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A copula-based approach for multi-modal demand dependence modeling: Temporal correlation between demand of subway and bike-sharing 基于 copula 的多模式需求相关性建模方法:地铁和共享单车需求之间的时间相关性
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-10-04 DOI: 10.1016/j.tbs.2024.100908
As a representative mode of shared mobility, bike-sharing serves not only as a convenient way to conduct short-distance trips in urban areas, but also as a feeder mode to public transit, forming the Bike and Ride (BnR) system. Conducting management for such a hybrid multi-modal system faces various challenges, including the complex interactions between bike-sharing and other modes, highly dynamic passenger demand, and the difficulty of accessing direct transfer data. To overcome such difficulties, our study proposes a framework for assessing the dependency between the two usage modes. Firstly, a Dynamic-Time-Warping-based (DTW) method is utilized to determine the catchment area (CA) between the two modes, allowing the BnR-related tendency similarity under a given time scale to be considered. Then, the patterns of probabilistic dependence between travel demand of the two modes are obtained by a copula-based approach, which separates correlations under specific usage levels from single modal demands. A case study on the multi-modal system formed by docked bike-sharing and subway in New York is conducted to validate the proposed framework. The tendency similarity is found to be most pronounced within 500 m on average under a 4-hour interval. For each formed station group (SG), the best-fitted copula type is selected, capturing the strong tail correlations present only at specific usage levels. The results show a variety of different correlation patterns within SGs, despite the close geographic locations they may share. Areas of potential transfer resistance between the two modes are identified, which is more evident in first-mile-related (FMR) activities. In contrast, the two modes display more weak connections in last-mile-related (LMR) activities. The obtained results can be utilized by bike-sharing service providers to analyze demand distributions and conduct efficient station-level rebalancing. Compared to previous methods, our proposed framework is computationally inexpensive since no direct transfer of data or complex inference network is required. It incorporates statistically significant spatial–temporal information, allowing for a more accurate determination of the bi-modal assessment range. Moreover, considering that single-mode influences are mathematically removed, the resulting correlation in principle links to the strength of the connections between the two modes. Therefore, it can be assessed as an indicator of the reliability of the multi-modal system.
作为共享交通的代表模式,共享单车不仅是城市地区短途出行的便捷方式,也是公共交通的接驳模式,形成了 "自行车与骑行(BnR)"系统。对这种多模式混合系统进行管理面临着各种挑战,包括共享单车与其他模式之间复杂的相互作用、高度动态的乘客需求以及难以获取直接换乘数据等。为了克服这些困难,我们的研究提出了一个评估两种使用模式之间依赖关系的框架。首先,利用基于动态时间战平(DTW)的方法确定两种模式之间的覆盖区域(CA),从而考虑在给定时间尺度下与 BnR 相关的趋势相似性。然后,通过基于 copula 的方法获得两种模式出行需求之间的概率依赖模式,该方法将特定使用水平下的相关性与单一模式需求分离开来。为了验证所提出的框架,我们对纽约由有桩共享单车和地铁组成的多模式系统进行了案例研究。研究发现,在 4 小时间隔内,平均 500 米范围内的趋势相似性最为明显。对于每个已形成的车站组(SG),选择了拟合效果最好的 copula 类型,以捕捉仅在特定使用水平下出现的强烈尾部相关性。结果显示,尽管 SG 的地理位置相近,但 SG 内部的相关模式却各不相同。两种模式之间存在潜在的转移阻力,这在第一英里相关活动(FMR)中更为明显。相比之下,在与最后一英里(LMR)相关的活动中,两种交通方式的联系更为薄弱。共享单车服务提供商可利用所得结果分析需求分布,并进行有效的站点级再平衡。与以前的方法相比,我们提出的框架计算成本低廉,因为不需要直接传输数据或复杂的推理网络。它结合了具有统计意义的时空信息,可以更准确地确定双模式评估范围。此外,考虑到在数学上剔除了单一模式的影响,由此得出的相关性原则上与两种模式之间的联系强度相关。因此,可以将其作为多模式系统可靠性的指标进行评估。
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引用次数: 0
The relationship between accessibility and land prices: A focus on accessibility to transit in the 15-min city 交通便利性与地价之间的关系:聚焦 15 分钟城市交通可达性
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-28 DOI: 10.1016/j.tbs.2024.100914
