Electric vehicles, tends to become a growing category of today′s human means of transport. But, because these kind of vehicles are actually quiet, or even silent, the question of a dedicated sound design arise almost inevitably in order to make them more present − then secure − both for their proximity (pedestrians) and their users (driver). This being, current issues for a sound design research framework is then to exploit and explore sound properties that, first, will fix a goal of functionnality (emergence, recognition, acceptance) and, second, will define guidelines for the development of new aesthetics to be included in a general design approach. Thus, a first study focusing on detection of warning signals in urban environments was achieved. Based on the state-of-the-art, a corpus of elementary signals was built and characterized in a time / frequency domain for representing basic temporal and spectral properties (continuous, impulsive, harmonic, etc.). A corpus of representative urban environments was also recorded and realistic sequences were mixed with a dynamic approaching-source model. A reaction time experiment was conducted and leads to interesting observations: especially, specific properties promoting emergence. Moreover, a seemingly significant learning effect also rises from the data and should be further investigated.