Abstract:This paper aims to describe the joint choice of residential location, travel mode, and departure time. First, based on random utility maximization theory, the innovative cross nested logit model and traditional nested logit model are formulated respectively. House price, travel time, travel cost, and factors depicting the individual socio economic characteristics are defined as exogenous variables, and the model choice sets are the combination of residential location subset, departure time subset, and travel mode choice subset. Second, based on Beijing traffic survey data of 2005, the model parameters are estimated, and the direct and cross elasticity are calculated to analyze the change of alternatives probability brought by factors variation. Estimation results show the cross nested logit model is more accurate statistically than any kind of NL model. When exogenous variables altered, decision makers will change their departure time in the first place, subsequently, the mode choice, finally, the residential location. Moreover, elasticity analysis results reveal that the car travel proportion will not decrease even if there is an extra toll on car using for long distance commuters. The effect on choice probability by variations in travel time of the other travel mode can be considered as negligible for commuters living within 5km from their workplaces, and this effect is the greatest for commuters living between 10 and 20km from their workplaces.
