A Multinomial Logit Framework for Secondary Location Choice with Attractiveness and Joint Mode Selection

Abstract

Agent-based transport simulations typically rely on a synthetic population and their travel demand over an average day. One important part of the travel demand generation is the assignment of secondary activity locations within trip chains. This work proposes an adapted multinomial logit framework for secondary location choice that jointly selects mode and location through importance sampling. The model incorporates location attractiveness from employment counts and distance decay parameters estimated from a national travel survey. Candidate locations are filtered by purpose and are sampled within spatially adaptive buffers, with a mixed local/global sampling scheme to preserve long-distance trip representation. The mode share is calibrated through an iterative ratio adjustment technique. Evaluated against the travel survey distance distributions, the proposed model generally reproduces similar distance distributions up to the 95th percentile of distances.