In the context of local residents’ travel activities, access to transportation facilities is crucial and a key factor in achieving the goals of a 15-min city. However, current research on accessibility and land prices seldom fully considers the exploration of the relationship between the two using machine learning models. In this study, we conduct an analysis based on land price and accessibility in Beijing. Firstly, factors such as accessibility, population density, land use types, the number of Points of Interest (POI), and housing prices are selected as independent variables for the model, with land price as the dependent variable. Secondly, the CatBoost model is employed to investigate the complex relationship between accessibility to transit and land prices. Finally, the study introduces the XGBoost model and the ordinary least squares (OLS) method for comparison, validating the effectiveness of the CatBoost model in studying the complex relationship between accessibility and land prices through the comparison of model performance evaluation metrics. A clear nonlinear relationship exists between public transportation accessibility and land prices. Accessibility to bus within a 15-min bicycle is positively associated with land price; its trend shows a sharp increase followed by a gradual increase, and then another sharp increase. Accessibility to metro within the multistage distance threshold walk has a roughly positive association with land price within a certain range. While accessibility to bus within a 15-min walk and accessibility to bus within the multistage distance threshold walk have a negative association with land price. The nonlinear patterns between the four accessibility variables and land prices differ and exhibit significant spatial heterogeneity. Both housing prices and population density positively correlate with land prices. Housing prices sharply increase, then gradually, while population density gradually rises, then sharply. This paper explores the relationship between the two, reinforcing research on the mutual influence of public transportation facilities and surrounding environmental elements. It provides a theoretical basis for promoting transit-oriented development (TOD) and city planning.
就当地居民的出行活动而言,交通设施的可达性至关重要,是实现 15 分钟城市目标的关键因素。然而,目前关于交通可达性和地价的研究很少充分考虑使用机器学习模型来探索二者之间的关系。在本研究中,我们基于北京的地价和可达性进行了分析。首先,选取交通可达性、人口密度、土地利用类型、兴趣点(POI)数量和房价等因素作为模型的自变量,地价作为因变量。其次,采用 CatBoost 模型研究交通可达性与地价之间的复杂关系。最后,研究引入了 XGBoost 模型和普通最小二乘法(OLS)进行比较,通过模型性能评价指标的比较,验证了 CatBoost 模型在研究交通可达性与地价之间复杂关系时的有效性。公共交通可达性与地价之间存在明显的非线性关系。单车 15 分钟内的公交可达性与地价呈正相关;其趋势是先急剧上升,然后逐渐上升,最后再次急剧上升。在一定范围内,多级距离临界值步行范围内的地铁可达性与地价大致呈正相关。而 15 分钟步行距离内的公交可达性和多级距离临界步行距离内的公交可达性与地价呈负相关。四个可达性变量与地价之间的非线性模式各不相同,并表现出显著的空间异质性。房价和人口密度都与地价正相关。住房价格先急剧上升,然后逐渐上升,而人口密度则先逐渐上升,然后急剧上升。本文探讨了两者之间的关系,加强了对公共交通设施与周边环境要素相互影响的研究。它为促进公交导向开发(TOD)和城市规划提供了理论依据。
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引用次数: 0
Temporal patterns of user acceptance and recommendation of the automated buses 用户接受和推荐自动驾驶巴士的时间模式
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-26 DOI: 10.1016/j.tbs.2024.100909
To help automated bus services to be competitive in the market, understanding what factors influence the public’s acceptance and adoption of an automated bus service and how these factors change over time is critical. Various factors affect users’ acceptance of this new bus mode, with the quality of service standing out as a significant consideration. Based on pilot demonstrations, some prior studies have explored the factors influencing the user acceptance of new automated vehicle technology based on real-life riding experience. However, these studies are restricted to predicting the adoption of an automated bus by utilising cross-sectional data, but with no data to explore whether public attitudes and acceptance would change over time. To fill the research gap, a longitudinal survey was conducted. Using the panel data, the present study focuses on users with real-world riding experiences on automated buses operated in a mixed-traffic environment on public roads in Stockholm. Contributing to the longitudinal analysis of the public’s acceptance of automated buses, we develop a novel conceptual model integrating the service quality and the technology acceptance model (TAM). A dynamic structural equation model is employed to explore the changes in judging criteria regarding service adoption among adopters and non-adopters. The findings indicate that comfort and convenience are the most significant determinants of satisfaction and the perception of usefulness, which, in turn, positively affect people’s adoption intentions, as well as encouraging favourable word-of-mouth behaviour. It is expected that the provision of faster, safer, more comfortable and convenient riding experiences with automated buses will eventually increase the use of these buses, as well as improve word-of-mouth communication.
