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Does built environment have impact on traffic congestion? —A bootstrap mediation analysis on a case study of Melbourne 建筑环境对交通拥堵有影响吗?-对墨尔本案例研究的自举中介分析
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-11-02 DOI: 10.1016/j.tra.2024.104297
Dong Xiao , Inhi Kim , Nan Zheng
While the relationship between built environment, mobility choices and travel productions has been well documented, the impact of built environment on traffic performance, particularly congestion, is not extensively investigated. In existing investigations, the mechanisms by which built environment affects traffic performance-whether direct or indirect-remain unclear. Furthermore, traffic performance is mostly quantified by aggregated and rough performance metrics that fail to capture the operational characteristics of traffic. This study examines both the direct and indirect relationships between built environment and traffic congestion using the macroscopic fundamental diagram (MFD) to connect traffic dynamics with built environment properties. The study hypothesizes that built environment has an indirect impact on congestion and analyzes the possible indirect effects utilizing the bootstrap mediation analysis. Two components, namely the “operational capacity” and “travel demand”, are defined as mediating factors. The analysis is conducted based on data collected from 133 Statistical Area Level 2 (SA2) in the Melbourne region, Australia, including both traffic and built environment data collected from 2019. Results show that “road network connectivity” and “road network structure” can intensify congestion, while “public transit accessibility” is critical in congestion reduction. The analysis also reveals that “operational capacity” serves as a mediating factor in this relationship. Notably, this analysis identifies less pronounced mediating effects, hinting that built environment may exert a more direct influence on congestion levels. The proposed analytical method and observations hold practical value for planners and policymakers in developing strategies for planning and infrastructure development. A critical takeaway is the imperative to assess the impact on the consequent operational traffic efficiency to ensure that potential congestion is proactively mitigated through informed and sustainable planning decisions.
虽然建筑环境、机动性选择和出行产品之间的关系已被充分记录,但建筑环境对交通性能,尤其是拥堵的影响却没有得到广泛的研究。在现有的研究中,建筑环境对交通性能的直接或间接影响机制仍不明确。此外,交通性能大多是通过综合和粗略的性能指标来量化的,无法反映交通的运行特征。本研究利用宏观基本图(MFD)将交通动态与建筑环境属性联系起来,研究建筑环境与交通拥堵之间的直接和间接关系。研究假设建筑环境对交通拥堵有间接影响,并利用引导中介分析法分析了可能的间接影响。其中,"运行能力 "和 "出行需求 "这两个要素被定义为中介因素。分析基于澳大利亚墨尔本地区 133 个二级统计区(SA2)收集的数据,包括 2019 年收集的交通和建筑环境数据。结果表明,"路网连通性 "和 "路网结构 "会加剧拥堵,而 "公共交通可达性 "则是减少拥堵的关键。分析还显示,"运行能力 "在这种关系中起着中介作用。值得注意的是,该分析发现的中介效应并不明显,这表明建筑环境可能会对拥堵水平产生更直接的影响。提出的分析方法和观察结果对规划者和决策者制定规划和基础设施发展战略具有实用价值。一个重要的启示是,必须评估对交通运行效率的影响,以确保通过明智和可持续的规划决策,积极缓解潜在的拥堵问题。
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引用次数: 0
Improving public transportation via line-based integration of on-demand ridepooling 通过基于线路的按需乘车整合改善公共交通
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-11-01 DOI: 10.1016/j.tra.2024.104289
Andres Fielbaum , Alejandro Tirachini , Javier Alonso-Mora
Ride-sourcing companies have worsened congestion in numerous cities worldwide, as many users are attracted from more sustainable modes. To reverse this trend, it is crucial to leverage the technology of connecting users and vehicles online and use it to strengthen public transport, which can be achieved by integrating on-demand pooled services with existing fixed-line services. We propose an efficient and practical integration idea: namely, to complement fixed bus lines with a fleet of smaller vehicles that follow flexible (on-demand) routes side-by-side with the fixed routes, so that part of the demand that would have used the fixed line can ride the flexible service instead. With this scheme, a smaller bus fleet is required, partially compensating for the increase in operators’ costs stemming from the flexible vehicles. This integration strategy favors mostly two types of users: those traveling in low-demand periods, through lower waiting times, and those located far from the bus stops, because the on-demand vehicles can reduce their access time. We develop simulations in real-world scenarios from Santiago, Chile, and Berlin, Germany, for the cases of human-driven and automated vehicles. Results show that when vehicles are automated: (i) A small number of on-demand vehicles can reduce average walking times from approximately 12 to 2 min while reducing operators’ costs, leading to a Pareto improvement, (ii) A larger number of on-demand vehicles can diminish total costs by 13%–39%, through a reduction in users’ costs, although increasing operators’ costs. If vehicles are not automated, total costs are reduced by more than 10% in all of the scenarios analyzed, but a Pareto improvement is not always possible. In general, this mixed fixed/on-demand system outperforms the use of on-demand ridepooling only. Results are more promising in Berlin, because large buses are cheaper in Santiago and run more crowded, so it is more costly to partially replace them by smaller vehicles.
