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Evaluating the impact of automated vehicles on residential location distribution using activity-based accessibility: A case study of Japanese regional areas 利用基于活动的可达性评估自动驾驶汽车对住宅位置分布的影响:日本地区案例研究
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-09 DOI: 10.1016/j.tra.2024.104281
Lichen Luo , Giancarlos Parady , Kiyoshi Takami
Automated Vehicles (AVs) are expected to disrupt the transport sector in the future. Extensive research efforts have been dedicated to studying its potential implications. However, the existing literature is yet limited regarding long-term impacts. To fill this gap, this paper estimates and validates a residential location choice model to evaluate the impacts of AVs on residential location distribution in the context of Japanese regional areas. Activity-based accessibility, a utility-based accessibility measure, is used to reflect the AV impacts on short-term travel demand. The year 2040 is set as the backdrop for the analyses, where the effects of the decreased population are reflected in the scenario settings, along with variables such as decreased travel impedance to accommodate the uncertainties in the characteristics of AVs. The simulation results of four AV scenarios confirm the potential of urban expansion. The results demonstrate that, compared to the Base Scenario, the median distances between the residences and the closest Dwelling Attraction Areas, representing as the target for attracting residences by the local government, expand by 5.2% to 10.2% for the AV scenarios. Two hypothetical policy mandates are then applied to alleviate the problem. The results indicate that providing a 10% subsidy to the land price might be effective to mitigate urban sprawl for the scenario with relatively conservative AV settings. Nonetheless, the substantial cost associated with implementing such a policy renders it effectively unfeasible and underscores the need for proactive planning in anticipation of a level 4 or 5 Automated Vehicle future.
自动驾驶汽车(AV)有望在未来颠覆交通运输行业。大量研究工作致力于研究其潜在影响。然而,现有文献对其长期影响的研究还很有限。为了填补这一空白,本文估算并验证了一个住宅区位选择模型,以日本地区为背景,评估自动驾驶汽车对住宅区位分布的影响。基于活动的可达性是一种基于效用的可达性测量方法,用于反映自动驾驶汽车对短期出行需求的影响。分析以 2040 年为背景,在情景设置中反映了人口减少的影响,同时还考虑了旅行障碍减少等变量,以适应自动驾驶汽车特性的不确定性。四种反车辆方案的模拟结果证实了城市扩张的潜力。结果表明,与基础情景相比,在自动视像情景中,住宅与最近的住宅吸引区(代表地方政府吸引住宅的目标)之间的距离中值扩大了 5.2%至 10.2%。为缓解这一问题,我们采用了两种假定的政策授权。结果表明,对地价提供 10%的补贴可能会有效地缓解相对保守的反车辆通行设置情景下的城市无计划扩展。尽管如此,实施这种政策所需的巨额成本使其实际上不可行,并强调了在预计未来将出现 4 级或 5 级自动驾驶汽车的情况下进行前瞻性规划的必要性。
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引用次数: 0
Corrigendum to “Public-Transportation Credits: The potential of three-part tariffs in public transportation” [Trans. Res. Part A 182 (2024) 104022] 公共交通信贷:公共交通三部分关税的潜力"[Trans. Res. Part A 182 (2024) 104022] 更正
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-08 DOI: 10.1016/j.tra.2024.104282
Silvio Sticher, Kevin Blättler
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引用次数: 0
A flight risk field model for advanced low-altitude transportation system using field theory 利用场论建立先进低空运输系统的飞行风险场模型
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-08 DOI: 10.1016/j.tra.2024.104268
Zhenyu Zhao, Lanfang Zhang, Ruida Zhou, Genze Li, Shuli Wang, Tingyu Liu, Yating Wu
Traffic congestion, as a global issue, often leads to adverse social impacts and huge economic losses, especially in urban areas. Utilizing the available urban low-altitude airspace (ULA) is a potential and promising solution to this problem. To fully leveraging ULA and establishing an advanced low-altitude transportation (ALT) system, ensuring the safety of low-altitude flight is of critical importance. However, the ALT system is currently in the exploratory and developmental stage, and the assessment of flight safety relies primarily on pre-flight evaluations and third-party risk indicators. This study introduces a novel flight risk field model considering risk factors during UAV cruising by introducing a new concept of a flight risk field. The model takes into account the key factors influencing the safety of low-altitude flights, considering both the static characteristics of buildings and the dynamic movements of unmanned aerial vehicles (UAVs). It is capable of reflecting the spatiotemporal variations in flight risks during the UAV cruising process. Finally, the model is validated through numerical examples and simulations. The contribution of this paper is to provide a new idea and method for the safety assessment of the ALT system, which can be further applied to airspace structure design, route optimization, and constitution of traffic regulations, to ensure a reasonable airspace design and enhance the safety of low-altitude flight activities.
