Commuter Travel Behavior Modeling in Metropolitan Areas Based on Cumulative Prospect Theory: A Case Study of Xi’an, China

A metropolitan area is a new form of urban development under the agglomeration effect and scale economy. The renewal and upgrading of urban spatial structures have brought new pressure to urban commuting. Under the new form of the metropolitan area, the process of regional integration has accelerated, and long-distance extreme commuting has increased. New changes have taken place in the travel structure. This paper constructs a travel behavior selection model for office workers based on the cumulative prospect theory, introduces the value of commuting travel time into the generalized travel cost function, uses the weight function and the improved generalized travel cost function as the basis of the transportation mode selection model, defines the reference point of the generalized travel cost in the model, and selects the prospect with the largest cumulative prospect value as the optimal decision for travelers. Based on the “expected utility maximization theory” and the “cumulative prospect theory,” the commuter is simulated under four different travel scenarios to study the optimal traffic mode selection behavior. The results show that under the framework of expected utility theory, the travel mode choice behavior of commuters is not affected by travel scenarios, and the cumulative prospect theory is more suitable for the study of travel mode choice behavior. The construction of a transportation mode selection model with the value of commuting travel time as the core variable can help commuters to choose a reasonable transportation mode and provide a basis for the government and relevant departments to formulate traffic management plans and implement traffic congestion mitigation policies.