乘车外包公司加剧了全球许多城市的交通拥堵状况,因为许多用户被更可持续的交通方式所吸引。要扭转这一趋势,关键是要利用在线连接用户和车辆的技术,并通过将按需集合服务与现有的固定线路服务相结合来加强公共交通。我们提出了一个高效而实用的整合方案:即在固定公交线路的基础上,增加一支由小型车辆组成的车队,与固定线路并排行驶灵活(按需)的线路,这样,原本使用固定线路的部分需求者就可以改乘灵活服务。在这种方案下,需要的公交车队规模较小,部分弥补了因灵活车辆而增加的运营商成本。这种整合策略主要对两类用户有利:一类是在低需求时段出行的用户,因为他们的候车时间较短;另一类是距离公交站点较远的用户,因为按需服务车辆可以缩短他们的到达时间。我们在智利圣地亚哥和德国柏林的实际场景中,针对人工驾驶车辆和自动驾驶车辆进行了模拟。结果表明,当车辆实现自动驾驶时:(i) 少量的按需车辆可将平均步行时间从约 12 分钟缩短至 2 分钟,同时降低运营商的成本,从而实现帕累托改进;(ii) 较多的按需车辆可通过降低用户成本将总成本降低 13%-39%,但会增加运营商的成本。如果车辆不是自动驾驶的,在所有分析的方案中,总成本都会降低 10%以上,但不一定能实现帕累托改进。总体而言,这种固定/按需混合系统优于仅使用按需乘车池的系统。柏林的结果更有希望,因为在圣地亚哥,大型公交车的价格更低,而且运行时更拥挤,因此用小型车辆部分取代大型公交车的成本更高。
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引用次数: 0
How has COVID-19 changed individuals’ e-commerce and shopping mobility habits? Evidence from Madrid Region COVID-19 如何改变了个人的电子商务和购物流动习惯?马德里地区的证据
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-31 DOI: 10.1016/j.tra.2024.104295
José Cano-Leiva, Juan Gomez, Guilherme F. Alves, José Manuel Vassallo
The use of e-commerce has grown exponentially in recent years, driven by the increase in Internet connectivity and the spread of electronic payment mechanisms. Lockdowns and social distancing measures imposed during the COVID-19 health crisis led to an extra growth in the use of e-shopping among the population, some of which has continued after the end of the pandemic. E-commerce practices have been found to influence mobility patterns of individuals, with many contributions having analyzed their effects on shopping trips before the pandemic and during COVID waves. However, there is a need to understand the lasting changes in individuals’ patterns of e-commerce as well as their subsequent impact on mobility in the aftermath of the pandemic. To that end, this research takes advantage of a macro survey campaign in the Region of Madrid, Spain between October and November 2022, collecting 15,666 valid responses in a fully post-COVID timeframe. This information was exploited to build a Generalized Structural Equation Model (GSEM) that explores individuals’ patterns of e-commerce use in two different time periods, pre- and post-COVID, with the aim of studying to what extent changes in e-commerce and shopping habits have modified individuals’ mobility patterns. The research concludes a positive, albeit modest, effect of the pandemic on e-commerce usage among the population, as well as an increased preference for shopping physically close to home. Reductions in shopping mobility are greater among intensive users of e-commerce and people who before COVID mainly used the private car or public transport for shopping trips, thus suggesting a positive impact on sustainability from the demand side. The paper provides additional insights on the relationships between shopping habits, e-commerce use, and reductions in the mobility of individuals due to the availability of e-commerce, of interest to researchers and policymakers.
