Project

The United States and the European Union have announced the beginnings of negotiation of the Transatlantic Trade and Investment Partnership (TTIP). This trade agreement is designed to reduce barriers to trade between the two economic units. One potential barrier to trade is the differing safety standards testing and requirements for vehicles sold in the EU and the US. Testing the same make/model under both regimens could be expensive, and negotiation of common standards may be difficult and time-consuming, so the Alliance of Automotive Manufacturers was seeking proposals for a methodology that could be used to demonstrate whether or not vehicles meeting EU standards and vehicles meeting US standards are essentially equivalent in real-world safety performance. If this equivalence could be generally demonstrated, then a tested-once approach may be supported (i.e., passing either set of requirements would certify a vehicle to be sold in either region). In response to the request for proposal, the University of Michigan Transportation Research Institute (UMTRI), located in Ann Arbor, MI, USA, has teamed with SAFER to address this research question in a two-stage process. Phase 1 of the project is designed to assess feasibility in that it is investigated whether existing available datasets support analysis under the methodology proposed in the project application. Phase 2, if funded, would carry out feasible analyses on datasets from both the EU and the US, as planned in Phase 1. The proposed methodology focuses on the idea that although exposure to the driving environment may be very different in the US and the EU (and even within the US and within the EU), vehicle testing is, in its essence, designed to assess risk and provide standards for maximum acceptable risk. Thus, the methodology for assessing essentially equivalent real-world performance should focus on measuring risk, independent of exposure, in the two regions and comparing the assessed risk. To carry out these analyses, it is necessary to have datasets from each region that include certain required variables. Thus, the process for determining the feasibility of this analysis includes cataloging datasets and their contents, in addition to refining the proposed methodology.