The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Alarm effectiveness in driver-centred collision-warning systems
Abstract
The potential use of systems that seek to communicate a warning of impending collision directly to the driver is examined. Technological advances in collision-warning systems include reliable, low-cost radars, sensors with low noise levels, and the development of accurate detection algorithms for particular crash types, e.g. rear-end collisions. However, fundamental practical constraints make perfect sensor detection difficult to achieve. Imperfect detection conflates the false alarm rate and experience with other technologies confirms driver aversion to false warnings. Although sensitive alarm systems with high detection rates and low false alarm rates have been developed, the posterior probability of a collision given an alarm can be quite low because of the low base rate of collision events. As a result, only a small proportion of alarms will represent true collision scenarios. These and other factors can conspire to reduce alarm effectiveness in collision-warning systems. The problem is illustrated analytically and potential solutions are advanced.
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“To ensure alert reliability, the probability that an alarm reflects a true hazardous event must also be maximized to the extent possible: this can be examined by combining signal detection theory and Bayesian statistics [70].”
From A model for types and levels of human interaction with automation (2000) · cites this paper as [70]
Citations
Cites
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Self-citation
Research works printed but not linked: 8
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Cited by
Sorted by citations
Items 201–205 of 205
Weibull, K., Norell, M. B., Thorslund, B., & Lidestam, B. (2026) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208261436744
Maruyama, M., Koyama, K., Ezaki, T., Sakamoto, J., Sawada, Y., & Matsuoka, T. (2026) · SAE International Journal of Transportation Safety · doi:10.4271/09-14-01-0026
Wang, F., Wu, K., Li, R., Man, S. S., & Chan, A. H. S. (2026) · Ergonomics · doi:10.1080/00140139.2026.2722278
Metadata
- Authors
- PARASURAMAN, R., HANCOCK, P. A., & OLOFINBOBA, O.
- Affiliations
- Catholic University of America (US)
- Venue
- Ergonomics
- Publisher
- Informa UK Limited
- Published
- 1997-03
- Volume
- 40
- Issue
- 3
- Pages
- 390-399
- ISSN
- 0014-0139 (ISSN-L)
- 1366-5847
- OpenAlex
- W2119374926
- Cited by
- 205
- References
- 28
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 3 · 2021: 9 · 2020: 8 · 2019: 8 · 2018: 7 · 2017: 5 · 2016: 11 · 2015: 13 · 2014: 13 · 2013: 7 · 2012: 7
- FWCI
- 9.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ergonomics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- collision warning systems, false alarm rate, driver distraction
- MeSH terms
- Accidents, Traffic, Algorithms, Decision Support Techniques, Equipment Design, Humans
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