近年来,随着互联网连接的增加和电子支付机制的普及,电子商务的使用呈指数级增长。在 COVID-19 健康危机期间实施的封锁和社会疏远措施导致民众使用电子购物的额外增长,其中一些在疫情结束后仍在继续。人们发现电子商务会影响个人的流动模式,许多研究都分析了电子商务对大流行前和 COVID 期间购物旅行的影响。然而,我们有必要了解个人电子商务模式的持久变化及其对大流行后流动性的后续影响。为此,本研究利用了 2022 年 10 月至 11 月期间在西班牙马德里大区开展的一项宏观调查活动,收集了 15,666 份有效问卷,这些问卷的时间跨度完全在世界艾滋病病毒/艾滋病大流行之后。研究利用这些信息建立了一个广义结构方程模型(GSEM),探讨了个人在两个不同时间段(COVID 前后)的电子商务使用模式,旨在研究电子商务和购物习惯的变化在多大程度上改变了个人的流动模式。研究得出的结论是,大流行病对人们使用电子商务产生了积极影响,尽管影响不大,但人们更倾向于就近购物。电子商务密集型用户和在 COVID 之前主要使用私家车或公共交通工具购物的人的购物流动性降低幅度更大,这表明需求方面对可持续性产生了积极影响。本文为研究人员和政策制定者提供了更多关于购物习惯、电子商务使用以及电子商务的使用导致个人流动性降低之间关系的见解。
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引用次数: 0
How public transport users would react to different pandemic alert scenarios in the post-vaccine era? An analysis of preferences and attitudes of the users in the metropolitan area of Naples (Italy) 在后疫苗时代,公共交通用户将如何应对不同的大流行病警报情景?对意大利那不勒斯大都会区用户的偏好和态度的分析
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-31 DOI: 10.1016/j.tra.2024.104301
Fiore Tinessa , Concepción Román Garcia , Fulvio Simonelli , Andrea Papola , Francesca Pagliara
The dramatic experience due to COVID-19 spread has reshaped travel preferences of public transport (PT) users worldwide, especially in urban areas. As the PT is expected to recover its major role in such areas, it is important to understand the factors influencing PT users’ willingness to pay (WTP) for onboard safety measures, in the event of future pandemic scenarios. Furthermore, both individual latent traits (e.g. concern for the pandemic, trust/distrust in city services and national government actions) and perceived entity of the pandemic are expected to influence preferences for PT users under such a post-pandemic scenario. This paper analyses the preferences and attitudes of PT users in the Naples metropolitan area (Italy) through a hybrid choice model (HCM). First, WTPs for onboard service features are assessed in three hypothetical pandemic alert scenarios, which are explicitly introduced in the model as context variables. Second, the model allows for assessing the relative importance of onboard characteristics as the pandemic scenario evolves. Third, the model incorporates psycho-attitudinal variables and shows how they impact WTPs. Finally, several policy implications for policymakers and transport companies operating in the study area are derived. In particular: (a) WTPs for increased/reduced occupancy rate and green pass check at the entrance significantly depend upon the latent traits investigated; (b) relative importance of safety measures varies significantly between the pandemic alert scenarios; (c) possible ticketing strategies for PT users have been investigated based on the HCM findings, searching for the configuration of safety measures to ensure that users accept a 100% allowed capacity on board during moderate/high pandemic scenarios without varying the price, as well as the price variations needed to stay in an indifference range of the utility in restricted conditions of the service; (d) the acceptability of safety measures has been assessed through a simulation exercise, finding that non-vaccinated travellers are 2.6 and 2.1 times more willing to accept a full capacity of the buses/trains on board than vaccinated people if subscribers or not, respectively.
