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Cited by 570

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator

Lee, John D., McGehee, Daniel V., Brown, Timothy L., Reyes, Michelle L.·2002·Human Factors: The Journal of the Human Factors and Ergonomics Society

Abstract

Rear-end collisions account for almost 30% of automotive crashes. Rear-end collision avoidance systems (RECASs) may offer a promising approach to help drivers avoid these crashes. Two experiments performed using a high-fidelity motion-based driving simulator examined driver responses to evaluate the efficacy of a RECAS. The first experiment showed that early warnings helped distracted drivers react more quickly---and thereby avoid more collisions---than did late warnings or no warnings. Compared with the no-warning condition, an early RECAS warning reduced the number of collisions by 80.7%. Assuming collision severity is proportional to kinetic energy, the early warning reduced collision severity by 96.5%. In contrast, the late warning reduced collisions by 50.0 % and the corresponding severity by 87.5%. The second experiment showed that RECAS benefits even undistracted drivers. Analysis of the braking process showed that warnings provide a potential safety benefit by reducing the time required for drivers to release the accelerator. Warnings do not, however, speed application of the brake, increase maximum deceleration, or affect mean deceleration. These results provide the basis for a computational model of driver performance that was used to extrapolate the findings and identify the most promising parameter settings. Potential applications of these results include methods for evaluating collision warning systems, algorithm design guidance, and driver performance model input.

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Cites

  • A model for types and levels of human interaction with automation

    Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×

    “Whether drivers view the collision warning system as automation that triggers a response or as automation that redirects attention can have important implications for design (Parasuraman et al., 2000).”
    Background

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Research works printed but not linked: 22

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Metadata

Authors
Lee, J. D., McGehee, D. V., Brown, T. L., & Reyes, M. L.
Venue
Human Factors: The Journal of the Human Factors and Ergonomics Society
Published
2002-06
Volume
44
Issue
2
Pages
314-334
ISSN
  • 0018-7208 (ISSN-L)
  • 1547-8181
OpenAlex
W1989805652
Cited by
570
References
1
FWCI
13.52
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)

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CoChat. (2026). Citation check: Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator. https://app.cochat.ai/papers/10.1518/0018720024497844
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Lee, J. D., McGehee, D. V., Brown, T. L., & Reyes, M. L. (2002). Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator. Human Factors: The Journal of the Human Factors and Ergonomics Society. https://doi.org/10.1518/0018720024497844

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.