Analysis of driver’s choice behavior based on the combined model of utility-regret

In the context of increasing urban traffic trajectory data, based on large-scale urban traffic trajectory data, in the field of intelligent transportation, it has become an urgent need to analyze travelers’ routing behaviors and establish effective routing models to provide travelers with efficient and reasonable driving route recommendations. It is often the case that urban taxi groups has better route choice behavior than other travel group under the cost-benefit constraints. Therefore, providing route recommendations for other travelers according to the route choice habits of urban taxi group is a feasible solution to the above need. This paper starts with the utility maximization model and the stochastic regret minimization model, for the problem that the traveler cannot satisfy the premise of the complete rationality of the utility maximization model when choosing routes and the random regret minimization model ignores the traveler’s sensitivity to the original value of the alternative attribute, and improve the calculation formula of the regret value in the random regret minimization model. A route choice model under the utility-regret combination rule is proposed based on the combination of the utility model and the improved regret model, and then, based on the historical trajectory data of taxis in Xi’an, the RP data required by the model is extracted, and the parameters of the model are estimated and verified. The experimental results show that the route choice probability calculated by the model is closer to the route choice probability in the real scene than the simple utility maximization model or the simple random regret minimization model.