Denmark is one of the world-leading countries in terms of bicycle infrastructure and has a relatively good public transport system. Yet, a large share of commuters in the Greater Copenhagen Area still uses the car on a regular or semi-regular basis, causing severe problems of congestion and pollution. This article seeks to understand to what extent individuals’ perceived mobility necessities (PMN), activity pattern complexity, and temporal, spatial, social, or compulsory constraints in everyday activities inhibit switching from private motorized transport modes to more environmentally friendly modes. We formulate an Integrated Choice and Latent Variable model that accounts for PMN and activity patterns, complexity and constraints. To estimate the model, we used two datasets: the first dataset is the Danish National Transport Survey, which is a large dataset consisting of approximately 150,000 respondents; the second is a small(er) but highly detailed dataset, which contains relevant information regarding activity patterns, constraints and PMN. We found that the more complex the activity patterns are, the higher are both PMN and the probability of selecting car and bike, and this effect is even more evident when individuals are constrained by some activities. Consistently, individuals who perceive high mobility needs are more likely to select car and bike. The result that mobility needs and related constraints increase cycling conflicts with results found in low-cycling countries. Yet, it indicates that the bike can play a similar role as the car when the respective infrastructure is provided. Our results also indicate that structural improvements, such as flexible work and day-care times, day-care service close to the workplace, or escorting services for children are likely to lead to a substantial reduction in the use of the car.