Investigation of speed and trajectory of motorcycle riders at curved road sections of two-lane rural roads under diverse lighting conditions

Lemonakis, Panagiotis; Eliou, Nikolaos; Karakasidis, Theodoros E.

doi:10.1016/j.jsr.2021.05.009

Cited by 12 publications

(5 citation statements)

References 10 publications

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“…Its reference center should be oriented to the vehicle's median longitudinal plane. The reference center should be symmetrical concerning the longitudinal plane [9]. The height should not be less than 250 mm or more than 900 mm above the ground.…”

Section: Methodsmentioning

confidence: 99%

Realización del Ensayo de Iluminación para la Homologación de Motocicletas y Triciclos según la Norma ISO 11460:2007

Puente Moromenacho,

Noroña Merchán,

Angulo Álvarez

et al. 2024

INGENIO

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El desarrollo de este ensayo aborda la temática de la aplicación de la normativa internacional ISO 11460:2007 y su cumplimiento para la evaluación de motocicletas y tricimotos de la ciudad de Quito, la cual se encuentra específicamente relacionada a la colocación y nivel de iluminación de los dispositivos de iluminación de estos vehículos. Por esa razón, el objetivo principal del estudio se encuentra relacionado a realizar el ensayo de iluminación que se usa para la homologación de motocicletas y tricimotos acorde a la norma ISO 11460:2007, para lo cual se utilizó como muestra a varias motos aprobadas para circulación en nuestro medio tomadas del mercado a partir del año 2019, ensambladas en el país y en el exterior, el mismo que pondrá en evidencia las falencias y nivel de cumplimiento observados en las motos que conforman la muestra para la investigación, cuyos resultados permitirán establecer la realidad actual de esta problemática. Se realizó un procedimiento adecuado para la evaluación de las motocicletas en el ensayo de iluminación, así como el enfoque, los métodos e instrumentos que permitieron analizar y recolectar información de acuerdo con los lineamientos planteados. Posteriormente en los resultados obtenidos del ensayo de iluminación y los datos de la norma ISO 11460:2007, demostrando que las motos evaluadas desobedecen a dicha norma en algunos de sus dispositivos de iluminación.

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Section: Methodsmentioning

confidence: 99%

Realización del Ensayo de Iluminación para la Homologación de Motocicletas y Triciclos según la Norma ISO 11460:2007

Puente Moromenacho,

Noroña Merchán,

Angulo Álvarez

et al. 2024

INGENIO

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“…Chang(2005 evaluated the performance of negative binomial regression model and neural network to predict accident frequency of a national freeway in Taiwan. Such studies showed that crash risk might be related to vehicle speeds (Aarts and van Schagen, 2006;Lemonakis et al, 2021), weather conditions (Ma et al, 2019;Tao et al, 2016), driver's attention (Kim et al, 2013), etc. Although the aforementioned research has uncovered many key injury indicators of traffic accidents, they would meet the bottleneck to capture particular data characteristics like time periodicity, spatial auto-correlation, and heterogeneity.…”

Section: Traffic Accident Predictionmentioning

confidence: 99%

Sparse Spatio-Temporal Dynamic Hypergraph Learning for Traffic Accident Prediction

Cui¹,

Yang

Abdel-Aty

2023

Preprint

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Traffic accidents have become one of the biggest public health safety matters, which has raised many concerns from citizens and city managers. Accurate traffic accident prediction can not only assist the government in making decisions in advance but also enhance public trust in public safety. Conventional spatio-temporal prediction models, limited by the skewed distributions and sparse labels of traffic accident occurrence, are prone to overfitting. Inspired by hypergraph learning and self-supervised learning, this paper suggests a sparse spatio-temporal dynamic hypergraph learning (SST-DHL) framework to capture the higher-order dependencies in sparse traffic accidents. Specifically, a multi-view spatio-temporal convolution block is employed first to capture the local spatio-temporal correlation and inherent semantics of traffic accidents. Then we propose a cross-regional dynamic hypergraph learning model to capture global spatio-temporal dependencies beneath the entire urban landscape. In addition, a two-supervised self-learning paradigm is intended to strengthen the representation of sparse traffic occurrences by regional self-identification, which can capture local and global spatio-temporal traffic patterns. The proposed model is applicable to most sparse datasets for traffic forecasts. Extensive experiments was conducted on two heterogeneous accident datasets from New York City and London, and the results shows an average improvements of 7.21%-23.09% at different sparsity levels compared to the optimal baselines. More importantly, the proposed SST-DHL improves the interpretability of model results, which demonstrates that hypergraph learning can efficiently capture the complex higher-order spatio-temporal dependencies among different traffic accident instances.

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“…It reflects a result describing the driving behavior as closely as possible to an actual scenario, which is important for strategic planning and safety assessment. Many instrumented vehicle studies have been conducted (Table 1), including the behavior of drivers overtaking bicycles [15][16][17][18], behavior of bicyclists overtaken by vehicles [19], and various behaviors of motorcycle riders, including overtaking behavior in an exclusive motorcycle lane [20] and a trajectory on curved road sections [21].…”

Section: Instrumented Vehicle Studies On Drivingmentioning

confidence: 99%

Lane-Filtering Behavior of Motorcycle Riders at Signalized Urban Intersections

Promraksa

Satiennam

et al. 2022

Journal of Advanced Transportation

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In developing countries, motorcycle riders typically perform lane filtering at signalized urban intersections. This study aims to determine the factors that affect the lateral clearance of motorcycle riders as they travel between two lanes of mixed traffic at signalized urban intersections in developing countries. In this study, an onboard measurement device was developed to measure the lane-filtering behavior of motorcycle riders. It was installed on a test motorcycle to continuously record the lateral clearance, riding behavior, and surrounding traffic conditions. Thirty participants rode the test motorcycle through a signalized urban intersection. Multilevel linear regression was applied to analyze the relationship between lateral clearance and relevant variables at a significance level of 0.05. The instant speed and side of the filtering motorcycle, condition of the lateral vehicle, type of lateral vehicle, and riding frequency of the motorcycle rider significantly influenced the lateral clearance. The findings of this study can contribute to filtering lane management, connected autonomous vehicles, and microscopic traffic simulations for motorcycles traveling in mixed traffic at signalized urban intersections.

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Investigation of speed and trajectory of motorcycle riders at curved road sections of two-lane rural roads under diverse lighting conditions

Cited by 12 publications

References 10 publications

Realización del Ensayo de Iluminación para la Homologación de Motocicletas y Triciclos según la Norma ISO 11460:2007

Realización del Ensayo de Iluminación para la Homologación de Motocicletas y Triciclos según la Norma ISO 11460:2007

Sparse Spatio-Temporal Dynamic Hypergraph Learning for Traffic Accident Prediction

Lane-Filtering Behavior of Motorcycle Riders at Signalized Urban Intersections

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