由于 COVID-19 的传播,全球公共交通(PT)用户的出行偏好发生了巨大变化,尤其是在城市地区。由于公共交通有望恢复其在这些地区的主要作用,因此了解影响公共交通用户在未来大流行情况下对车载安全措施的支付意愿(WTP)的因素非常重要。此外,个人的潜在特质(如对疫情的担忧、对城市服务和国家政府行为的信任/不信任)和对疫情实体的感知预计都会影响疫情后情景下公共交通用户的偏好。本文通过混合选择模型(HCM)分析了意大利那不勒斯大都市区公共交通用户的偏好和态度。首先,在三种假定的大流行警报情景下评估了机上服务功能的 WTP,并将其作为背景变量明确引入模型中。其次,该模型允许随着大流行情景的变化评估机上特征的相对重要性。第三,该模型纳入了心理态度变量,并展示了这些变量对 WTP 的影响。最后,得出了对政策制定者和在研究地区运营的运输公司的若干政策影响。特别是(a) 增加/减少乘座率和在入口处检查绿色通行证的 WTP 显著取决于所调查的潜在特质;(b) 在不同的大流行警报情景下,安全措施的相对重要性存在显著差异;(c) 根据 HCM 的研究结果,研究了针对公共交通用户的可能的票务策略,寻找安全措施的 配置,以确保用户在不改变价格的情况下接受在中度/高度流行情况下 100%的允许乘 客量,以及在服务受限的情况下保持在效用的冷漠范围内所需的价格变化; (d) 通过模拟演练评估了安全措施的可接受性,发现未接种疫苗的旅客比接种疫苗的旅 客分别高 2.6 倍和 2.1 倍。(d) 通过模拟演练评估了安全措施的可接受性,发现未接种疫苗的旅客比已接种疫苗的旅客更愿意接受巴士/火车满载的情况,分别是已接种疫苗的旅客的 2.6 倍和 2.1 倍。
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引用次数: 0
Long-distance mode choice estimation on joint travel survey and mobile phone network data 基于旅行调查和手机网络数据的长途模式选择估算
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-30 DOI: 10.1016/j.tra.2024.104293
Angelica Andersson , Ida Kristoffersson , Andrew Daly , Maria Börjesson
The accuracy of a transport demand model’s predictions is inherently limited by the quality of the underlying data. This issue has been highlighted by the decline in response rates for transport surveys, which have traditionally served as the primary data source for estimating transport demand models. At the same time, mobile phone network data, not requiring active participation from subjects, have become increasingly available. However, some key trip and traveller characteristics enhancing the prediction power of the estimated models are not collected in mobile phone network data. In this paper we therefore investigate what can be gained from combining mobile phone network data with travel survey data, using the strengths of each data source, to estimate long-distance mode choice models. We propose and estimate a set of mode choice demand models on joint mobile phone network data and travel survey data. We show that combining the two data sources produces more credible estimates than models estimated on each data source separately. The travel survey should preferably include the variables: travel party size, cars per household licence, licence holding, in addition to origin, destination, mode, trip purpose, age, and gender of the respondent.
