Contemporary transport project evaluation requires the ability to value reductions in the number of estimated fatal and non-fatal accidents after project implementation. In this quest, we designed a stated preference (SP) experiment to estimate willingness-to-pay (WTP) for reducing fatal accident risk in urban areas. The survey was implemented in a Web page allowing rapid turnover and a complete customisation of the interview. The sample was presented with a series of route choice situations based on travel time, cost and number of car fatal accidents per year. With this data we estimated Multinomial Logit (MNL) and Mixed Logit (ML) models based on a consistent microeconomic framework; the former with linear and non-linear utility specifications and allowing for various stratifications of the data. The more flexible ML models also allow to treat the repeated observations problem common to SP data and, as expected, gave a better fit to the data in all cases. Based on these models, we estimated subjective values of time, that were consistent with previous values obtained in the country, and also sensible values for the WTP for reductions in fatal accident risk. Thus, the Internet appears as a potentially very interesting medium to carry out complex stated choice surveys.