Abstract

Knowledge and analysis of crash scenarios from naturalistic driving data can provide insight into the causes of crashes and thus motivate or benefit the future design of automated driving systems (ADSs). The circumstances commonly resulting in crashes for human-driven, light-duty vehicles were previously compiled into the 37 pre-crash scenarios by NHTSA [1]. However, crash analyses and reconstructions for Class 8 long-haul trucks have not yet been explored in the literature. The Crash Investigation Sampling System (CISS) database has been used as the crash data source for compiling a dataset containing details on a nationally representative sample of thousands of heavy-duty vehicle crashes, including information from crash sites, vehicles, victims, and medical records. A census of Class 8 truck crashes with human drivers was compiled for 2016-2020, resulting in 275 incidents with crash reports. After collecting, analyzing, and categorizing crash data involving at least one long-haul truck, this study defines 13 pre-crash scenarios based on the frequency of the crashes. The established scenarios depict vehicle movements, dynamics, and critical events right before a crash. Like the pre-crash scenarios for light-duty vehicles, a database of pre-crash scenarios for Class 8 long-haul trucks can be used to set research priorities and direction in technology development and evaluate the effectiveness of active safety and driving automation features. This study also provides the foundation for future work by establishing pre-crash scenarios and recreating them to assess the potential for driving safety performance of a Class 8 ADS-equipped vehicle.

Document Type

Presentation

Publication Date

2024

Notes/Citation Information

Presented at the 2024 Road Safety & Simulation Conference in Lexington, KY, held October 28-31, 2024

Digital Object Identifier (DOI)

https://doi.org/10.13023/2024.RSS01

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