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The Statement of National Transportation Policy issued by President Bush and Secretary Skinner last year points out that “innovation and technological advances within the transportation field will be vital to ensure that the system can meet the Nation's transportation requirements for the 21st century.” TravTek, a major Intelligent Vehicle/Highway System (IVHS) advanced motorist information demonstration program in the United States, provides an example of just such innovation. The TravTek program focuses on the navigation and route-guidance needs of out-of-town visitors and utilizes a fleet of specially equipped rental cars as the test bed for the advanced technologies to be evaluated. One of the goals of the TravTek program is to evaluate the potential for, and identify needed enhancements for, increased safety of advanced route-guidance projects.

This paper presents a new data analysis approach to describe driver performance in situations that have the potential of leading to a rear-end crash. The approach provides at least two key benefits. It provides a unified means of analyzing data from different sources such as simulators, test tracks, and instrumented vehicles. It may also provide a means of addressing the huge diversity of driver performance in pre-crash situations.