为了帮助自动驾驶巴士服务在市场上具有竞争力,了解哪些因素会影响公众对自动驾驶巴士服务的接受和采用,以及这些因素如何随时间推移而变化至关重要。影响用户接受这种新巴士模式的因素有很多,其中服务质量是一个重要的考虑因素。在试点示范的基础上,之前的一些研究根据实际乘车体验探讨了影响用户接受新自动驾驶汽车技术的因素。然而,这些研究仅限于利用横截面数据预测自动驾驶巴士的采用情况,而没有数据探讨公众的态度和接受程度是否会随着时间的推移而发生变化。为了填补这一研究空白,我们开展了一项纵向调查。本研究利用面板数据,重点研究用户在斯德哥尔摩公共道路混合交通环境中乘坐自动驾驶公交车的实际体验。为了对公众对自动驾驶公交车的接受程度进行纵向分析,我们开发了一个新颖的概念模型,将服务质量和技术接受模型(TAM)融为一体。我们采用了一个动态结构方程模型来探讨采用者和非采用者对服务采用的判断标准的变化。研究结果表明,舒适度和便利性是满意度和实用性感知的最重要决定因素,而满意度和实用性感知反过来又会对人们的采用意愿产生积极影响,并鼓励良好的口碑行为。预计自动驾驶公交车提供的更快、更安全、更舒适、更方便的乘车体验最终将提高这些公交车的使用率,并改善口碑传播。
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引用次数: 0
The transformation of mobility in Europe: Technological change and social conditionings 欧洲流动性的转变:技术变革与社会条件
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-25 DOI: 10.1016/j.tbs.2024.100907
The mobility of persons is changing due to technological innovation linked to autonomous and electric vehicles or to connectivity and data communication technologies. Furthermore, it is being conditioned by social behaviours. Qualitative research based on in-depth interviews with experts in mobility from three European countries is used to analyse the main trends that characterize the current transformation of mobility. Results show that the transformation towards the new autonomous, connected, shared and electric mobility is not only driven by technological development, but mainly by social conditionings such as environmental values, behavioural change or adaptability to users’ habits, and socio-demographic features of citizens to adopt servitization. These changes involve different impacts depending on the segment or niche of population, especially in terms of different age groups. The main conclusion of the research is that the new mobility can be considered a social challenge rather than a technological one.