交通需求模型预测的准确性在本质上受到基础数据质量的限制。传统上,交通调查是估算交通需求模型的主要数据来源,但随着交通调查响应率的下降,这一问题也凸显出来。与此同时,不需要被调查者积极参与的手机网络数据也越来越多。然而,手机网络数据中并没有收集到一些能增强估算模型预测能力的关键行程和旅客特征。因此,我们在本文中研究了将移动电话网络数据与旅行调查数据相结合,利用每种数据源的优势来估算长途模式选择模型的益处。我们联合手机网络数据和旅行调查数据,提出并估算了一套模式选择需求模型。我们的研究结果表明,将两种数据源结合在一起所得出的估算结果比单独使用每种数据源估算出的模型更可信。除出发地、目的地、出行方式、出行目的、被调查者的年龄和性别外,出行调查最好还包括以下变量:出行人数、每户牌照汽车数、牌照持有数。
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引用次数: 0
Potential short- to long-term impacts of on-demand urban air mobility on transportation demand in North America 按需城市空中交通对北美交通需求的潜在短期至长期影响
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-29 DOI: 10.1016/j.tra.2024.104288
Kexin Chen , Ali Shamshiripour , Ravi Seshadri , Md Sami Hasnine , Lisa Yoo , Jinping Guan , Andre Romano Alho , Daniel Feldman , Moshe Ben-Akiva
This study applies an agent-based approach to investigate the potential individual-level demand for and system-wide impacts of Urban Air Mobility (UAM) in the short- to long-term, in two real U.S. metropolitan areas. The UAM service we envision in this research provides mobility to on-demand requests from one vertiport to another. The investigations consider the existing electric vertical take-off and landing (eVTOL) aircraft models (assuming they are piloted) and vertiport designs, while accounting for the uncertainties in (i) service attributes (e.g., time saving and service price), and (ii) demand characteristics (e.g., perceived waiting time in various conditions). Towards this goal, the state-of-the-art agent-based simulation platform SimMobility is expanded in this research with new modules required for realistic simulation of the demand, supply, and demand–supply interactions. The expanded platform adopts a high-fidelity model system with: (i) a behaviorally sound demand model to mimic the switching behavior from current non-UAM mode to UAM and to capture the individuals’ willingness to pay and plan-action dynamics in decision-making; (ii) a detailed operation model to account for not only the integration of ground and aerial transportation but also fleet rebalancing and the intra-vertiport state dynamics such as charging, gate availability, taxiing, pre-landing hovering (as a result of capacity limitations), etc.; (iii) a demand-driven vertiport placement and capacity generation module. The results show that the UAM market is expected to start narrow (0.187 % to 0.197 % of all trips) and remain niche in the long term (1.45 % to 1.81 % of all trips) for both cities. In addition, the service is expected to increase mobility inequality, even in the long term. The potential UAM users turned out to be primarily high-income in all scenarios (e.g., 46.9 % to 59.2 % in the long term). Moreover, car-oriented individuals are identified as the main users – not only are most UAM trips expected to emerge from drive-alone trips (84.7 % to 92.8 % at launch), but also drive-alone is expected to be the most preferred access/egress mode (78.4 % to 83.6 % share among all UAM trips at launch). Notably, short-range UAM trips (i.e., flight distance below 40 km) constitute the majority of the UAM potential demand (94.6 % in the long-term scenario).
本研究采用基于代理的方法,在两个真实的美国大都市地区调查个人层面对城市空中交通(UAM)的潜在需求和对整个系统的短期至长期影响。我们在这项研究中设想的城市空中交通(UAM)服务可按需提供从一个港口到另一个港口的交通服务。研究考虑了现有的电动垂直起降(eVTOL)飞机模型(假定其为驾驶型)和机场设计,同时考虑了以下方面的不确定性:(i) 服务属性(如节省时间和服务价格);(ii) 需求特征(如各种条件下的感知等待时间)。为实现这一目标,本研究对最先进的基于代理的模拟平台 SimMobility 进行了扩展,增加了现实模拟需求、供应和供需互动所需的新模块。扩展后的平台采用了高保真模型系统,包括(i) 一个行为合理的需求模型,以模拟从当前非 UAM 模式到 UAM 模式的转换行为,并捕捉个人在决策中的支付意愿和计划行动动态;(ii) 一个详细的运营模型,不仅考虑到地面和空中运输的整合,还考虑到机队再平衡和垂直港内状态动态,如充电、登机口可用性、滑行、着陆前悬停(由于容量限制)等;(iii) 一个需求驱动的垂直港布局和容量生成模块。研究结果表明,在这两个城市,预计 UAM 市场起步较窄(占总出行量的 0.187% 至 0.197%),并将长期保持小众市场地位(占总出行量的 1.45% 至 1.81%)。此外,即使从长远来看,该服务也会加剧流动性的不平等。在所有方案中,UAM 的潜在用户主要是高收入人群(例如,长期为 46.9% 至 59.2%)。此外,以汽车为导向的个人被确定为主要用户--不仅大多数 UAM 旅行预计将来自自驾车旅行(启动时占 84.7% 至 92.8%),而且自驾车旅行预计将成为最受欢迎的出入口模式(启动时在所有 UAM 旅行中占 78.4% 至 83.6%)。值得注意的是,短程 UAM 旅行(即飞行距离低于 40 公里)占 UAM 潜在需求的大部分(长期情景中占 94.6%)。
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引用次数: 0
Development and safety evaluation of an adaptive personalized speed guidance system for on-ramp merging in highway service areas 高速公路服务区匝道并线自适应个性化速度引导系统的开发与安全评估
