Active transportation –cycling and biking– not only are sustainable travel modes with zero environmental impact, but also have associated health benefits. However, in comparison with motorized transportation, the motives underlying demand for active transportation –especially beyond recreational purposes– is poorly understood, especially because the standard tradeoff between travel time and cost does not apply to active modes (as it is virtually free and usually takes longer). In this project, we investigate the factors that explain demand for active transportation, including non-instrumental attributes, non-standard observed attributes, and extended decision rules. To integrate non-instrumental attributes (attitudes and perceptions) we propose an extension to the hybrid choice model (HCM) that considers data coming from virtual-reality environments. In fact, we designed and implemented virtual, immersive city blocks to analyze valuation of cycling infrastructure. These scenarios will be exploited in a follow-up project.