Travel Behaviour and Society最新文献_第3页

Assessing the impact of walkability indicators on health outcomes using machine learning algorithms: A case study of Michigan 使用机器学习算法评估可步行性指标对健康结果的影响：密歇根州的案例研究

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-01-06 DOI: 10.1016/j.tbs.2025.100983

Musab Wedyan, Fatemeh Saeidi-Rizi

Urban planning and public health are increasingly interlinked in efforts to shape healthier communities. To build a healthier community, walkability has shown positive outcomes for population health. This study employs machine learning to analyze the impact of walkability indicators such as intersection density, proximity to transit stops, employment mix, and employment and household mix and social vulnerability factors on health outcomes in Michigan. Data from the Environmental Protection Agency (EPA) and Centers for Disease Control and Prevention (CDC) were used to evaluate health outcomes including obesity, blood pressure, cholesterol, and depression. The analysis also incorporated the Social Vulnerability Index (SVI) to examine the influence of socioeconomic and demographic factors. Different supervised machine-learning algorithms were applied to assess these relationships. Among the algorithms, the Random Forest algorithm showed the best performance. The results indicate that there is a variation in the impact of walkability indicators on health outcomes. Key findings reveal that among walkabiltity indicators, intersection density is the most significant predictor of all health outcomes, while the other indicators have less impact. In addition, it was found that variables such as Socioeconomic Status, Household Composition & Disability, Minority Status, Housing Type and Transportation have also impact of health outcomes. In conclusion, this research shows the relationship between walkability and human health by providing an evidence-based guidance for building healthier, more walkable communities.

在塑造更健康社区的努力中，城市规划和公共卫生日益相互关联。为了建立一个更健康的社区，可步行性对人口健康产生了积极的影响。本研究采用机器学习来分析密歇根州的步行指标，如十字路口密度、靠近公交站点、就业组合、就业和家庭组合以及社会脆弱性因素对健康结果的影响。来自环境保护署（EPA）和疾病控制与预防中心（CDC）的数据被用来评估健康结果，包括肥胖、血压、胆固醇和抑郁。该分析还纳入了社会脆弱性指数（SVI），以检查社会经济和人口因素的影响。不同的监督机器学习算法被应用于评估这些关系。其中，随机森林算法表现出最好的性能。结果表明，可步行性指标对健康结果的影响存在差异。主要研究结果表明，在可步行性指标中，交叉口密度是所有健康结果的最显著预测因子，而其他指标的影响较小。此外，研究还发现，社会经济地位、家庭构成等变量；残疾、少数民族身份、住房类型和交通也对健康结果产生影响。总之，本研究通过为建设更健康、更适宜步行的社区提供循证指导，揭示了步行性与人类健康之间的关系。

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引用次数: 0

Identifying low-to-middle-income residents’ secondary activity patterns using smart card data

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-01-02 DOI: 10.1016/j.tbs.2024.100977

Ziyan Zhao , Meihan Jin , Mei-Po Kawn , Qingfeng Zhou , Yongxi Gong , Yu Liu

The enrichment of urban lifestyles necessitates a comprehensive understanding of individuals’ secondary activity patterns. For low-to-middle-income residents, secondary activities assume a crucial role in understanding their living conditions. Accordingly, this study proposes a method to extract secondary activities from smart card data and to analyze its spatio-temporal patterns. Corroborated by travel survey data, a significant portion of smart card users have low to middle incomes, we contend that the derived patterns effectively represent the living circumstances of low-to-middle-income individuals travel by public transportation. These patterns are characterized from three aspects, e.g., quantity, spatial coverage, and preference based on home and workplace. A case study in Shenzhen, China identifies several meaningful patterns in the secondary activities of the low-to-middle-income groups who travel frequently by public transportation: groups whose activity patterns are occasional and with strong home-workplace constraints, groups with small activity coverages and strong home-workplace constraints, groups with wide activity coverages and weak home-workplace constraints, and groups with multiple activities and weak home-workplace constraints. The case study indicates that the majority of low-to-middle-income groups who frequently use public transportation either have very few secondary activities by public transportation, or are severely constrained by home and workplace. These discoveries have the potential to assist urban planners in enhancing the accessibility of urban amenities for low-to-middle-income residents, thereby enhancing both the quantitative and qualitative aspects of their secondary activities.

