Prediction of Travel Mode Choice Behavior Preference under the Impacts of Congestion Pricing Based on ICLV Model

Psychological factors play a significant role in formation of travel mode choice behavior preference. An integrated choice and latent variable (ICLV) model, which integrates the theory of planned behavior (TPB) and multinomial logit model (MNL) is proposed in this paper to predict mode choice behavior under congestion pricing. The model is estimated using stated preference travel mode choice data of over 1,000 automobile travelers (including more and less habitual automobile travelers) collected in Beijing inner districts. Results from the empirical application shows that the goodness of fit for the integrated choice and latent variable model is higher than that of the traditional mixed-logit model, which proves that latent variables have an obvious impact on mode choice behavior under congestion pricing. This study provides insights for designing congestion pricing and illustrates the importance of developing complementary modules that target psychological factors to promote mode shifts to sustainable travel modes in China.