Comparison of pedestrian trip generation models

Using Poisson regression and negative binomial regression, this paper presents an empirical comparison of four different regression models for the estimation of pedestrian demand at the regional level and finds the most appropriate model with reference to the National Household Travel Survey (NHTS) 2001 data for the Baltimore (USA) region. The results show that Poisson regression seems to be more appropriate for pedestrian trip generation modeling in terms of x2 ratio test, Pseudo R2, and Akaike’s information criterion (AIC). However, R2 based on deviance residuals and estimated log-likelihood value at convergence confirmed the empirical studies that negative binomial regression is more appropriate for the over-dispersed dependent variable than Poisson regression.