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-25 DOI: 10.1016/j.tra.2024.104296
Haoran Li , Tengfa Xiao , Yaqiu Li , Yuanjun Feng
As autonomous driving and Vehicle-to-Everything (V2X) technologies evolve, the efficiency and safety of ramp merging in the highway service areas have become increasing critical. This study introduces a closed-loop feedback speed guidance system that accommodates individual driving styles, aiming to optimize merging behaviour, reduce traffic accidents, and enhance total traffic efficiency. The system dynamically adjusts the merging vehicle speeds by continuously monitoring their speed and location with variable steps to promote smoother merging. Moreover, this research also involves collecting naturalistic driving data from ramp merging scenarios, using the K-means clustering and point estimation method to recognize and analyse driving style characteristics, and integrating these styles into the developed closed-loop feedback speed guidance system. This approach results in personalized speed guidance curves tailored to different driving styles, facilitating more efficient mering. Additionally, the study conducts a Safety of the Intended Functionality (SOTIF) evaluation of this system using the System-Theoretic Process Analysis (STPA) method, which helps identify potential security risks and develop appropriate mitigation strategies to ensure the system’s safe and stable operation. The simulation results confirm that this innovative dynamic speed guidance system substantially improves traffic safety and efficiency in ramp merging areas.
随着自动驾驶和车对物(V2X)技术的发展,高速公路服务区匝道并线的效率和安全性变得越来越重要。本研究介绍了一种适应个人驾驶风格的闭环反馈速度引导系统,旨在优化并线行为、减少交通事故并提高总体交通效率。该系统通过持续监测并线车辆的速度和位置,以可变的步骤动态调整并线车辆的速度,从而促进更顺畅的并线。此外,这项研究还包括收集匝道并线场景中的自然驾驶数据,使用 K-means 聚类和点估计方法识别和分析驾驶风格特征,并将这些风格特征整合到所开发的闭环反馈速度引导系统中。这种方法可根据不同的驾驶风格生成个性化的速度引导曲线,从而提高驾驶效率。此外,该研究还采用系统理论过程分析(STPA)方法对该系统进行了预期功能安全(SOTIF)评估,以帮助识别潜在的安全风险并制定适当的缓解策略,确保系统安全稳定地运行。仿真结果证实,这一创新的动态速度引导系统大大提高了匝道合流区的交通安全和效率。
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引用次数: 0
Housing choice in an evolving remote work landscape 不断变化的远程工作环境中的住房选择
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-25 DOI: 10.1016/j.tra.2024.104285
Dale Robbennolt, Angela J. Haddad, Aupal Mondal, Chandra R. Bhat
We estimate a joint model of housing choice along several dimensions to account for changing valuations of housing outcomes due to the COVID-19 pandemic. We consider housing outcomes including housing type, tenure type, the presence of a patio or yard, the number of bedrooms, neighborhood population density, median housing cost, accessibility of amenities, school quality, crime rate, and commute distance. Data used for this analysis were collected in October and November of 2021 from 24 metropolitan areas across the United States. A Generalized Heterogeneous Data Model (GHDM) is used to estimate these housing outcomes as a function of exogenous household sociodemographic characteristics and latent lifestyle propensities. The GHDM also captures jointness caused by unobserved factors, allowing for the estimation of accurate causal effects between outcomes. The results reveal that lifestyle preferences have significant impacts on housing outcomes. Specifically, individuals with a preference for teleworking are more likely to reside in single-family homes in highly populated areas, experience longer commute distances, and exhibit a higher sensitivity to the presence of amenities in their neighborhoods. Additionally, the analysis of tradeoffs between housing outcomes reveals the relative valuations of various housing outcomes. An increased commute distance is found to lead to an increase in single-family homes, reductions in density, and an increased crime rate. Choosing an apartment in a high-density neighborhood is found to lead to reductions in school quality and significant increases in crime rates. Implications of the results for land-use planning, travel demand analysis, and equity considerations are identified and discussed.
