Spatiotemporal instability analysis of injury severities in truck-involved and non-truck-involved crashes
The truck involvement could potentially increase the crash frequency and resulted injury outcomes and it is of great necessity to understand the similarities and differences in the mechanism of how determinants influence injury severities of truck-involved and non-truck-involved crashes and explore their spatiotemporal stability. Based on the crash data of Beijing-Shanghai Expressway and Changchun-Shenzhen Expressway over the three years (2017-2019), the heterogeneity and spatiotemporal stability of contributing factors affecting truck-involved and non-truck-involved crashes were investigated through random-parameter logit models with unobserved heterogeneity in means and variances. Three injury severity outcomes of severe injury, minor injury, and no injury were examined considering multiple factors including driver, vehicle, roadway, environmental, temporal, spatial, traffic and crash characteristics. Besides, the spatiotemporal stability was investigated based on the likelihood ratio tests. Marginal effects were also calculated to analyze the spatiotemporal stability and potential heterogeneity of the contributing variables from year to year. The findings exhibited remarkable differences between truck-involved and non-truck-involved crashes, and an overall spatiotemporal instability was observed in the current study while several indicators were also reported to show relative spatial or temporal stability such as length of the horizontal curve, annual average daily traffic (AADT), early morning, cloudy weather. This paper provided some suggestions to prevent crashes for truck-involved and non-truck-involved crashes across different highways respectively and develop safety measures accordingly.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/22136657
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Supplemental Notes:
- © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Wang, Chenzhu
- Chen, Fei
- Zhang, Yunlong
- Cheng, Jianchuan
- Publication Date: 2022-6
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 100214
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Serial:
- Analytic Methods in Accident Research
- Volume: 34
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 2213-6657
- Serial URL: http://www.sciencedirect.com/science/journal/22136657
Subject/Index Terms
- TRT Terms: Alternatives analysis; Crash characteristics; Injury severity; Motor vehicles; Traffic crashes; Truck crashes
- Geographic Terms: Beijing (China); Changchun (China); Shanghai (China); Shenzhen (China)
- Subject Areas: Highways; Motor Carriers; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 01842003
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 7 2022 5:31PM