Microsimulation of activity generation, activity scheduling and shared travel choices within an activity-based travel demand modelling system

This study presents the microsimulation of activity generation, activity scheduling and shared travel choice processes within an activity-based shorter-term decisions simulator (SDS). Activity generation simulates individuals' daily activities in an orderly fashion utilizing a Markov Chain Monte Carlo modelling technique within the SDS model. Activity scheduling is simulated as a process of activity agenda formation, destination location choice and shared travel choice decisions utilizing heuristics and econometric modelling (e.g. mixed logit) approaches. The proposed SDS model addresses multi-way interactions among different activity and travel decision components. It also accounts for individuals' social interactions within the modelling framework. The model is implemented within C#.NET platform for Halifax, Canada from 2006 to 2036 on each year interval. The performance of the model is measured based on absolute percentage error (APE) values for the year 2011, and microsimulation results are validated with the 2016 Canadian Census information. The simulation results suggest that higher density of activity destinations is predicted within approximately 10 km distances from home locations in 2006. Interestingly, with time, the densities become more skewed to the left of 10 km. The highest percentage of non-shared travel (32%) is predicted for a travel length of less than 5 km in 2036, which decreases with distance. In contrast, the proportions of shared travel choice alternatives are predicted to increase as travel length increases. This paper offers critical insights on spatio-temporal evolution of activity and travel decisions, which will be useful for integrated transportation and land use policy making.