交通拥堵作为一个全球性问题,往往会导致不良的社会影响和巨大的经济损失,尤其是在城市地区。利用现有的城市低空空域(ULA)是解决这一问题的一个潜在可行的办法。要充分利用城市低空空域并建立先进的低空交通(ALT)系统,确保低空飞行安全至关重要。然而,ALT 系统目前还处于探索和发展阶段,对飞行安全的评估主要依赖于飞行前评估和第三方风险指标。本研究通过引入飞行风险场这一新概念,引入了一种考虑无人机巡航过程中风险因素的新型飞行风险场模型。该模型考虑了影响低空飞行安全的关键因素,同时考虑了建筑物的静态特征和无人机(UAV)的动态运动。该模型能够反映无人飞行器巡航过程中飞行风险的时空变化。最后,通过数值示例和模拟验证了该模型。本文的贡献在于为 ALT 系统的安全评估提供了一种新的思路和方法,可进一步应用于空域结构设计、航线优化和交通法规的制定,以确保空域设计的合理性,提高低空飞行活动的安全性。
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引用次数: 0
Con-Accessibility: Logit-based catchment area modeling for strategic airport system planning Con-Accessibility:基于 Logit 的集水区模型用于机场系统战略规划
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-07 DOI: 10.1016/j.tra.2024.104270
Sebastian Birolini, Nicolò Avogadro, Paolo Malighetti, Stefano Paleari
National airport system plans serve as the primary programmatic documents employed by policy-makers to outline the roles of different airports and devise strategies for their coordinated and integrated development, encompassing economic, environmental, and social perspectives. This paper proposes a modeling framework to estimate the strength of each airport’s influence and contribution to the surrounding territories, providing methodological foundation for assessing airport demand and delineating the scope of airport interactions. We propose a novel origin-based nested logit model of airport demand based on a comprehensive utility function—denoted as con-accessibility—integrating advanced metrics of ground accessibility and airport connectivity. To address the lack of extensive pairwise municipality–airport data, we cast the estimation problem as a nonlinear constrained least-squares optimization problem, solved via a differential evolution algorithm. The framework’s applicability and insights are demonstrated in a real-world case study of the latest Italian national airport system plan. We highlight the model’s capability in addressing three key policy questions: (i) characterizing airport catchments toward investigating the degree of overlap and airport interactions in serving contended areas; (ii) systematically quantifying the overall level of con-accessibility in any region to assess deficits or surpluses and pinpoint areas for strategic interventions; (iii) supporting the assessment and prioritization of various initiatives, including the upgrade of ground access networks, the expansion of airport supply, and the establishment of new airport facilities.