由于与自动驾驶汽车和电动汽车相关的技术创新,或与连接和数据通信技术相关的技术创新,人员的流动性正在发生变化。此外,它还受到社会行为的制约。通过对三个欧洲国家的交通专家进行深入访谈,开展定性研究,分析当前交通变革的主要趋势。研究结果表明,向新型自主、互联、共享和电动交通方式的转变不仅受到技术发展的驱动,而且主要受到社会条件的影响,如环境价值观、行为变化或对用户习惯的适应性,以及公民采用服务化的社会人口特征。这些变化涉及不同的影响,取决于人口的细分或细分群体,特别是不同的年龄组。研究的主要结论是,新的流动性可被视为一种社会挑战,而不是技术挑战。
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引用次数: 0
Ridehailing use, travel patterns and multimodality: A latent-class cluster analysis of one-week GPS-based travel diaries in California 打车软件的使用、出行模式和多模式:对加利福尼亚州基于全球定位系统的一周旅行日记的潜类聚类分析
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-24 DOI: 10.1016/j.tbs.2024.100855
Based on the analysis of one-week GPS-based travel diary data from the four largest metropolitan areas in California, this study performs a latent-class cluster analysis and identifies four distinctive traveler groups with varying levels of multimodality. These groups are characterized by their distinctive use of five travel modes (i.e., single-occupant vehicles, carpooling, public transit, biking, and walking) for both work and non-work trips. Two of these groups are more car-oriented and less multimodal (i.e., drive-alone users and carpoolers), whereas the other two are less car-oriented and display higher levels of multimodality (i.e., transit users and cyclists). Results from this study reveal the unique profiles of each traveler group in terms of their sociodemographic characteristics and built-environment attributes. The study further investigates the different characteristics of each traveler group in relation to ridehailing adoption, trip frequency and trip attributes. Transit users are found to have the highest rate of ridehailing adoption and usage. They are also more prone to use pooled ridehailing services in comparison to other groups. In terms of mode substitution, if ridehailing were not available, respondents tend to choose the mode they use most frequently. In other words, car-based travelers are more likely to substitute ridehailing trips with car trips, whereas non-car-based travelers are more likely to replace ridehailing with less-polluting modes. The findings from this study will prove valuable for transit agencies and policymakers interested in integrating ridehailing with other modes and promoting more multimodal and less car-dependent lifestyles.
本研究基于对加利福尼亚州四大都市区一周 GPS 旅行日记数据的分析,进行了潜类聚类分析,并确定了四个具有不同程度多式联运的独特旅行者群体。这些群体的特点是在工作和非工作出行中使用五种出行方式(即单人乘车、拼车、公共交通、骑自行车和步行)。其中有两个群体更倾向于使用汽车,而较少使用多种出行方式(即自驾车用户和拼车用户),而另外两个群体则不太倾向于使用汽车,但使用多种出行方式的程度较高(即公交用户和骑自行车者)。研究结果揭示了每个旅行者群体在社会人口特征和建筑环境属性方面的独特特征。研究还进一步调查了每个出行群体在采用打车服务、出行频率和出行属性方面的不同特征。研究发现,公交用户采用和使用打车服务的比例最高。与其他群体相比,他们也更倾向于使用集合打车服务。在出行方式替代方面,如果没有打车服务,受访者倾向于选择他们最常使用的出行方式。换句话说,以汽车为出行工具的受访者更倾向于以汽车出行替代打车出行,而非以汽车为出行工具的受访者则更倾向于以污染较少的出行方式替代打车出行。这项研究的结果将对公交机构和有兴趣将打车服务与其他交通方式相结合、促进多式联运和减少对汽车依赖的生活方式的政策制定者很有价值。
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引用次数: 0
Influence of neighborhood walkability on older adults’ walking trips: Does income matter? 社区步行能力对老年人步行出行的影响:收入重要吗?
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-24 DOI: 10.1016/j.tbs.2024.100912
This study examines the links between neighborhood walkability, household income, and older adults’ walking trips. This study mainly utilizes the detailed individual-level data from the 2017 National Household Travel Survey-California Add-on (2017 NHTS-CA). To understand neighborhood walkability and its effects on older adults’ walking trips, we first classify neighborhoods using K-means clustering algorithm based on neighborhood-built environment attributes and access to urban amenities. We then employ negative binomial regression models to analyze the determinants of older adults’ walking trips, with a focus on the effects of household income and neighborhood walkability. Key findings from our empirical analyses are as follows. First, older adults with physical disabilities tend to have fewer walk trips as compared to those without disabilities. Second, subjective health conditions are critical for older adults’ walking trips. Third, increasing household income decreases walking frequency. Fourth, after controlling for various other factors, older adults living in walkable neighborhoods have more frequent walking trips. Fifth, although an increase in household income leads to decreases in older adults’ walking trips, high neighborhood walkability moderates this effect and reduces the adverse effect on walking trip frequencies.
