Estimating mountainous freeway crash rate: Application of a spatial model with three-dimensional (3D) alignment parameters

Wang, Jie; Shi-jian, HE; Zhai, Xiaoqi; Wang, Zhihua; Fu, Xinsha

doi:10.1016/j.aap.2022.106634

Cited by 11 publications

(6 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Research on the safety effects of weather conditions has been increasing in recent years. Collected meteorological data, such as annual/monthly rainfall, average/maximum/ minimum temperatures, and other easily obtainable weather conditions data are widely used in road traffic safety studies [2,[27][28][29][30]. For example, the results of Wen et al (2019) [28] showed that an increase in monthly average wind speed, monthly average daily precipitation, and monthly average visibility were detrimental to freeway traffic safety.…”

Section: Impacts Of Risk Factors On Traffic Safetymentioning

confidence: 99%

Estimation of Crash Modification Factors (CMFs) in Mountain Freeways: Considering Temporal Instability in Crash Data

Zhang,

Huang,

Kuang

et al. 2024

Sustainability

View full text Add to dashboard Cite

The combined contributions to mountain freeway safety of pavement performance, weather conditions, and traffic condition indicators have not been thoroughly investigated due to the complexity of their interactions and temporal instability. A cross-sectional analysis using a Generalized Linear Model (GLM) approach with negative binomial distribution considering time-correlation effects (TC-NB) was adopted to estimate the Crash Modification Factors (CMFs) of these indicators for different segment types, alignment types, and cross-sectional forms based on eight quarters of data from mountain freeways in China. According to the results, improving the pavement performance indexes positively impacts the safety of different freeway segments, especially for the curved segments. Quarterly Average Daily Traffic (QADT) has significantly negative safety effects on two-lane segments with relatively narrow spaces, while the proportion of large vehicles plays a decisive role in the safety impacts of tunnel segments. Small/moderate rain days in a quarter (SMR) were significantly positively correlated with crash frequency, while the percentage of torrential rain days in a quarter (TR) showed an opposite trend. The results of this study contribute to the effective coordination of traffic monitoring systems, pavement management systems, and traffic safety management systems to develop targeted improvement countermeasures for different freeway section types.

show abstract

Section: Impacts Of Risk Factors On Traffic Safetymentioning

confidence: 99%

Estimation of Crash Modification Factors (CMFs) in Mountain Freeways: Considering Temporal Instability in Crash Data

Zhang,

Huang,

Kuang

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…They have discovered that the locations of continuous changes in three-dimensional parameters are directly associated with accident-prone sections. On this basis, Ahmed [ 16 ] and Wang [ 17 ] used three-dimensional parameters to establish a Bayesian accident prediction model, and found their model outperformed traditional two-dimensional parameters-based models. These findings demonstrate that road segment classification and prediction models, based on three-dimensional parameters closely reflecting their intrinsic features, yield more effective and reliable modeling results.…”

Section: Introductionmentioning

confidence: 99%

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways

He,

Fu,

Wang

et al. 2024

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Introduction While driving, drivers frequently adapt their driving behaviors according to their perception of the road’s alignment features. However, traditional two-dimensional alignment methods lack the ability to capture these features from the driver’s perspective. Method This study introduces a novel method for road alignment recognition, employing image recognition technology to extract alignment perspective features, namely alignment perspective skewness (APS) and alignment perspective kurtosis (APK), from in-real driving images. Subsequently, the K-means clustering algorithm is utilized for road segment classification based on APS and APK indicators. Various sliding step length for clustering are employed, with step length ranging from 100m to 400m. Furthermore, the accident rates for different segment clusters are analyzed to explore the relationship between alignment perspective features and traffic safety. A 150 km mountain road section of the Erlianhaote-Guangzhou freewway from Huaiji to Sihui is selected as a case study. Results The results demonstrate that using alignment perspective features as classification criteria produces favorable clustering outcomes, with superior clustering performance achieved using shorter segment lengths and fewer cluster centers. The road segment classification based on alignment perspective features reveals notable differences in accident rates across categories; while traditional two-dimensional parameters-based classification methods fail to capture these differences. The most significant differences in accident rates across categories are observed with segment length of 100m, with the significance gradually diminishing as segment length increases and disappearing entirely when the length exceeds 300m. Implication These findings validate the reliability of using alignment perspective features (APS and APK) for road alignment classification and road safety analysis, providing valuable insights for road safety management.

show abstract

“…Horizontal alignment is of paramount signifcance to location in highway geometric design, while vertical alignment is restricted by altitude and has great impacts on project costs, including earthwork, construction, land use, and user costs [5]. Due to the complexity of threedimensional (3D) spatial curve design, a two-stage method is typically adopted to facilitate the combinations of horizontal and vertical alignments (spatial curve) by completing the horizontal location frst and then the vertical design [7,8]. In the two stages, quantitative reference values are assigned to design elements as control standards to meet fundamental safety and comfort requirements.…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have begun to contemplate and investigate combined highway alignment design [9][10][11]. To optimise highway design, Wang et al [7] and Zhou et al [12] created a method for constructing a 3D model of highway alignments using parameter programming. Te use of visualization technology was an alternative way of creating a 3D model of highway alignments.…”

Section: Introductionmentioning

confidence: 99%

Safety Evaluation for Highway Geometric Design Based on Spatial Path Properties

Wang

2023

Journal of Advanced Transportation

View full text Add to dashboard Cite

Safety is an important aspect of road design. In highway geometric design, road engineers use a two-stage design method due to its convenience, but the available two-dimensional design tools on the market are believed to impose limitations. Horizontal and vertical alignment parameters are considered and determined at the designer’s discretion, potentially downplaying the three-dimensional characters of spatial curves. This study focuses on the three-dimensional characteristics of highway alignments and investigates a safety evaluation method to establish the relationship between crash rate and spatial curve properties. This will necessitate an analytical investigation into the effects of higher-order properties, such as curvature and torsion, on the geometry of spatial Cartesian curves. First, these combinations of horizontal and vertical alignments were categorized into six classifications, each with its own spatial expression in mathematical form. After manipulating the curvature and torsion of the spatial curve algebraically, the correlation between geometric design variables and crash rate was ultimately established. A few cases involving geometric design data and crash facts were utilized for verification. The results revealed a considerable positive correlation between curvature or torsion variance and crashes per million vehicles kilometers, as a slight difference between curvature and torsion could also be spotted. And curvature distribution is correlated with collision frequency more closely than torsion spatial variation.

show abstract

Estimating mountainous freeway crash rate: Application of a spatial model with three-dimensional (3D) alignment parameters

Cited by 11 publications

References 35 publications

Estimation of Crash Modification Factors (CMFs) in Mountain Freeways: Considering Temporal Instability in Crash Data

Estimation of Crash Modification Factors (CMFs) in Mountain Freeways: Considering Temporal Instability in Crash Data

Exploring road safety using alignment perspective features in real driving images: A case study on mountain freeways

Safety Evaluation for Highway Geometric Design Based on Spatial Path Properties

Contact Info

Product

Resources

About