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Journal Article

Citation

Scanlon JM, Sherony R, Gabler HC. Traffic Injury Prev. 2017; 18(Suppl 1): S9-S17.

Affiliation

a Biomedical Engineering and Mechanics Department , Virginia Tech , 440 Kelly Hall, 325 Stanger Street, Blacksburg , VA 24061.

Copyright

(Copyright © 2017, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2017.1300257

PMID

28323447

Abstract

OBJECTIVE: Accounting for one-fifth of all crashes and one-sixth of all fatal crashes in the U.S., intersection crashes are among the most frequent and fatal crash modes. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (MAIS3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS.

METHODS: This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of five separate activation timing thresholds, three separate computational latency times, and two different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-v. The results were then compiled across all crashes in order to estimate system effectiveness.

RESULTS: The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 s to 0.5 s was found to reduce crash and injury prevention estimates by approximately one-third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to changes in activation timing (warning delivered 1.0 to 3.0 s prior to impact). If autonomous braking was used, system effectiveness was found to largely plateau for activation timings greater than 1.5 s prior to impact. In general, the results of this study suggest that I-ADAS will be 2-3 times more effective if an autonomous braking system is utilized over a warning-based system.

CONCLUSIONS: This study highlights the potential effectiveness of I-ADAS in the U.S. vehicle fleet, while also indicating the sensitivity of system effectiveness to design specifications. The results of this study should be considered by designers of I-ADAS and evaluators of this technology considering a future I-ADAS safety test.


Language: en

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