国家机场系统规划是政策制定者的主要纲领性文件,用于概述不同机场的作用,并从经济、环境和社会角度制定机场协调综合发展战略。本文提出了一个模型框架,用于估算每个机场对周边地区的影响和贡献强度,为评估机场需求和划定机场互动范围提供方法论基础。我们基于综合效用函数(简称为 con-accessibility),提出了一种新颖的基于出发地的嵌套 logit 机场需求模型,该模型整合了先进的地面可达性和机场连通性指标。为了解决缺乏广泛的城市-机场成对数据的问题,我们将估算问题视为一个非线性受限最小二乘优化问题,并通过微分进化算法加以解决。通过对意大利最新国家机场系统计划的实际案例研究,展示了该框架的适用性和见解。我们强调了该模型在解决三个关键政策问题方面的能力:(i) 描述机场集水区的特征,以调查服务于争夺区域的重叠程度和机场之间的相互作用;(ii) 系统量化任何区域的总体通达性水平,以评估不足或过剩,并确定战略干预的区域;(iii) 支持各种措施的评估和优先排序,包括地面通达网络的升级、机场供应的扩大以及新机场设施的建立。
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引用次数: 0
Modelling COVID-19 travel rebound with automated land use identification 利用土地利用自动识别建立 COVID-19 旅行反弹模型
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-07 DOI: 10.1016/j.tra.2024.104280
Jielun Liu, Mei San Chan, Ghim Ping Ong
As movement restrictions during the COVID-19 pandemic forced urban workforces around the world to temporarily adopt telecommuting or flexible working arrangements, some speculate that these practices could remain as the ‘future-of-work’. Therefore, transportation and urban planners would both need to react to new post-pandemic work-based travel patterns. Unlike most common methods of analysing post-COVID telecommuting trends that rely on survey responses, this study develops a two-stage methodology of automatic land use identification (ALI) and mixed effects regression for the synthesis of both land use and transportation data with the aim of monitoring the post-pandemic travel recovery situation. Firstly, clustering methods are used for ALI around public transport destinations to generate different classes of regions based on land use characteristic. Mixed effects regression is then conducted to estimate the variability between different classes of regions. To gain insights on the travel rebound in Singapore, the case study focuses on business entity locations and bus transit volumes during the peak hours. Predictive modelling of a hypothetical travel recovery situation indicates that pre-COVID levels of traffic demand could likely return. The findings from this study have implications on transportation and urban planning, as well as decision-making in the post-COVID world and can be used as a basis for further COVID-related behavioural studies.
由于 COVID-19 大流行期间的行动限制迫使世界各地的城市劳动力暂时采用远程办公或灵活的工作安排,一些人推测这些做法可能会成为 "未来的工作"。因此,交通和城市规划者都需要对大流行后新的基于工作的出行模式做出反应。与大多数依赖调查反馈来分析后 COVID 电子通勤趋势的常见方法不同,本研究开发了一种分两个阶段的方法,即土地利用自动识别(ALI)和混合效应回归,用于综合土地利用和交通数据,目的是监测大流行后的出行恢复情况。首先,围绕公共交通目的地使用聚类方法进行自动土地利用识别,根据土地利用特征生成不同类别的区域。然后进行混合效应回归,以估计不同类别地区之间的差异。为了深入了解新加坡的出行反弹情况,本案例研究重点关注商业实体的位置和高峰时段的公交流量。对假设的出行恢复情况进行的预测建模表明,COVID 前的交通需求水平很可能会恢复。本研究的结果对交通和城市规划以及后 COVID 世界的决策都有影响,可作为进一步开展 COVID 相关行为研究的基础。
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引用次数: 0
Modelling the complementarity and flexibility between different shared modes available in smart electric mobility hubs (eHUBS) 模拟智能电动交通枢纽(eHUBS)中不同共享模式之间的互补性和灵活性
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-05 DOI: 10.1016/j.tra.2024.104279
Fanchao Liao , Dilum Dissanayake , Gonçalo Homem de Almeida Correia
eHUBS are physical locations that integrate two or more electric shared mobility modes. As they provide transport users easier access to a wide range of transport modes, multimodal behaviour is expected to be more common. However, this issue has not been addressed in previous stated preference studies on mode choices involving innovative transport modes. In this study, multimodal behaviour is explicitly addressed both in measurement and in modelling by adopting the multiple discrete–continuous (MDC) modelling framework in contrast to discrete choice models. Instead of asking transport users to indicate the most preferred alternative, they were allowed to choose more than one alternative by allocating trips between several modes. This study aims to answer two questions: 1) whether there is complementarity between the multiple shared modes offered in eHUBS and 2) how would transport users adapt when one of the shared modes that they plan to use becomes unavailable. Using stated mode choice data of non-commuting trips from transport users whose current mode is driving a private car in Manchester, UK, several models under the MDC framework were estimated including Multiple Discrete-Continuous Extreme Value (MDCEV) model, mixed MDCEV model, and the extended Multiple Discrete Continuous (eMDC) model. The results show that there is complementarity between shared electric vehicle (EV) and electric bike (e-bike) offered in the eHUBS. In addition, the research show that the flexibility between those two shared modes is stronger than assumed in the MDCEV model, and common preference heterogeneity cannot fully account for this phenomenon.
