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Open AccessArticle

Geographical Detection of Traffic Accidents Spatial Stratified Heterogeneity and Influence Factors

by Yuhuan Zhang 1, Huapu Lu 1,* and Wencong Qu 2
1
Institute of Transportation Engineering and Geomatics, Tsinghua University, Beijing 100084, China
2
Road Transport Books Center, China Communications Press Co., Ltd., Beijing 100011, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(2), 572; https://doi.org/10.3390/ijerph17020572
Received: 27 December 2019 / Revised: 8 January 2020 / Accepted: 11 January 2020 / Published: 16 January 2020
(This article belongs to the Section Public Health Statistics and Risk Assessment)
The purpose of this paper is to investigate the existence of stratification heterogeneity in traffic accidents in Shenzhen, what factors influence the casualties, and the interaction of those factors. Geographical detection methods are used for the analysis of traffic accidents in Shenzhen. Results show that spatial stratification heterogeneity does exist, and the influencing factors of fatalities and injuries are different. The traffic accident causes and types of primary responsible party have a strong impact on fatalities and injuries, followed by zones and time interval. However, road factors, lighting, topography, etc., only have a certain impact on fatalities. Drunk driving, speeding over 50%, and overloading are more likely to cause more casualties than other illegal behaviors. Speeding over 50% and speeding below 50% have significant different influences on fatalities, while the influences on injuries are not obvious, and so do drunk driving (Blood Alcohol Concentration ≥ 0.08) and driving under the influence of alcohol (0.08 > Blood Alcohol Concentration ≥ 0.02). Both pedestrians and cyclists violating the traffic law are vulnerable to fatality. Heavy truck overloading is more likely to cause major traffic accidents than minibuses. More importantly, there are nonlinear enhanced interactions between the influencing factors, the combination of previous non-significant factors and other factors can have a significant impact on the traffic accident casualties. The findings could be helpful for making differentiated prevention and control measures for traffic accidents in Shenzhen and the method selection of subsequent research. View Full-Text
Keywords: spatial analysis; spatial statistics; geographical detectors; stratified heterogeneity; factors; traffic accident; nonlinear interaction spatial analysis; spatial statistics; geographical detectors; stratified heterogeneity; factors; traffic accident; nonlinear interaction
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Zhang, Y.; Lu, H.; Qu, W. Geographical Detection of Traffic Accidents Spatial Stratified Heterogeneity and Influence Factors. Int. J. Environ. Res. Public Health 2020, 17, 572.

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