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引用次数: 0

Using a Simulation and Optimisation decision support tool to evaluate impacts of an intermodal travel management system combining ride-pooling and public transport 使用模拟和优化决策支持工具来评估拼车和公共交通相结合的多式联运旅行管理系统的影响

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-01-01 DOI: 10.1016/j.tbs.2024.100974

Ester Lorente, Esteve Codina, Jaume Barceló

This paper explores using a decision support tool, an already developed and preliminary tested system with highly parameterised Simulation and Optimisation engines. This tool manages the assignment of user requests to an intermodal transport system in which conventional transit transportation modes, buses, subways, railways, and trams, are complemented and coordinated with a ride-pooling service. The main objective of this paper is to evaluate the suitability and sustainability of the intermodal transport system in terms of the reduction of emissions, number of conventional trips, and the policies efficiency depending on variable fleet sizes, detour penalties sensibility and fares. The computational tests have been conducted with a realistic Barcelona Metropolitan Area model. The results indicate a significant reduction in emissions with the implementation of ride-pooling services, both in multimodal and intermodal approaches, contributing to alleviating urban traffic congestion caused by private vehicles. A second contribution is the development and evaluation of a policy for the detour reduction of the services assigned to the requests, resulting in better routes with a smaller increase of the fare for already en-route passengers. Furthermore, the implementation of a variable active fleet policy involving a gradual adjustment of the operating number of vehicles during the start-up and shutdown of the system proves to be beneficial for the company in mitigating the system’s operational costs, especially in periods of lower demand, where maintaining a full-time fleet would incur in unnecessary expenses given the limited number of requests.

本文探讨了使用决策支持工具，一个已经开发和初步测试的系统，具有高度参数化的模拟和优化引擎。该工具管理用户对多式联运系统的请求分配，在多式联运系统中，传统的运输方式，如公共汽车、地铁、铁路和有轨电车，与拼车服务相补充和协调。本文的主要目的是评估多式联运系统在减少排放、常规行程数量和政策效率方面的适用性和可持续性，这取决于不同的车队规模、绕行处罚敏感性和票价。利用巴塞罗那市区的实际模型进行了计算试验。结果表明，在多式联运和多式联运方式中，拼车服务的实施显著减少了排放，有助于缓解私家车造成的城市交通拥堵。第二个贡献是制定和评价了一项政策，以减少分配给请求的服务的绕行，从而为已经在途中的乘客提供更好的路线，费用增加较少。此外，在系统启动和关闭期间逐步调整车辆运行数量的可变主动车队政策的实施，对公司减轻系统的运营成本是有益的，特别是在需求较低的时期，在有限的请求数量下，维持一个全职车队会招致不必要的费用。

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引用次数: 0

Text as data: Narrative mining of non-collision injury incidents on public buses by structural topic modeling 以文本为数据：基于结构主题建模的公交非碰撞伤害事件叙事挖掘

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-31 DOI: 10.1016/j.tbs.2024.100981

Pengpeng Xu , Qianfang Wang , Yun Ye , S.C. Wong , Hanchu Zhou

Introduction

Although numerous studies have investigated collisions involving public buses, there has been inadequate research on passenger injuries caused by non-collision incidents on public buses. One major obstacle is that the manual extraction of thematic information from massive document repositories is exceedingly labor intensive, cumbersome, and inaccurate. Our study thereby illustrated how to automatically characterize non-collision injury incidents on public buses by fusing advanced language processing techniques and large-scale incident reports.

Methods

Based on the 12,823 textural narratives recorded by police during 2010–2019 in Hong Kong, the structural topic modeling was developed to uncover underlying themes, quantify topic prevalence, and portray complex interconnectedness.

Results

Thirty-three topics were successfully labeled, with the topic stand and lost balance being the most prevalent. Non-collisions were more likely to result in serious consequences when incidents occurred because the bus skidded, when a passenger was boarding, and when a standing passenger lost the balance. Six unique patterns were uncovered, i.e., the failure to hold handrails accompanied by inappropriate behaviors of bus drivers when approaching bus stations, loss of balance among standing passengers due to the sharp braking of bus drivers in response to red traffic lights ahead, alighting passengers being hit by the door, passengers falling while climbing staircases, passengers being injured because of bus driver’s emergency maneuvers to avoid collisions with nearside pedestrians, and passengers being injured due to the careless lane-changing of bus drivers when weaving through roundabouts.

Conclusions

By leveraging the emerging text mining techniques, unstructured narratives written by the police can provide valuable and organized information for regular injury surveillance. Tailor-made countermeasures were proposed to prevent non-collision injury incidents on public buses.