eHUBS 是整合了两种或两种以上电动共享交通模式的物理场所。由于它们能让交通使用者更方便地使用多种交通方式,因此预计多式联运行为会更加普遍。然而,在以往涉及创新交通模式的模式选择陈述偏好研究中,这一问题尚未得到解决。在本研究中,通过采用多重离散-连续(MDC)建模框架,与离散选择模型相比,多式联运行为在测量和建模方面都得到了明确解决。我们没有要求交通用户指出最喜欢的选择,而是允许他们通过在几种交通方式之间分配行程来选择一种以上的选择。本研究旨在回答两个问题:1)eHUBS 提供的多种共享模式之间是否存在互补性;2)当交通用户计划使用的一种共享模式无法使用时,他们将如何适应。利用英国曼彻斯特目前使用私家车的交通用户非通勤出行的既定模式选择数据,对多重离散连续极值(MDC)框架下的多个模型进行了估算,包括多重离散连续极值(MDCEV)模型、混合 MDCEV 模型和扩展多重离散连续(eMDC)模型。结果表明,eHUBS 提供的共享电动汽车(EV)和电动自行车(e-bike)之间存在互补性。此外,研究还表明,这两种共享模式之间的灵活性比 MDCEV 模型假设的更强,而共同偏好异质性不能完全解释这一现象。
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引用次数: 0
Comprehensive impacts of high-speed rail and air transport on tourism development in China 高铁和航空运输对中国旅游业发展的综合影响
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-04 DOI: 10.1016/j.tra.2024.104263
Wei Wei , Fengyi Wang , Tao Li , Fangzhou Li
The comprehensive impacts of different transportation systems on tourism development (TD) are becoming more and more profound. High-speed rail (HSR) and air transport (AT), two closely related, convenient, and fast-traffic options, have increasingly become the preferred choice for travelers. Based on a panel data set of 287 cities in China from 2011 to 2019, the impacts of HSR and AT operations on TD and the heterogeneity of these impacts are explored by using multi-period difference-in-differences (DID) and dose–response (DR) models. The results reveal that AT operation and the simultaneous operations of HSR and AT (HSR-AT operations) have a positive and significant impact on TD. However, the significance of the positive impact of HSR operation on TD is not stable. Furthermore, HSR operation and AT operation have different impacts on the TD of the cities in various regions and the cities with various tourism resource endowments. The findings by the DR model indicate that there are differences in terms of the level of HSR and AT operations in small-medium cities compared to large cities. Meanwhile, HSR and AT operations have different impacts on various classes of cities, and the impacts of HSR and AT operation levels on the TD is positive. The obtained results imply that when seizing the development opportunities of HSR and AT to promote TD, administrators should implement different strategies according to local conditions and the current status of TD.
不同交通系统对旅游业发展(TD)的综合影响越来越深刻。高铁(HSR)和航空(AT)这两种密切相关、方便快捷的交通方式日益成为旅游者的首选。本文基于 2011 年至 2019 年中国 287 个城市的面板数据,采用多期差分(DID)和剂量反应(DR)模型,探讨了高铁和航空运输运营对运输量的影响及其异质性。结果显示,自动售检票系统的运营以及高铁和自动售检票系统的同时运营(高铁-自动售检票系统运营)对运输署有积极和显著的影响。然而,高铁运营对运输总成本的积极影响的显著性并不稳定。此外,高铁运营和空铁运营对不同区域城市和不同旅游资源禀赋城市的运输总周转量的影响也不尽相同。DR模型的研究结果表明,与大城市相比,中小城市的高铁和空铁运营水平存在差异。同时,高铁和空铁运营对不同等级城市的影响不同,高铁和空铁运营水平对TD的影响为正。研究结果表明,在抓住高铁和空铁的发展机遇促进运输发展时,管理者应因地制宜,根据运输发展现状采取不同的策略。
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引用次数: 0
A novel data-driven approach for customizing destination choice set: A case study in the Netherlands 定制目的地选择集的数据驱动新方法:荷兰案例研究
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-04 DOI: 10.1016/j.tra.2024.104278
Bin Zhang , Soora Rasouli , Tao Feng
Modeling the destination choice has been of great interest for travel behavior community as well as policymakers in understanding the demand for land use and transportation infrastructures at aggregate and disaggregate levels and possibly devising policies to balance the demand and supplies. One of the challenges underlying predictions of location choice is the large choice set. While traditionally many methods had been devised to limit the choice set size either on a rather ad hoc basis or based on space–time prism by removing the locations out of reach of the subjects, the current study takes a substantially different approach and proposes a data-driven method to customize the generation of the choice set. The proposition is that observing the mobility patterns of citizens for multiple weeks would enable us to limit the choice set, depending on how far the subjects travel (beyond or within the distance they travel for their most frequent activities) to conduct their various activities. More precisely, using longitudinal trajectory data, we first classify people into two subgroups: returners and explorers, based on the size of the area (around their k most visited locations: k-radius of gyration) they move during the observation period. The destination choice set for four types of activities is then customized for returners (and explorers) and is used in a sequence of decisions represented by decision trees for the prediction of their destinations. The models for the whole sample and each subgroup separately are compared. The results suggest that the accuracy of destination prediction improves substantially for all four selected activity types, especially for the returners whose choice sets are formed based on their radius of gyration.
