Determining the Impact of Self-Driving Cars on Changes in the Number of Trips with Activity Sim Software

The purpose of this research is to investigate the impact of self-driving cars on changes in travel. To do the work, first, the data related to persons, households, land use, and skim matrices between the studied areas of Washington DC were entered into Activitysim software. The information obtained from the models without the presence of self-driving cars was examined, then the way the self-driving car traveled was added to the software, and the information resulting from the effects of these cars on the changes in trips, which is derived from the changes in the variables of the specific age group, the travel time in the accessibility, choosing more distant destinations for non-mandatory tours and the frequency of non-mandatory tours, in considered. The results in the one-dimensional analysis of the variables show that among the selected variables, the variable of non- mandatory activities of people in the frequency model of non- mandatory tours with 11.7% and the variable of travel time in accessibility model with 5.5% have the greatest effect on the changes in the number of trips. Also, the presence of self-driving cars has the greatest impact on shopping and leisure trips. Another goal of this research is to build a quick response model. After examining the interactive effect of the variables, it was found that the travel time variables and the activities of the working people, the age group under 18 years, and the retired are the most important variables influencing the changes in the number of trips.