A national randomized field experiment testing the impact of simulated usage-based insurance programs on driver safety
Many motor vehicle crashes are due to risky driving behaviors measurable by smartphone telematics applications. These apps are deployed by usage-based insurance (UBI) programs to estimate crash risk and price policies, incentivizing customers to drive safer. A preregistered randomized controlled trial (NCT06101251) tested whether a simulated UBI program improved driver safety, and whether being assigned or choosing focused goals yielded further improvement. Adult drivers (n = 1,449) were recruited nationally with social media advertisements. After a 6-week baseline period, participants were randomly assigned to one of four groups for a 12-week intervention: 1) Observation (control); 2) Standard Feedback (weekly texts about four risky behaviors, $100 incentive); 3) Assigned Goal (weekly texts about algorithmically assigned focus behavior and goal, $100 incentive); 4) Chosen Goal (weekly texts about self-chosen focus behavior and goal, $100 incentive). Post-intervention, participants were monitored for 6 more weeks. The primary outcome was a 0-100 score for overall safety (100 = safest). Standard Feedback (covariate-adjusted difference, 2.0 [95 % CI, 1.2-2.7]; P < 0.001), Assigned Goal (2.7 [95 % CI, 2.0-3.5]; P < 0.001), and Chosen Goal (2.2 [95 % CI, 1.4-3.0]; P < 0.001) had higher safety scores than control during the intervention period and at follow-up. Differences between treatment groups were not significant after adjusting for number of comparisons, Ps > 0.10. Treatment groups had significant relative reductions in speeding (11 %-13 %, depending on group), hard braking (16 %-21 %), and rapid acceleration (16 %-25 %), Ps < 0.01. The kind of feedback and incentives offered by UBI programs can cause sustained improvements in driver safety.
Authors
- Dina Abdel-Rahman (ORCID: https://orcid.org/0000-0003-4099-8058)
- Arjun Patel (ORCID: https://orcid.org/0000-0003-4215-4289)
- M. Kit Delgado (ORCID: https://orcid.org/0000-0002-2248-8401)
- Ruiying Xiong (ORCID: https://orcid.org/0000-0002-7524-6764)
- Brian C. Tefft (ORCID: https://orcid.org/0000-0002-8886-9856)
- Sadie Friday
- Malcolm Irving (ORCID: https://orcid.org/0000-0001-6419-3583)
- Athena Lee
- William J. Horrey (ORCID: https://orcid.org/0000-0002-9533-4411)
- Catherine C. McDonald (ORCID: https://orcid.org/0000-0003-3856-8542)
- Jeffrey P. Ebert (ORCID: https://orcid.org/0009-0004-4044-0972)
- Subhash Aryal (ORCID: https://orcid.org/0000-0002-8300-1484)
- Michael O. Harhay (ORCID: https://orcid.org/0000-0002-0553-674X)
- Neda Khan (ORCID: https://orcid.org/0000-0002-2741-5404)
Institutions
- AAA Foundation for Traffic Safety (US)
- University of Pennsylvania (US)
- Temple University (US)
Publication Details
- Journal
- Accident Analysis & Prevention
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1016/j.aap.2025.108331
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00