我们从几个方面对住房选择的联合模型进行了估算,以考虑到 COVID-19 大流行病导致的住房价值变化。我们考虑的住房结果包括住房类型、保有权类型、是否有庭院或院子、卧室数量、社区人口密度、住房成本中位数、设施便利性、学校质量、犯罪率和通勤距离。本分析所使用的数据是 2021 年 10 月和 11 月从全美 24 个大都会地区收集的。广义异质数据模型(GHDM)用于估算这些住房结果,将其作为外生家庭社会人口特征和潜在生活方式倾向的函数。广义异质性数据模型还能捕捉到未观察到的因素所导致的关联性,从而准确估算出结果之间的因果效应。结果显示,生活方式偏好对住房结果有显著影响。具体而言,偏好远程办公的个人更有可能居住在人口密集地区的单户住宅中,通勤距离更长,对社区内是否存在便利设施的敏感度更高。此外,对住房结果之间的权衡分析揭示了各种住房结果的相对价值。研究发现,通勤距离的增加会导致单户住宅的增加、密度的降低以及犯罪率的上升。在高密度社区选择公寓会导致学校质量下降和犯罪率显著上升。研究结果对土地使用规划、出行需求分析和公平考虑的影响得到了确认和讨论。
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引用次数: 0
Inferring spatial–temporal attributes of vehicle itinerary with Automatic Vehicle Identification data: Methodology and application 利用车辆自动识别数据推断车辆行程的时空属性:方法与应用
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-24 DOI: 10.1016/j.tra.2024.104264
Qi Cao , Yang Liu , Gang Ren , Shunchao Wang , Dawei Li , Yue Deng , Xiaobao Qu
Daily itinerary, consisting of an individual’s trips and activities on a day, is usually fundamental input for many travel demand models. However, current research lacks effective methods to extract daily itineraries of large-scale samples for a long period. To this end, this study presents a methodology to Infer Daily Itineraries (IDI) of vehicles with Automatic Vehicle Identification (AVI) data. A problem-specific Probabilistic Graphical Model is constructed to define how possible one itinerary is true given its observed AVI data. To seek the most possible itinerary among vast feasible states, a candidate movement state generation algorithm and optimal itinerary searching algorithm are developed. Empirical studies have been conducted based on field-test data. Compared with two benchmarks, the proposed IDI improved the inference accuracy significantly even for activities with missing observations. Sensitivity analyses on the size of traffic area zone and data collection have also been performed, which can provide guidance for administrations and researchers on the partition of the study region and placement of the sensors. As the AVI system captures almost entire samples, vehicle movements inferred by IDI can provide a better representation of traffic patterns. This enables a series of applications related to transportation policy and practice. Traffic congestion tracking and parking demand estimation are introduced as two application examples.
