Sponsors (5)
The bill enables state, local, and freight stakeholders to use predictive analytics and telematics to better target safety investments and improve freight performance, but it raises costs, privacy risks, equity concerns, and vendor-dependence that will require strong safeguards and oversight to avoid harms.
State and local transportation agencies can use predictive analytics and telematics to identify high-risk road segments and target safety investments more effectively.
Freight operators and planners gain access to tools that can improve freight safety and performance-based planning, potentially reducing crashes and improving supply-chain reliability.
DOT-required guidance on anonymization, PII protection, and validation creates baseline privacy and data-quality safeguards to promote trustworthy use of safety data by agencies and vendors.
Drivers and transportation workers face increased privacy exposure if anonymization and PII protections are not robustly implemented or enforced when telematics and detailed safety data are used.
State and local agencies may incur new costs to acquire, validate, and integrate predictive analytics, telematics, and related systems into safety programs, straining budgets.
Communities and routes with limited data coverage—often rural and low-income areas—could be disadvantaged by performance evaluations driven by predictive tools, skewing investments toward data-rich areas.
Based on analysis of 2 sections of legislative text.
Authorizes use of safety data, predictive analytics, telematics, and related tools within federal highway and freight programs and directs DOT guidance on privacy, validation, and interoperability.
Allows federal highway safety and freight programs to develop, acquire, deploy, and use safety data, predictive analytics, telematics, and similar validated tools to model risk, target high-risk locations, plan performance-based projects, and evaluate safety outcomes. Directs the Department of Transportation to define terms, issue guidance within one year on privacy, anonymization, security, transparency, accountability, and validation, and to coordinate internally and consult other agencies to support interoperable, responsible use. Intended effects include improved identification of dangerous road segments, better freight safety monitoring, and stronger evaluation of safety projects; it also sets privacy and validation expectations for analytics and requires interagency cooperation to promote consistent, secure implementation.
Introduced December 18, 2025 by John Boozman · Last progress December 18, 2025