Identification of local detouredness and correlation effects in a bounded route choice model: solution & estimation in large-scale networks

The Bounded Choice Model with Local Detour Threshold (BCM-LDT) route choice model (Rasmussen et al. 2024) proposes that local detouredness (the extent to which a route detours on its subparts) is an influential factor upon route choice probability and choice set formation. The current paper first extends the BCM-LDT to capture correlations between overlapping used routes, formulating a Bounded Path Size (BPS) LDT model. It then develops a heuristic solution method for computing BPS-LDT probabilities on large-scale networks. The method involves pre-processing necessary sub-route information from representative universal choice sets. Solution tricks are proposed which are shown to considerably improve computation times. A modified maximum likelihood estimation procedure is developed for estimating the BPS-LDT model. Empirical evidence from a simulation study and real-life large-scale case study show that parameter estimates can be identified, are statistically significant and unique, and that local detouredness is an influential factor upon route choice probability.