本研究探讨了社区步行能力、家庭收入和老年人步行出行之间的联系。本研究主要利用 2017 年全国家庭出行调查-加州附加项目(2017 NHTS-CA)中详细的个人层面数据。为了解社区步行能力及其对老年人步行出行的影响,我们首先根据社区建设环境属性和城市便利设施的可及性,使用 K-means 聚类算法对社区进行分类。然后,我们采用负二叉回归模型分析老年人步行出行的决定因素,重点关注家庭收入和街区步行能力的影响。实证分析的主要结论如下。首先,与无残疾的老年人相比,有身体残疾的老年人的步行出行次数往往较少。第二,主观健康状况对老年人的步行出行至关重要。第三,家庭收入增加会降低步行频率。第四,在控制了其他各种因素后,居住在步行环境好的社区的老年人的步行出行频率更高。第五,虽然家庭收入的增加会导致老年人步行出行次数的减少,但高步行能力社区会缓和这种影响,减少对步行出行频率的不利影响。
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引用次数: 0
Unveiling mobility patterns beyond home/work activities: A topic modeling approach using transit smart card and land-use data 揭示家庭/工作活动之外的流动模式:利用公交智能卡和土地使用数据的主题建模方法
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-20 DOI: 10.1016/j.tbs.2024.100905

In this paper, a probabilistic topic modeling algorithm called Latent Dirichlet Allocation (LDA) is implemented to infer trip purposes from activity attributes revealed from smart card transit data in an unsupervised manner. While most literature focused on finding patterns for home and work activities, we further investigated non-home and non-work-related activities to detect patterns associated with them. Temporal attributes of activities are extracted from trip information recorded by Tehran subway’s automatic fare collection system. In addition, land-use data is also incorporated to further enhance spatial attributes for non-home/work activities. Various activity attributes such as start time, duration, and frequency in addition to land-use data are used to infer the activity purposes and patterns. We identified 14 different patterns related to non-commuting activities on the basis of both their temporal and spatial attributes including educational, recreational, commercial, and health and other service-related activity types. We investigated passengers’ activity pattern and behavior changes before and during COVID-19 pandemic by comparing the discovered patterns. For recreational patterns it is revealed that not only has the number of recreational patterns dropped, but also the duration of recreational activities decreased. Morning patterns of educational activities have also been eliminated and number of commercial activities was decreased during COVID-19. The proposed model demonstrates the ability to capture travel behavior changes for different disruptions using smart card transit data without performing costly and time consuming manual surveys which can be useful for authorties and decision makers.

本文采用了一种名为潜狄利克特分配(Latent Dirichlet Allocation,LDA)的概率主题建模算法,以无监督的方式从智能卡交通数据中揭示的活动属性推断出行目的。大多数文献都集中于寻找家庭和工作活动的模式,而我们则进一步研究了与家庭和工作无关的活动,以发现与之相关的模式。活动的时间属性是从德黑兰地铁自动收费系统记录的行程信息中提取的。此外,还纳入了土地使用数据,以进一步增强非居家/工作活动的空间属性。除了土地使用数据外,我们还利用开始时间、持续时间和频率等各种活动属性来推断活动目的和模式。根据非通勤活动的时间和空间属性,我们确定了 14 种不同的非通勤活动模式,包括教育、娱乐、商业、健康和其他与服务相关的活动类型。通过比较所发现的活动模式,我们调查了 COVID-19 大流行之前和期间乘客的活动模式和行为变化。在娱乐活动方面,我们发现不仅娱乐活动的数量减少了,而且娱乐活动的持续时间也缩短了。在 COVID-19 期间,上午的教育活动模式也被淘汰,商业活动的数量也有所减少。所提出的模型证明了利用智能卡交通数据捕捉不同干扰情况下的出行行为变化的能力,而无需进行昂贵和耗时的人工调查,这对当局和决策者非常有用。
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引用次数: 0
Post-disaster decision-making framework for roadway networks considering social vulnerability 考虑社会脆弱性的公路网络灾后决策框架
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-20 DOI: 10.1016/j.tbs.2024.100910