每日行程由个人一天的行程和活动组成,通常是许多旅行需求模型的基本输入。然而,目前的研究缺乏长期提取大规模样本每日行程的有效方法。为此,本研究提出了一种利用车辆自动识别(AVI)数据推断车辆每日行程(IDI)的方法。本研究构建了一个针对具体问题的概率图形模型,以定义在观测到 AVI 数据的情况下,某一行程的真实可能性。为了在大量可行状态中寻找最可能的行程,开发了候选运动状态生成算法和最佳行程搜索算法。基于现场测试数据进行了实证研究。与两个基准相比,所提出的 IDI 即使在观测数据缺失的活动中也能显著提高推断精度。此外,还对交通区域面积和数据收集进行了灵敏度分析,为管理部门和研究人员划分研究区域和放置传感器提供了指导。由于 AVI 系统几乎能捕捉到整个样本,因此通过 IDI 推断的车辆移动情况能更好地反映交通模式。这使得一系列与交通政策和实践相关的应用成为可能。交通拥堵跟踪和停车需求估算是两个应用实例。
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引用次数: 0
Greening the commute: A case study of demand for employer-sponsored microtransit 绿色通勤:雇主赞助的微型公交需求案例研究
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-23 DOI: 10.1016/j.tra.2024.104258
Andre L. Carrel , Stavroula M. Mavrouli , Priyamvada R. Natarajan , Rana Tarabay , Andrea Broaddus
Demand-responsive, pooled, app-based transportation services, often known as microtransit, fill a gap in providing public transportation where fixed-route transit services are weak. While prior research mostly focused on public-access microtransit services, little is known about the potential of restricted-access, employer-sponsored services to achieve mode shifts away from driving. This study investigates the possible use of employer-sponsored microtransit service by commuters who currently drive to work, using data from a stated choice experiment conducted at a major medical center in Columbus, Ohio. The results reveal a considerable interest in a hypothetical microtransit commuter service among medical center employees, with on average 29.6% of them shifting from car to microtransit. Overall, relatively few sociodemographic characteristics are found to correlate with interest in employer-sponsored microtransit use, but income, status as a shift worker, and a desire to work while commuting are found to affect choice. Valuations of in-vehicle travel time, flexibility in drop-off/pick-up time, and stop location are calculated and compared to prior results from the transit literature. Such valuations can serve as inputs for optimization models to design microtransit systems. Furthermore, respondents’ potential concerns about a microtransit service and reactions to proposed incentive schemes are analyzed. The study results highlight the value of combining employer-sponsored microtransit implementations with transportation demand management strategies that reduce the attractiveness of commuting by car. The findings suggest that employer-sponsored microtransit represents an opportunity to reduce greenhouse gas emissions and congestion in an industry sector that employs 6.6 million workers in the US.
响应需求、集合式、基于应用程序的交通服务,通常被称为微型公交,填补了固定路线公交服务薄弱的公共交通空白。以往的研究大多集中在公共交通的微型公交服务上,而对于限制进入、由雇主赞助的服务在实现驾驶模式转变方面的潜力却知之甚少。本研究利用在俄亥俄州哥伦布市一家大型医疗中心进行的陈述选择实验数据,调查了目前开车上班的通勤者使用雇主赞助的微型公交服务的可能性。研究结果表明,医疗中心的员工对假设的微型公交通勤服务相当感兴趣,平均有 29.6% 的员工从开车转向乘坐微型公交。总体而言,与对雇主赞助的微型公交使用兴趣相关的社会人口特征相对较少,但发现收入、轮班工作者身份和通勤时工作的愿望会影响选择。我们计算了车内旅行时间、上下车时间灵活性和站点位置的价值,并将其与公交文献中的先前结果进行了比较。这些估值可作为设计微型公交系统的优化模型的输入。此外,还分析了受访者对微型公交服务的潜在顾虑以及对拟议激励方案的反应。研究结果强调了将雇主赞助的微型公交实施与交通需求管理策略相结合的价值,这种策略可以降低驾车通勤的吸引力。研究结果表明,雇主赞助的微型公交是减少温室气体排放和交通拥堵的一个机会,该行业在美国雇佣了 660 万工人。
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Transportation Research Part A-Policy and Practice
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