虽然有许多研究调查了涉及公共汽车的碰撞事故，但对公共汽车非碰撞事故造成的乘客伤害的研究还不够。一个主要的障碍是，从大量文档存储库中手动提取主题信息非常费力、麻烦且不准确。因此，我们的研究说明了如何通过融合先进的语言处理技术和大规模事件报告来自动描述公共汽车非碰撞伤害事件。

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引用次数: 0

Active travel and socioeconomic segregation in Temuco, Chile: The association of personal factors and perceived built environment 智利特穆科的积极旅行和社会经济隔离：个人因素和感知建筑环境的关联

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-25 DOI: 10.1016/j.tbs.2024.100980

Mohammad Paydar , Asal Kamani Fard

Improvement of active travel would contribute to enhancing the minimum rate of physical activity; thus improving public health. Although the importance of social and built environmental variables in promoting active travel has been highlighted, there have been few studies on how both domains simultaneously affect active travel. The impact of socioeconomic status (SES) on the relationships between active travel and its contributing features was also highlighted in the relevant studies. In this sense, compared to low SES neighborhoods (NLSES), the high SES neighborhoods (NHSES) have a far superior infrastructure for active transport. This study aims to examine the associations between active travel and the factors that influence it using data from two different neighborhood types, namely NLSES and NHSES in Temuco, a medium-sized southern city in Chile. The objectives were examined using a questionnaire, two types of regression analysis, and an open-ended question. The results of the qualitative approach showed that personal insecurity is the most significant barrier to walking in NLSES. In addition, the results of the quantitative approach demonstrated the associations of several socio-demographic, personal, social, and built environmental factors with active travel in both NLSES and NHSES, including monthly income, access to a bicycle, attitude toward walking, specific lifestyles, role models, social cohesion, encouragement, perceived accessibility, and perceived access to bus stations. These findings could be used by urban and transport policymakers of this city to enhance active travel based on each neighbourhood type in this city.

积极出行的改善将有助于提高最低体力活动率；从而改善公众健康。虽然社会和建筑环境变量在促进主动旅行中的重要性已经得到强调，但关于这两个领域如何同时影响主动旅行的研究很少。社会经济地位（SES）对主动出行及其贡献特征之间关系的影响也在相关研究中得到了强调。从这个意义上说，与低SES社区（NLSES）相比，高SES社区（NHSES）拥有更优越的主动交通基础设施。本研究旨在利用智利南部中等城市特木科的两种不同社区类型（即NLSES和NHSES）的数据，研究积极出行与影响因素之间的关系。使用问卷、两种类型的回归分析和一个开放式问题来检查目标。定性分析的结果表明，个人不安全感是NLSES中最显著的行走障碍。此外，定量方法的结果表明，在NLSES和NHSES中，几个社会人口、个人、社会和环境因素与积极出行有关，包括月收入、获得自行车、对步行的态度、特定的生活方式、角色榜样、社会凝聚力、鼓励、感知可达性和感知到公交车站的可达性。这些发现可以被该城市的城市和交通政策制定者用来根据该城市的每个社区类型来增强主动出行。

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引用次数: 0

A latent class dynamic discrete choice model for travel behaviour and scheduling 出行行为与调度的潜在类动态离散选择模型

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-24 DOI: 10.1016/j.tbs.2024.100978

Stephen McCarthy, Daniel Jonsson, Qian Wang, Anders Karlström

In travel behaviour modelling, latent class models are used to represent underlying discrete groupings of behavioural preferences. The paper presents a latent class extension of a dynamic discrete choice model (DDCM) and applies the model to the problem of activity demand generation and scheduling. The DDCM is a recursive multinomial logit model where agents make sequential decisions in time, maximizing the expected future utility of their decisions in a random utility maximization framework. It generates activities and their associated travel within a full day schedule, endogenously respecting agents’ inherent time-space constraints. The latent class DDCM builds on the base model by representing heterogeneous lifestyle preferences. A specification of the model is estimated on a Stockholm travel survey and uses age, income level, gender, car ownership and presence of children in the household as classifying variables. The models result in classes which primarily represent modality styles, finding car-, transit- and bike-primary behavioural groups as well as a multimodal group, each linked with different socio-demographic characteristics. The models improve over non-latent class reference models and provide insight into the structure of heterogeneity in travel behaviour preferences in Stockholm.

