Dynamic Traffic Assignment Incorporating Commuters? Trip Chaining Behavior

Traffic assignment is the last step in the conventional four-step transportation planning model, following trip generation, trip distribution, and mode choice. It concerns selection of routes between origins and destinations on the traffic network. Traditional traffic assignment methods do not consider trip chaining behavior. Since commuters always make daily trips in the form of trip chains, meaning a traveler?s trips are sequentially made with spatial correlation, it makes sense to develop models to feature this trip chaining behavior. Network performance in congested areas depends not only on the total daily traffic volume but also on the trip distribution over the course of a day. Therefore, this research makes an effort to propose a network traffic assignment framework featuring commuters? trip chaining behavior. Travelers make decisions on their departure time and route choices under a capacity-constrained network. The modeling framework sequentially consists of an activity origin-destination (OD) choice model and a dynamic user equilibrium (DUE) traffic assignment model. A heuristic algorithm in an iterative process is proposed. A solution tells commuters? daily travel patterns and departure distributions. Finally, a numerical test on a simple transportation network with simulation data is provided. In the numerical test, sensitivity analysis is additionally conducted on modeling parameters.