Analyzing Risk Factors for Fatality in Urban Traffic Crashes: A Case Study of Wuhan, China

Wang, Zhensheng; Yue, Yang; Li, Qingquan; Nie, Ke; Tu, Wei; Shi, Liang

doi:10.3390/su9060897

Cited by 18 publications

(15 citation statements)

References 31 publications

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“…The geographical detector method [41] is a spatial analysis method for measuring spatial stratified heterogeneity [42,43]. It was applied in this study to examine whether multiple variables (i.e., population density and road density) independently or dependently affect the aggregate intensity of the health care facilities along the road network at the community level.…”

Section: Methodsmentioning

confidence: 99%

Measuring Spatial Patterns of Health Care Facilities and Their Relationships with Hypertension Inpatients in a Network-Constrained Urban System

Wang

Nie

2019

IJERPH

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There is evidence of a strong correlation between inequality in health care access and disparities in chronic health conditions. Equal access to health care is an important indicator for overall population health, and the urban road network has a significant influence on the spatial distribution of urban service facilities. In this study, the network kernel density estimation was applied to detect the hot spots of health care service along the road network of Shenzhen, and we further explored the influences of population and road density on the aggregate intensity distributions at the community level, using spatial stratified heterogeneity analyses. Then, we measured the spatial clustering patterns of health care facilities in each of the ten districts of Shenzhen using the network K-function, and the interrelationships between health care facilities and hypertension patients. The results can be used to examine the reasonability of the existing health care system, which would be valuable for developing more effective prevention, control, and treatment of chronic health conditions. Further research should consider the influence of nonspatial factors on health care service access.

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Section: Methodsmentioning

confidence: 99%

Measuring Spatial Patterns of Health Care Facilities and Their Relationships with Hypertension Inpatients in a Network-Constrained Urban System

Wang

Nie

2019

IJERPH

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“…Currently, researchers studying weaving area safety mainly concentrate on the impact of traffic characteristics on the weaving area risk characteristics and the determination of dangerous segments in weaving areas [3][4][5][6][7][8]. In terms of risk and capacity analysis of entrance and exit weaving areas, Lord and Bonneson [9] found that there were more crashes on crossroad off-ramps than crossroad on-ramps by a ratio of 1.5, and non-free-flow ramps had twice as many crashes as other ramp types.…”

Section: Introductionmentioning

confidence: 99%

Risk Distribution Characteristics and Optimization of Short Weaving Area for Complex Municipal Interchanges

Liao

Yang

Ding

et al. 2021

Journal of Advanced Transportation

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This paper is focused on analyzing the risk distribution characteristics in short weaving areas of urban interchanges. The study was carried out on merge-diverge weaving areas with different lengths of 350 m, 450 m, and 550 m. To evaluate and identify the risk, the average speed, speed standard deviation, acceleration range, and average absolute value of acceleration were selected as indicators. Vissim simulation was applied to collect the identification indicator value of 21 typical lane sections. The results show that the risk is concentrated at the 3/4 section and exit section of the outer lane. The vehicle-operating status of the inner and middle lanes is almost unaffected. The operating speed of the outer lane is approximately 4/5 of the same position in the inner lane at 3/4 of the length of the weaving segment, while the speed standard deviation is approximately 2 times greater, and the acceleration range is approximately 2–3 times greater. Moreover, the acceleration of the average absolute value is also approximately 2–3 times greater. To balance the risk distribution, an optimization method is proposed based on the result analysis. Compared with the original design, the results show that a reasonable method of traffic organization for the complex weaving area can effectively improve the risk distribution in the weaving area and reduce the high peak of risk concentration. These results provide a basis for the optimization method and traffic organization of short weaving areas of municipal interchanges.

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“…A sustainable transportation system allows the access needs of individuals to be met safely and consistent with human health [ 3 ]. Therefore, ensuring traffic safety is a major goal of local Traffic Management Bureaus for the sustainable urban transportation [ 4 – 6 ]. The analysis of traffic collisions is key to reducing traffic injuries [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

et al. 2018

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The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions.

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Analyzing Risk Factors for Fatality in Urban Traffic Crashes: A Case Study of Wuhan, China

Cited by 18 publications

References 31 publications

Measuring Spatial Patterns of Health Care Facilities and Their Relationships with Hypertension Inpatients in a Network-Constrained Urban System

Measuring Spatial Patterns of Health Care Facilities and Their Relationships with Hypertension Inpatients in a Network-Constrained Urban System

Risk Distribution Characteristics and Optimization of Short Weaving Area for Complex Municipal Interchanges

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

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