在旅行行为建模中，潜在类别模型用于表示行为偏好的潜在离散分组。提出了动态离散选择模型（DDCM）的潜在类扩展，并将该模型应用于活动需求生成和调度问题。DDCM是一个递归多项式逻辑模型，其中代理及时做出顺序决策，在随机效用最大化框架中最大化其决策的预期未来效用。它在一整天的时间表内生成活动及其相关的旅行，内生地尊重代理固有的时间空间约束。潜在类DDCM通过表示异质生活方式偏好建立在基本模型的基础上。该模型的规格是根据斯德哥尔摩旅行调查估计的，并使用年龄、收入水平、性别、汽车所有权和家庭中是否有儿童作为分类变量。这些模型产生了主要代表交通方式风格的类别，找到了以汽车、交通和自行车为主要行为方式的群体，以及一个多模式群体，每个群体都与不同的社会人口特征相关联。该模型对非潜在阶层参考模型进行了改进，并提供了对斯德哥尔摩旅游行为偏好异质性结构的洞察。

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引用次数: 0

What type of person is at different stages of change for cycling? A case study of Montreal 什么样的人处于不同的骑车变化阶段？以蒙特利尔为例

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-23 DOI: 10.1016/j.tbs.2024.100969

Zahra Zarabi , Jérôme Laviolette , Owen Waygood , Kevin Manaugh

Promoting cycling for daily transport has significant health, equity, and environmental benefits. To understand what factors influence individuals’ cycling motivational stages, our study pursued two main objectives: 1) Enhancing the Stage Model of Self-Regulated Behavioral Change (SSBC) by integrating it with the psychological mechanisms of the TPB, and 2) Examining the impacts of perceived cycling motivators and barriers, cycling and general attitudes, and sociodemographics on cycling motivational stage. Using an online survey of the adult population (n = 1055) in Montreal, Canada, a multivariate analysis reveals meaningful connections between behaviour stages and perceived barriers and attitudes toward cycling. Those in the lowest stage exhibit lower internal motivation and express concerns about the lack of convenience, physical effort, and slowness associated with cycling. Furthermore, the results challenge the common understanding that people always progress through the stages with increasingly positive attitudes and more cycling. Specifically, our findings highlight the need to distinguish between people who cycle by choice and those who do so out of necessity (i.e., captive riders) when categorizing travelers into action and post-action stages. This is important due to the risk of people in the “captive action stage” going back to using cars if barriers are reduced. This suggests that intervention policies should also focus on current cyclists, not just non-cyclists of the preaction stages. This nuanced understanding can inform more effective and targeted interventions for promoting cycling. Finally, objective characteristics of cycling infrastructure retains significance in explaining who belongs to the postaction stage for cycling, even after controlling for residential self-selection.

提倡骑自行车作为日常交通方式具有显著的健康、公平和环境效益。为了了解影响个体骑行动机阶段的因素，本研究的主要目的有两个：1)通过整合自我调节行为改变阶段模型（SSBC）与TPB的心理机制，完善SSBC阶段模型；2)考察感知的骑行动机和障碍、骑行和一般态度以及社会人口统计学对骑行动机阶段的影响。通过对加拿大蒙特利尔成年人（n = 1055）的在线调查，一项多变量分析揭示了行为阶段与感知障碍和对自行车的态度之间有意义的联系。那些处于最低阶段的人表现出较低的内在动力，并对骑车缺乏便利、体力消耗和速度慢表示担忧。此外，研究结果挑战了人们的共识，即人们总是以越来越积极的态度和更多的骑行在各个阶段取得进步。具体来说，我们的研究结果强调，在将旅行者分为行动阶段和行动后阶段时，有必要区分自愿骑车的人和非自愿骑车的人（即“俘虏骑手”）。这一点很重要，因为如果障碍减少，处于“俘虏行动阶段”的人们可能会重新使用汽车。这表明干预政策也应该关注当前的骑自行车者，而不仅仅是预防阶段的非骑自行车者。这种微妙的理解可以为促进骑自行车提供更有效和有针对性的干预措施。最后，即使在控制了居民自我选择之后，自行车基础设施的客观特征对于解释谁属于自行车的后行动阶段仍然具有重要意义。

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引用次数: 0

Exploring the relationships among life satisfaction, neighborhood satisfaction and travel satisfaction in Beijing

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-21 DOI: 10.1016/j.tbs.2024.100979

Jingwen Rao , Haiqing Lin , Jing Ma , Yanwei Chai

Life satisfaction (LS) is considered a key objective in improving quality of life and is connected to many satisfaction domains. However, few studies have investigated the bidirectional relationships between satisfaction in various domains and LS based on the theories of top-down, bottom-up, and horizontal spillover simultaneously. This article argues for more research into how neighborhood satisfaction (NS) and travel satisfaction (TS) influence LS, and vice versa. Based on GPS trajectories and travel diaries of Meiheyuan residents in Beijing, structural equation modeling is employed in this study to analyze the pathways among NS, TS and LS, while controlling for air and noise pollution at different geographic scales. The modeling results indicate that the theories of top-down, bottom-up, and horizontal spillover co-exist in the relationships among TS, NS, and LS. However, the top-down model performs better than the bottom-up model, and TS has a stronger horizontal spillover effect on NS than the opposite direction. The results also reveal that TS mediates the relationship between NS and LS. This study develops a comprehensive conceptual framework for long-term satisfaction and momentary wellbeing.