旅行行为学界和政策制定者对目的地选择建模都非常感兴趣,他们希望通过建模了解总体和细分层面对土地利用和交通基础设施的需求,并制定政策来平衡需求和供给。地点选择预测面临的挑战之一是选择集太大。传统上,人们设计了许多方法来限制选择集的规模,这些方法有的是临时性的,有的是基于时空棱镜,通过删除被试者无法到达的地点来限制选择集的规模,而目前的研究则采取了一种截然不同的方法,提出了一种数据驱动的方法来定制选择集的生成。我们的主张是,通过观察市民连续多周的流动模式,我们可以根据受试者进行各种活动时的出行距离(超出或在其最常活动的出行距离之内)来限制选择集。更准确地说,利用纵向轨迹数据,我们首先根据人们在观察期间移动的区域(围绕他们最常去的 k 个地点:k-回旋半径)的大小,将他们分为两个亚组:回归者和探索者。然后为返回者(和探索者)定制四种活动的目的地选择集,并将其用于决策树所代表的一系列决策中,以预测他们的目的地。对整个样本和每个分组的模型分别进行了比较。结果表明,对所有四种选定的活动类型而言,目的地预测的准确性都有大幅提高,尤其是对回归者而言,他们的选择集是根据其回旋半径形成的。
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引用次数: 0
A dynamic discrete choice modelling approach for forward-looking travel mode choices 前瞻性出行方式选择的动态离散选择建模方法
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-04 DOI: 10.1016/j.tra.2024.104272
Joseph Leong, Neema Nassir, Seyed Sina Mohri, Majid Sarvi
In this paper, we present a systematic approach based on dynamic discrete choice models (DDCM) to investigate individuals’ forward-looking mode choice behaviours in daily travel tours with multiple destinations. We propose a novel network transformation model that encompasses the entire decision space of all feasible mode combinations for every observed trip/tour in the dataset. By applying the well-established Recursive Logit model structure commonly used in path choice modelling, we address the tour mode choice problem effectively and quantify forward looking considerations in the mode choice process. The proposed model captures the complex considerations individuals take into account when making mode choices. The network transformation incorporates downstream mode limitations into the preceding mode choice options, enabling us to model individuals’ forward-looking behaviour and gain insights into how considerations of future trips such as a shopping in the evening, or school pick-up trip influence previous mode choice decisions earlier in the day. Uncovering and quantifying these hidden forward-looking factors can help modellers better explain the private car usage usually observed for the entire sequences of daily trips, even in presence of competitive alternative modes. The proposed network transformation also enables us to measure the effect of the requirement/preference to return private vehicles (car, motorcycle, and bicycle) home on mode choices in home-bound trips, and subsequently, on the entire daily mode choice decisions. To validate the proposed model, we utilise the VISTA household travel survey data from the Melbourne Metropolitan area in Australia. The model is compared against baseline models, demonstrating its statistical advantages. Additionally, intuitive illustrations using the data showcase the model’s efficacy. From transport planning and policy perspective, tour-based mode choice modelling provides a more comprehensive and precise understanding of travel behaviour by considering the sequence of trips made by an individual. This can help capture the interactions and dependencies between different trips, which trip-based models may overlook. The proposed model is more suitable for analysing the effects of policy interventions like congestion pricing, public transport investments, or new mobility initiatives, as they can better represent the cascading effects of such policies across multiple trips.
