Trip Chaining Model with Classification and Optimization Parameters

Abstract

In order to model the complex requirements of users travelling in an urban environment, the relevant parameters for creating activity chains have to be identified. In this study, travel related parameters were collected and grouped into two main types: classification parameters and optimization parameters. In the case of optimization parameters, further grouping was performed where general and comfort parameters were introduced. Additionally, the possible values and data sources of the parameters were identified. A utility function was created to take into account the optimization parameters and the weights. Weights related to comfort optimization parameters were aggregated to decrease the number of required settings by the users. Finally, the features of the proposed optimization algorithm are described. With the identified parameters, aggregated weights and elaborated utility function activity chains can be optimized for users with different requirements.