Resilience is a characteristic of a system to adapt, resist and recover from disruptions as defined by the U.S. Federal Highway Administration. The concept has been adopted across several fields of research. Existing literature on roadway network resilience typically frames resilience in terms of performance metrics based on the attributes of the network (travel time or travel distance, for example). However, the impact of disruptions to roadway networks varies for different populations within communities because of various socioeconomic factors. While it is important to capture the performance characteristics of transportation networks to ensure goods and services can flow throughout a community, there also lies a need to consider the needs of populations in a community that are more vulnerable to disruptions due to limited mobility. This study aims to propose a framework for roadway network post-disaster recovery planning that considers the needs of socially vulnerable populations. Specific objectives of the study include: i) developing a geographic social vulnerability index (SVI) using census demographic data to quantify the extent to which communities may be considered “socially vulnerable” ii) integrating the index into an actionable decision framework for post-disaster bridge repair strategy and iii) demonstrating how the consideration of social vulnerability can influence network performance. By applying the framework to the Mobile Bay area in Alabama, the significance of including social vulnerability in resilience evaluation becomes evident.

根据美国联邦公路管理局的定义,复原力是一个系统适应、抵御和从中断中恢复的特性。这一概念已被多个研究领域采用。关于公路网络恢复能力的现有文献通常根据网络的属性(例如旅行时间或旅行距离)来确定恢复能力的性能指标。然而,由于各种社会经济因素,道路网络中断对社区内不同人群的影响各不相同。虽然掌握交通网络的性能特征以确保货物和服务能够在整个社区内流动非常重要,但同时也需要考虑社区内因流动性受限而更容易受到交通中断影响的人群的需求。本研究旨在提出一个考虑到社会弱势群体需求的道路网络灾后恢复规划框架。研究的具体目标包括:i) 利用人口普查数据开发地理社会脆弱性指数 (SVI),量化可被视为 "社会脆弱性 "社区的程度;ii) 将该指数纳入灾后桥梁维修战略的可操作决策框架;iii) 展示社会脆弱性的考虑如何影响网络性能。通过将该框架应用于阿拉巴马州的莫比尔湾地区,将社会脆弱性纳入抗灾能力评估的意义就显而易见了。
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引用次数: 0
Assessing bicycle safety risks using emerging mobile sensing data 利用新兴移动传感数据评估自行车安全风险
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-19 DOI: 10.1016/j.tbs.2024.100906

The surge in global electric bicycle ownership has exerted immense pressure on bicycle infrastructure. Theoretically, there’s a need to reassess the risk factors associated with multiple bike lane users. Based on this, there’s a practical need to re-evaluate the safety and quality of outdated infrastructure. This paper aims to reconsider risk factors related to bicycle infrastructure safety in the context of electric bicycles sharing lanes with traditional bicycles. Moreover, many countries lack precise spatial data concerning bicycle infrastructure. This study introduces a mobile sensing method based on bicycles, aiming to acquire daytime and nighttime bike lane datasets in a cost-effective, efficient, and large-scale manner. A computer vision-based bicycle risk factor assessment model was established, and the distribution of bicycle safety risk factors was visually analyzed. Research data was collected from a representative 59.5-kilometer bicycle lane area in Beijing. The results confirm the significant impact of the surge in electric bicycles, with electric bike users accounting for 72.1% of cyclists, 32.3% wearing helmets, and 8.4% riding against traffic. During the day, the highest-ranking risk factors include the type of bicycle lanes (half lacking dedicated lanes or being shared), roadside parking, and subpar road conditions. At night, insufficient street lighting are notable concerns. The research methodology is easily replicable and can be extended to new multi-user coexistence cycling environments or countries without bicycle spatial data, offering insights for bicycle safety policies and road design.