在本文中,我们提出了一种基于动态离散选择模型(DDCM)的系统方法,用于研究个人在有多个目的地的日常旅行中的前瞻性模式选择行为。我们提出了一种新颖的网络转换模型,该模型涵盖了数据集中每次观察到的旅行/游览的所有可行模式组合的整个决策空间。通过应用路径选择建模中常用的成熟递归 Logit 模型结构,我们有效地解决了旅游模式选择问题,并量化了模式选择过程中的前瞻性考虑因素。所提出的模型捕捉到了个人在进行模式选择时所考虑的复杂因素。网络转换将下游模式限制纳入了前面的模式选择选项中,使我们能够模拟个人的前瞻性行为,并深入了解对未来旅行(如晚上购物或接送学校)的考虑如何影响一天中早些时候的模式选择决策。发现并量化这些隐藏的前瞻性因素,可以帮助建模者更好地解释在整个日常出行序列中通常观察到的私家车使用情况,即使在存在竞争性替代模式的情况下也是如此。所提出的网络转换还使我们能够衡量私家车(汽车、摩托车和自行车)回家的要求/偏好对回家出行方式选择的影响,以及随后对整个日常出行方式选择决策的影响。为了验证所提出的模型,我们利用了澳大利亚墨尔本大都会地区的 VISTA 家庭出行调查数据。我们将该模型与基线模型进行了比较,证明了其统计优势。此外,利用数据进行的直观说明也展示了该模型的功效。从交通规划和政策的角度来看,基于旅游的模式选择模型通过考虑个人的旅游顺序,提供了对旅游行为更全面、更精确的理解。这有助于捕捉不同出行之间的相互影响和依赖关系,而基于行程的模型可能会忽略这一点。建议的模型更适合分析拥堵定价、公共交通投资或新的交通措施等政策干预的效果,因为它们能更好地体现这些政策在多次出行中的连带效应。
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引用次数: 0
Do ride-hailing congestion fees in NYC work? 纽约市的打车拥堵费有用吗?
IF 6.3 1区 工程技术 Q1 ECONOMICS Pub Date : 2024-10-03 DOI: 10.1016/j.tra.2024.104274
Yanchao Li, Daniel Vignon
What is the impact of congestion policies targeting ride-hailing systems? This work empirically evaluates NYC’s congestion surcharge policy, particularly in light of the city’s forthcoming implementation of congestion pricing. Using a Difference-in-Differences (DiD) framework, our analysis reveals a statistically significant reduction of approximately 11% in overall ride-hailing travel volume following the implementation of the policy. In particular, Lyft experienced a 17% reduction in travel demand while Uber and yellow-cabs experienced reductions of about 9% and 8% respectively. We further elucidate two key mechanisms — travel distance and subway station availability — to explain this reduction. The surcharge policy has a more pronounced impact on shorter trips (with the most significant decline observed in trips less than one mile), and on ride-hailing trips originating from areas with at least one substitute (such as subway or Citi Bike). Furthermore,the policy’s effect seems more pronounced in lower-income areas of the city and seems to reduce street-hailing industry revenues by 8%. However, despite these reductions, the policy does not result in a corresponding decrease in traffic congestion. Thus, it seems that the policy results in a net welfare loss for the city, at least in the shorter term. Our findings provide insights for understanding the dynamics of congestion policies focused on the ride-hailing industry, especially as New York City prepares to introduce congestion pricing.
针对打车系统的拥堵政策有何影响?这项研究对纽约市的拥堵附加费政策进行了实证评估,特别是考虑到该市即将实施拥堵定价。利用差分法(DiD)框架,我们的分析显示,该政策实施后,打车出行总量在统计上显著减少了约 11%。其中,Lyft 的出行需求减少了 17%,而 Uber 和黄包车分别减少了约 9% 和 8%。我们进一步阐明了两个关键机制--出行距离和地铁站的可用性--来解释这种减少。附加费政策对短途出行的影响更为明显(不足一英里的出行下降最为显著),对从至少有一个替代品(如地铁或花旗自行车)的地区出发的打车出行的影响也更为明显。此外,该政策对城市低收入地区的影响似乎更为明显,似乎使街头打车行业的收入减少了 8%。然而,尽管减少了这些收入,该政策并没有相应减少交通拥堵。因此,该政策似乎给城市带来了净福利损失,至少在短期内是这样。我们的研究结果为理解以打车行业为重点的拥堵政策的动态提供了启示,尤其是在纽约市准备引入拥堵定价的时候。
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Transportation Research Part A-Policy and Practice
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