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Pre-production vehicle validation is a critical step in understanding what potential issues end customers may find. Road profiles used in vehicle level tests are critical in finding failures. Clearly, if all the vehicles are tested only on highway, many failures will not be discovered. Therefore, using the right road profiles is very important. Traditionally, customer survey data is used to identify an appropriate road profile by defining a route that represents the Xth percentile customer. In this paper, a clustering method is applied to group all the customers into several groups. Each group is represented by a single road profile, and the entire customer population can be represented by multiple road profiles. If vehicles are tested using these profiles, then the road test can better represent the field condition, and hopefully failures can be discovered more efficiently.