Assessing the applicability of the cyclists’ Level of Traffic Stress (LTS) classification to a medium-sized city in a developing country

Rodrigues, Murilo Ribeiro; Silva, Antônio Nélson Rodrigues da; Teixeira, Inaian Pignatti

doi:10.1016/j.jth.2021.101321

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…The simultaneous influence of more than one additional stressor was also observed in many cases, causing some road segments originally classified as LTS 1, in critical situations, to be reclassified as LTS 4. The authors who suggested the criteria used in the present research for the LTS reclassification highlight that, for scenarios where steep uphill slopes and roundabouts are observed simultaneously, the inclusion of both factors in the LTS reclassification is sufficient to promote a reasonable agreement between the original model and cyclists' real perceptions of stress (Rodrigues, Silva and Teixeira, 2022). As for the city's bike lanes, originally classified as LTS 2, some road sections close to roundabouts also had their classification worsened, since these cycling facilities are only partially segregated from motorized traffic.…”

Section: Resultsmentioning

confidence: 96%

Comparing distance-based and stress-based centralities to rank priority locations for cycling infrastructure investments in small-sized cities

Monari,

Segantine,

Rodrigues da Silva

et al. 2024

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The lack of technical guidelines to define investment priority locations is one of the barriers to cycling in emerging countries, limiting the preparation of urban mobility plans even when legally required. The objective of this paper is to propose and compare two approaches, with and without considering the cyclists’ perception of stress (assessed with the LTS, or Level of Traffic Stress), to determine the relative importance of road segments in the network and to rank priority locations for investments in cycling infrastructure. A case study was conducted in the city of Bariri (Brazil), for which the overall contribution of each network link to the identified cycling routes was mapped and ranked according to both criteria. The spatial distribution of differences between homologous ranks (i.e., ranks of the same network link according to different criteria) was also mapped, and the spatial autocorrelation between these differences was assessed by the Local Moran’s Index, allowing the identification of road segments of greater similarity and dissimilarity between the proposed approaches for resource allocation.

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Section: Resultsmentioning

confidence: 96%

Comparing distance-based and stress-based centralities to rank priority locations for cycling infrastructure investments in small-sized cities

Monari,

Segantine,

Rodrigues da Silva

et al. 2024

TRANSPORTES

Self Cite

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“…Feizi et al [26] also proposed a cycling comfort index, based on an ordered probit model, and used it to explore the relationship between bicycle dynamics and the level of comfort. Yan et al [54] found that the maximum number of side-by-side riding allowed by the path width can be used to evaluate the road width. Li et al [55] built a model to analyze the physical environmental factors that afect comfort and found that cyclist comfort was mainly infuenced by road geometry and surrounding conditions on physically separated paths.…”

Section: Evaluation Indicatorsmentioning

confidence: 99%

Evaluating Bicycling Environments with Trajectory Data on Shared Bikes: A Case Study of Beijing

Shao

Wang

et al. 2023

Journal of Advanced Transportation

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A detailed evaluation of the riding environment can help the government master the urban riding environment, identify problematic road sections, and improve riding quality. However, the current evaluation of riding environment is mainly subjective, lacking big data (e.g., shared bicycle trajectory data) as a data-driven objective evaluation system. The emergence of shared bicycle data has provided data support for data-driven riding environment evaluation, but there are few studies using shared bicycle data for riding evaluation at present. First, according to the characteristics of the data and the riding environment, a boxplot method and Bayesian probabilistic network model are used to exclude abnormal data and to match trajectories to road sections. Second, this paper proposes a data-driven evaluation framework based on riding influencing factors. An evaluation framework, which is composed of node-, link-, and block-level evaluation indicators, was constructed, using an evaluation model combining TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and KNN (K-Nearest Neighbors). The evaluation results can identify parking issues, intersection difficulties, and lane occupancy issues on bicycle sections, and visually reflect the riding environment. The significance of this article is to create an objective evaluation system based on a data-driven technology to accurately identify sections and causes of riding quality problems. The research results can be applied in the future to evaluate the cycling environment around the railway stations for bicycle parking planning and determine the foothold for traffic management.

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A multi-criteria approach for urban mobility project selection in medium-sized cities

Silva

Santos²,

Setti³

2022

Sustainable Cities and Society

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Assessing the applicability of the cyclists’ Level of Traffic Stress (LTS) classification to a medium-sized city in a developing country

Cited by 3 publications

References 19 publications

Comparing distance-based and stress-based centralities to rank priority locations for cycling infrastructure investments in small-sized cities

Comparing distance-based and stress-based centralities to rank priority locations for cycling infrastructure investments in small-sized cities

Evaluating Bicycling Environments with Trajectory Data on Shared Bikes: A Case Study of Beijing

A multi-criteria approach for urban mobility project selection in medium-sized cities

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