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引用次数: 0

How do static and dynamic commute characteristics shape commuting satisfaction? 静态和动态通勤特征如何影响通勤满意度？

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-16 DOI: 10.1016/j.tbs.2024.100973

Richa Maheshwari , Dick Ettema

Despite the significant role that life events such as a change of residence or workplace have on travel behaviour in general and commute trips in particular, little attention has been paid to the effects of changes in commute characteristics on commuting satisfaction (CS). This study focuses on changes in commute characteristics due to changes in workplace location, distinguishing between voluntary and involuntary change. Using data from a large scale online retrospective survey, the findings reveal that dynamic variables such as changes in commuting mode, changes in commute time and changes in workplace location may be more important than static variables such as current commuting mode, current commute time, and current travel attitudes, as they explain a larger proportion of the variation in CS than static variables, at least shortly after the change of workplace location. Most importantly, individuals seem to be more satisfied with their commute after a voluntary workplace relocation than those who changed workplaces involuntarily. However, the question of how lasting this effect of a workplace relocation on CS is and whether CS changes over time as people become accustomed to the changed environment (treadmill effect) is open for future research.

尽管生活事件（如居住地或工作场所的变化）对旅行行为，特别是通勤旅行具有重要作用，但很少有人关注通勤特征变化对通勤满意度的影响。本研究的重点是由于工作地点的变化而导致的通勤特征的变化，并区分了自愿和非自愿的变化。利用大规模在线回顾性调查的数据，研究结果显示，动态变量（如通勤模式的变化、通勤时间的变化和工作地点的变化）可能比静态变量（如当前通勤模式、当前通勤时间和当前旅行态度）更重要，因为它们比静态变量（至少在工作地点改变后不久）解释了更大比例的CS变化。最重要的是，与非自愿换工作场所的人相比，自愿换工作场所的人似乎对自己的通勤更满意。然而，工作场所搬迁对CS的影响有多持久，以及CS是否会随着人们适应变化的环境而改变（跑步机效应），这一问题有待于未来的研究。

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引用次数: 0

What Drives the Use of Pooled Autonomous Vehicles? Some Insights in California Users’ Perspective 是什么推动了共享自动驾驶汽车的使用？加州用户视角下的一些见解

IF 5.1 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2024-12-16 DOI: 10.1016/j.tbs.2024.100975

Md. Mokhlesur Rahman , Jean-Claude Thill

The study investigates people’s perceptions of Pooled Autonomous Vehicles (PAVs) and the key determinants of household intentions to use them using a structural equation modeling framework. The analysis serves to test the validity of a comprehensive conceptual model. Data were sourced from the 2019 California Vehicle survey to estimate the complex association between dependent and independent variables via mediators. Results indicate that higher educational attainment, income, labor force participation, Asian population origin, and urban living are negatively associated with PAVs, and conversely for young and working-age adults. People who prefer public transportation, car-sharing, ride-hailing, and ride-sharing services would be more likely to use PAVs. The perceived usefulness, enjoyment, safety associated with Autonomous Vehicles (AVs) and prior knowledge of AVs significantly influence people to use PAVs, while the enjoyment of driving and the fear of losing control of vehicles are dissuasive factors. The study concludes that people’s travel behaviors, positive attitude to shared mobility, and psychological features of AVs are the key determinants of PAVs.

该研究使用结构方程建模框架调查了人们对拼车自动驾驶汽车（pav）的看法，以及家庭使用pav意愿的关键决定因素。分析有助于检验一个综合概念模型的有效性。数据来自2019年加州汽车调查，通过中介估计因变量和自变量之间的复杂关联。结果表明，较高的受教育程度、收入、劳动力参与、亚洲人口来源和城市生活与paas呈负相关，而对于年轻人和工作年龄的成年人则相反。喜欢公共交通、汽车共享、乘车服务和乘车共享服务的人更有可能使用pav。与自动驾驶汽车（AVs）相关的感知有用性、享受性、安全性以及对自动驾驶汽车的先验知识显著影响人们使用自动驾驶汽车，而驾驶的享受和对车辆失去控制的恐惧是劝阻因素。研究认为，人们的出行行为、对共享出行的积极态度以及自动驾驶汽车的心理特征是自动驾驶汽车的关键决定因素。

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引用次数: 0