Estimation of utility distribution parameters for joint and solo activities

Abstract

Set of activities performed by individuals is influenced by the choices and preferences of other household members, and their social groups. The utility of an activity depending on the nature of the activity and companionship may vary. In this paper, we propose a methodology to estimate distribution for the utility of joint and solo activities, along with the penalty values associated with the deviation from the mode of activity start time and duration. We develop a bi-level optimization model, where the upper level estimates the accuracy of the activity scheduling predicted from lower level optimization models. Lower level models are variations of pickup and delivery problem, where each model schedules activities for each individual in the population using the parameters of utility distribution and penalty values generated by the Genetic Algorithm. The model was tested on six weeks travel survey data collected in Frauenfeld, Switzerland. The results indicate that travelers are trying to be more consistent with their arrival time to work, school and pickup/drop off activities, also associated penalty values for deviation from the mode value for work and school activities are high. Additionally, significant differences in the estimated utility distribution for joint and solo activities are observed. The proposed methodology has the potential to be applied to any multiday travel survey data, which due to advancements in handheld smart devices and mobile applications is becoming more convenient to collect.