全球电动自行车保有量的激增给自行车基础设施带来了巨大压力。从理论上讲,有必要重新评估与多个自行车道使用者相关的风险因素。在此基础上,实际需要重新评估过时基础设施的安全和质量。本文旨在结合电动自行车与传统自行车共用自行车道的情况,重新考虑与自行车基础设施安全相关的风险因素。此外,许多国家缺乏有关自行车基础设施的精确空间数据。本研究介绍了一种基于自行车的移动传感方法,旨在以低成本、高效率和大规模的方式获取白天和夜间自行车道数据集。建立了基于计算机视觉的自行车风险因素评估模型,并对自行车安全风险因素的分布进行了视觉分析。研究数据采集自北京市具有代表性的 59.5 公里自行车道区域。结果证实了电动自行车激增的重大影响,电动自行车使用者占骑车人的 72.1%,戴头盔的占 32.3%,逆行的占 8.4%。在白天,排名最高的风险因素包括自行车道的类型(半数没有专用车道或共用车道)、路边停车以及路况不佳。夜间,街道照明不足也是值得关注的问题。该研究方法易于复制,可推广到新的多用户共存自行车环境或没有自行车空间数据的国家,为自行车安全政策和道路设计提供启示。
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引用次数: 0
The influence of residential location and public transit options on commuters’ intention to use travel apps for different travel purposes 居住地点和公共交通选择对通勤者为不同出行目的使用旅行应用程序的意向的影响
IF 5.1 2区 工程技术 Q1 TRANSPORTATION Pub Date : 2024-09-19 DOI: 10.1016/j.tbs.2024.100913

While living in city centers is usually linked to higher accessibility levels, shorter travel times, and higher levels of public transit (PT) utilization, the opposite is true for residents of suburban areas. This assumption holds in metropolitan contexts, where central areas offer better accessibility and are associated with higher levels of PT use. In metropolitan peripheries, a large part of commuting is done on an interurban basis, so that the level of use of public transit can be linked to the supply and information available. This work aims to understand the conditions in terms of transit supply and land use, considering the most frequent trip, psychological variables, and the modal choice of commuters’ motorized modes, in the intention to use the new real-time multi-modal travel app, such as advanced traveler information systems (ATIS) for digital mobility-management assistance. A Structural Equation Model is developed to empirically test a sample of 768 respondents collected in two suburban corridors in the Lisbon Metropolitan Area (LMA). Finally, our findings indicate that residential location, mode choice, and trip complexity have a relevant influence on the intention to adopt travel apps. Male students belonging to Generation Y/Z are the most likely users of travel apps. Regardless of the reason, travel patterns associated with more complex (more transfers) and more frequent trips can reinforce the intention to use apps. Also, it is worth noting that students are frequent public transit users, and public transit is also related to trip complexity.

居住在城市中心通常与较高的可达性、较短的旅行时间和较高的公共交通(PT)利用率有关,而郊区居民的情况则恰恰相反。这一假设在大都市中也是成立的,因为在大都市中,中心区域的可达性更好,公共交通的使用率也更高。在大都市周边地区,大部分通勤都是在城际间进行的,因此公共交通的使用水平可以与可用的供应和信息联系起来。这项工作旨在了解公交供应和土地使用方面的条件,考虑最频繁的出行、心理变量以及通勤者对机动车辆的模式选择,以便使用新的实时多模式出行应用程序,如用于数字交通管理辅助的高级旅客信息系统(ATIS)。我们建立了一个结构方程模型,对里斯本大都会区(LMA)两个郊区走廊的 768 个受访者样本进行了实证测试。最后,我们的研究结果表明,居住地点、模式选择和出行复杂性对采用出行应用程序的意向有相关影响。属于 Y/Z 代的男性学生最有可能使用旅行应用程序。无论出于何种原因,与更复杂(更多换乘)和更频繁的旅行相关的旅行模式都会加强使用应用程序的意愿。此外,值得注意的是,学生是公共交通的频繁使用者,而公共交通也与旅行的复杂性有关。
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Travel Behaviour and Society
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