Investigation of clusters and injuries in pedestrian crashes using GIS in Changsha, China

Hu, Luojia; Wu, Xianhui; Huang, Jing; Peng, Yong; Liu, Weiguo

doi:10.1016/j.ssci.2020.104710

Cited by 57 publications

(21 citation statements)

References 52 publications

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“…On the one hand, the distribution of traffic accidents can be visualized through GIS visualization technology [7][8][9]. On the other hand, by using a variety of spatial analysis tools in GIS, scholars can explore the spatial distribution characteristics of traffic accidents and the spatial relationship between different traffic accidents from a variety of perspectives [10][11][12]. e most common spatial statistical methods in GIS are density analysis, which accomplishes spatial visualization of accidents through kernel density and point density methods [13][14][15][16], cluster analysis, which can identify the spatial distribution of traffic accidents as aggregation, diffusion, or random distributions by nearest neighbor distance, and Ripley's K function method [17][18][19], which can identify traffic accident hotspot areas by hotspot analysis [20][21][22] and spatial autocorrelation analysis [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Wang

Chen

et al. 2021

Journal of Advanced Transportation

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Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.

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Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Wang

Chen

et al. 2021

Journal of Advanced Transportation

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“…Tables 8 and 11 show how pedestrian responsibility in traffic accidents, in interaction with demographic and infrastructure variables, show states with a higher risk of serious or fatal injury, especially when there are no pavements (36.17%), poor or no lighting (24.62%), high-speed roads that are not pedestrian-friendly (49.36%) and age groups over 60 years old (31.83%). Consistent with these data, a study published in 2020 using data from China [23], found that the higher severity of pedestrian casualties in traffic accidents is closely related to age (elderly), lighting conditions (occasional darkness), roads (high speed) and infrastructure (such as pavements), as well as pedestrian behaviour.…”

Section: Results Discussionmentioning

confidence: 56%

Pedestrians’ Injury Severity in Traffic Accidents in Spain: A Pedestrian Actions Approach

et al. 2021

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Road traffic accidents are currently between the seventh and tenth leading cause of death in the world, with approximately 1.35 million people killed per year. Despite extensive efforts by governments, according to the World Health Organization, road accidents still cause far too many deaths, especially among pedestrians, cyclists and two-wheel motor vehicle riders, who together account for almost 50% of road traffic fatalities. In particular, Spain had 410,974 traffic accidents between 2016 and 2019, involving 722,516 vehicles and 61,177 pedestrians with varying degrees of injury. This study uses the Bayesian network method to understand how the pedestrians’ responsibility and actions at the time of the traffic accident affect the injury suffered by said pedestrian, also considering the variables of the road infrastructure and vehicles at the accident site. The results confirm that the variables linked to the unsafe behavior of pedestrians, and their responsibility in traffic accidents, increase the risk of suffering serious or fatal injuries during an accident; for example, if a pedestrian is distracted this increases his/her probability of suffering a severe injury (27.86%) with respect to not being distracted (20.73%). Conditions related to traffic in high-speed areas, areas with no or poor lighting, and areas lacking sidewalks, also record increases in pedestrian injury, as is the case in the age group of pedestrians over 60 years of age.

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“…ese studies use the frequency and severity of traffic conflicts to indirectly reflect the level of traffic safety, which mainly focuses on the effectiveness of traffic conflicts [7][8][9][10][11][12][13][14][15][16][17][18][19], traffic conflict evaluation indicators [20,21], and data methods [22,23]. To facilitate the extension and application of the definition of traffic conflict in practice, scholars have proposed a variety of traffic conflict indicators to quantify the proximity and interaction between two or more road users in time or space.…”

Section: Introductionmentioning

confidence: 99%

Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections

Zhang

2022

Journal of Advanced Transportation

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The safety of signalized intersections is of great concern. To allow for an effective evaluation measure on the safety level of intersections, traffic conflict analysis methods are commonly used. However, the existing literature has mainly focused on the statistical prediction of conflicts by using surrogate measurements, among which the spatial-temporal characteristics of the potential conflicts have been less addressed. In addition, most of the relevant studies rely on precise trajectory data, and the results could be limited to engineering applications when real-time/comprehensive trajectory data are not available. To address these issues, this study proposes a SICP (signalized intersection conflict probability) model to predict a straight-left traffic flow conflict with a spatial-temporal distribution in the heat map, which could effectively evaluate the traffic safety of the existing or prebuilt signalized intersections on urban roads. Firstly, the impact of vehicle movement characteristics on traffic conflict at signalized intersections was considered by incorporating the vehicle movement trajectory. Secondly, the signal phase was categorized in several stages (each phase contains switching and nonswitching stages); then, a vehicle-vehicle conflicts probability prediction model was established by integrating both horizontal and vertical arrival probability. Finally, to validate the performance of the proposed model, the measured data were collected from the intersection of Wushan road and Yuehan road in Tianhe District, Guangzhou, China. SSAM（Surrogate Safety Assessment Model）traffic conflict simulation was used to analyze the traffic conflict in the actual data and compared to the SICP model. A case study was conducted to reveal the evolution mechanism of the conflict risk coefficient at the signalized intersection and to estimate the safety status under the various security optimization strategies. The experimental results verified the effectiveness of the SICP model, indicating that the proposed model is effective in evaluating the safety level of existing or prebuilt signalized intersections.

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Investigation of clusters and injuries in pedestrian crashes using GIS in Changsha, China

Cited by 57 publications

References 52 publications

Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin

Pedestrians’ Injury Severity in Traffic Accidents in Spain: A Pedestrian Actions Approach

Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections

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