The DOI matches its Crossref record.
An evaluation of the real-world safety effect of a lane change driver support system and characteristics of lane change crashes based on insurance claims data
Open accessAbstract
Objective Lane changes, which frequently occur when vehicles travel on major roads, may contribute to critical situations that significantly affect the traffic flow and traffic safety. Thus, knowledge of lane change situations is important for infrastructure improvements as well as for driver support systems and automated driving development projects. The objectives of this study were to evaluate the crash avoidance performance of a lane change driver support system, the Blind Spot Information System (BLIS) in Volvo car models, and to describe the characteristics of lane change crashes by analyzing detailed information from insurance claim reports. Methods An overall evaluation of the safety effect of BLIS was performed by analyzing crash rate differences in lane change situations for cars with and without the optionally mounted BLIS system based on a population of 380,000 insured vehicle years. Further, crashes in which the repair cost of the host vehicle exceeded approximately US$1,250 were selected and compared. Finally, the study examined different precrash factors and crash configurations, using in-depth insurance claims data from representative lane change crash cases including all severity levels in a population of more than 200,000 insured vehicle years. Results The technology did not significantly reduce the overall number of crashes when all types of lane change crashes and severity levels were considered, though a significant crash-reducing effect of 31% for BLIS c…
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Liability insurance claims offer a more comprehensive assessment of human driving incidents than police collision databases because claims data have a higher reporting frequency of lower-severity collisions or injuries in human drivers.
“Liability insurance claims offer a more comprehensive assessment of human driving incidents than collision databases from police reports because (a) claims data have a higher reporting frequency of lower-severity collisions or injuries in human drivers [1,10]”
From Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver (2024) · cites this paper as [10]
Insurance data capture motor incidents that result in harm or the need for financial recovery, including lower-severity collisions and injuries, but excluding minor events that produce no damage or harm.
“Unlike police-reported crashes that underreport lower-severity collisions and naturalistic driving data that report any contact event, insurance data capture motor incidents that result in harm or the need for financial recovery, including lower-severity collisions and injuries, but excluding minor events that produce no damage or harm.”
From Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver (2024) · cites this paper as [10]
Police reports capture fewer instances of injury claims than liability claims data.
“capture fewer instances of injury claims [10]”
From Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver (2024) · cites this paper as [10]
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Cited by
Sorted by citations
Di Lillo, L., Gode, T., Zhou, X., Atzei, M., Chen, R., & Victor, T. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e34379 · Cited by 45
Metadata
- Authors
- Isaksson-Hellman, I., & Lindman, M.
- Affiliations
- If P&C Insurance, Mölndal, Sweden
- Volvo (Sweden) (SE)
- Corresponding author
- Isaksson-Hellman, Irene
- Venue
- Traffic Injury Prevention
- Publisher
- Informa UK Limited
- Published
- 2018-02-28
- Volume
- 19
- Issue
- sup1
- Pages
- S104-S111
- ISSN
- 1538-957X (ISSN-L)
- 1538-9588
- OpenAlex
- W2794449650
- Cited by
- 14
- References
- 0
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2021: 3 · 2020: 2 · 2019: 1 · 2018: 1
- FWCI
- 0.65
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- Traffic Injury Prevention (publishedVersion)
- PubMed (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Figshare (cc-by)
- Funders
- University of Michigan
- Topics
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Keywords
- driver assistance systems, crash avoidance, health insurance claims, accident severity, autonomous driving, Volvo Cars, repair costs, vehicle-to-vehicle communication, vehicle-to-infrastructure communication, connected vehicles
- MeSH terms
- Accidents, Traffic, Humans, Insurance Claim Review, Protective Devices
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