Analysing taxi customer-search behaviour using Copula-based joint model

The drivers of vacant taxis tend to cruise the road network searching new passengers, which leads to additional traffic congestion, air pollution and other problems. This study introduces a Copula-based joint model to analyse destination selection and route choice behaviour in the customer-search process. A multinomial logit model is used to analyse the destination selection behaviour, and a path size logit model is used to explore the routes choice behaviour. Accordingly, the joint model applied Copula function is then established to analyse the correlation between these two behaviours. The destination customer generation rate, destination distance, route customer generation rate, path travel time, cumulative intersection delay, path size and route length are selected as explanatory variables. The taxis trajectory data were collected by global positioning system in Xidan District of Beijing City from September 2014 to February 2015. Using the log-likelihood, Bayesian information criterion as evaluation indexes to measure the fitting result, the joint model applied Copula function has the highest goodness-of-fit. The effect of explanatory variables on customer search behaviour is discussed based on the parameter estimation results. The results of this study are helpful to understand the customer-search behaviour of taxi drivers to reduce operating costs and improve the efficiency of the taxi operation system.