Climate change creates an adverse impact on human sustainability on earth. Artificial intelligence here comes with a blessing to tackle uncontrolled climate change to make our earth more liveable.Robots need models of human behavior for both inferring human goals and preferences, and predicting what people will do. Typical models, like the Boltzmann noisily-rational decision model, assume that people approximately optimize a reward function and choose trajectories in proportion to their exponentiated reward. In this work, we observe that these models originate from discrete decision making in econometrics, and propose, instead, a probabilistic model of human behavior for continuous trajectory spaces. Rather than each candidate trajectory affecting the human's decision independently, similar trajectories now affect the decision together.