Detection Method for All Types of Traffic Conflicts in Work Zones
Zhepu Xu () and
Dashan Chen
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Zhepu Xu: Department of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
Dashan Chen: Department of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
Sustainability, 2022, vol. 14, issue 21, 1-21
Abstract:
Traffic conflict technology (TCT) is widely used to assess the safety of work zones. The current TCT is temporal and (or) spatial proximity defined based, which can only detect two-vehicle or multi-vehicle conflicts, and is not competent for single-vehicle conflicts. However, single-vehicle accidents in work zones are also severe. This study proposes a detection method for all types of traffic conflicts in work zones. Based on vehicle micro-behavior data, evasive behavior is detected by automatic segmentation, Support Vector Machine (SVM)-based behavior identification, and threshold-based judgment methods. Two-vehicle or multi-vehicle conflicts are detected by classical proximity defined-based method, i.e., the surrogate safety assessment model (SSAM). By comparing the analysis results of the evasive behavior with the one of SSAM, single-vehicle conflicts can be detected. Taking a practical work zone as an example, the effectiveness of this method in detecting all types of traffic conflicts in work zones is verified. The single-vehicle conflict can be subdivided into 10 types according to basic behavior types, such as straight-line driving and decelerating. The two or multi-vehicle conflicts can be subdivided into three types, such as rear-end conflict. The example also verifies the applicability of this method under different traffic volume scenarios.
Keywords: traffic conflict; safety assessment; work zone; surrogate safety assessment model (SSAM); evasive behavior; traffic conflict technology (TCT) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:21:p:14159-:d:957958
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