路段水平自行车骑行量估算方法的系统范围综述

IF 9.5 1区 工程技术 Q1 TRANSPORTATION Transport Reviews Pub Date : 2023-07-01 DOI:10.1080/01441647.2022.2147240
Debjit Bhowmick , Meead Saberi , Mark Stevenson , Jason Thompson , Meghan Winters , Trisalyn Nelson , Simone Zarpelon Leao , Sachith Seneviratne , Christopher Pettit , Hai L. Vu , Kerry Nice , Ben Beck
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引用次数: 2

摘要

骑自行车量的估算对于基础设施和相关交通要素和政策的战略实施至关重要。与区域级模型相比,链路级体积估计模型(估算单个街道段的体积的模型)能够以更高的空间分辨率理解整个网络中自行车体积的变化。这些模型有助于交通规划者有效地监测交通网络的使用情况,确定提高安全性的机会,并评估政策和基础设施干预措施的影响。然而,考虑到自行车数据的稀疏性和稀缺性,与机动车相比,链路级自行车量估计文献相对有限。本文通过在相关数据库中实施系统搜索策略,对链路级自行车量估计方法进行了范围审查,从而确定了适合审查的研究。审查产生了一些有趣的发现。在实施的所有方法中,直接需求建模是最主要的方法。没有一项研究在同一研究领域实施了多种建模方法,因此不允许对这些方法进行比较。大多数研究都是在美国进行的。我们还观察到,在报告基本研究特征和验证结果时存在很大的异质性,有时甚至根本不报告这些。该研究展示了建模中使用的不同类型的数据(计数、旅行调查、GPS数据)以及一系列流行的解释变量,这些解释变量可以为未来的数据收集和建模变量选择研究提供信息。研究讨论了不同方法的优势和局限性,最后提出了对未来研究的建议。
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A systematic scoping review of methods for estimating link-level bicycling volumes

Estimation of bicycling volumes is essential for the strategic implementation of infrastructure and related transport elements and policies. Link-level volume estimation models (models that estimate volumes on individual street segments) allow for understanding variation in bicycling volumes across an entire network at higher spatial resolution than area-level models. Such models assist transport planners to efficiently monitor network usage, to identify opportunities to enhance safety and to evaluate the impact of policy and infrastructure interventions. However, given the sparsity and scarcity of bicycling data as compared to its motorised counterparts, link-level bicycling volume estimation literature is relatively limited. This paper conducts a scoping review of link-level bicycling volume estimation methods by implementing systematic search strategies across relevant databases, thereby identifying appropriate studies for the review. The review resulted in some interesting findings. Among all the methods implemented, direct demand modelling was the predominant one. Not a single study implemented multiple modelling approaches in the same study area, thereby not allowing for comparison of these approaches. Most studies were conducted in the United States. It was also observed that there exists a lot of heterogeneity in the reporting of basic study characteristics and validation results, sometimes to the extent of not reporting these at all. The study presents the different types of data used in modelling (count, travel survey, GPS data) along with an array of popular explanatory variables that can inform future studies about data collection and variable selection for modelling. The study discusses the strengths and limitations of different methods and finally presents recommendations for future research.

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来源期刊
Transport Reviews
Transport Reviews TRANSPORTATION-
CiteScore
17.70
自引率
1.00%
发文量
32
期刊介绍: Transport Reviews is an international journal that comprehensively covers all aspects of transportation. It offers authoritative and current research-based reviews on transportation-related topics, catering to a knowledgeable audience while also being accessible to a wide readership. Encouraging submissions from diverse disciplinary perspectives such as economics and engineering, as well as various subject areas like social issues and the environment, Transport Reviews welcomes contributions employing different methodological approaches, including modeling, qualitative methods, or mixed-methods. The reviews typically introduce new methodologies, analyses, innovative viewpoints, and original data, although they are not limited to research-based content.
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