcastle, we identify 215 unique neighbourhoods with 339 modal filters. Notably, 55% of neighbourhoods contain no modal filtering, while 66% have traffic through-routes. Permeability differences with neighbourhoods range from 0 m to 4046 m. Metrics are combined to provide an overall LTN plausibility score, which is visualised through automatically generated web map outputs.

低交通街区（ltn）是英国城市主动出行基础设施和政策的重要组成部分。这些区域旨在通过减少社区内的机动交通，优先考虑自行车和步行的街道空间。虽然这些区域的影响已经在地方范围内进行了研究，但研究往往依赖于地方议会提供的定制数据集，而这些数据集往往无法获得，或者在许多城市地区不存在。为了更大规模地检查ltn，需要工具和方法来确定它们的位置。本研究开发了一种开放的、数据驱动的方法来识别和评估英国任何地方政府区的合理LTN，为国家LTN数据集奠定了基础。将这些方法应用于泰恩河畔纽卡斯尔来演示该工具。首先，我们将城市划分为不同的社区，在这些社区中，人们可以舒适地骑自行车或步行，而不会遇到分隔物，比如主要道路。对于每个社区，使用OpenStreetMap数据生成三个指标来衡量该区域的交通特征：模态过滤的密度，通过路线的交通存在，以及通过社区的主动模式和车辆模式之间的渗透率差异。在整个纽卡斯尔，我们用339个模态过滤器确定了215个独特的社区。值得注意的是，55%的社区没有模态过滤，而66%的社区有通道交通。与邻域的渗透率差异在0 ~ 4046 m之间。这些指标结合起来，提供了一个整体的LTN可信度评分，该评分通过自动生成的网络地图输出可视化。

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