Mid-Term Simulator

The mid-term (MT) level simulates daily travel at the household and individual level. It is categorized as a mesoscopic simulator since it combines activity-based microsimulator on the demand side with macroscopic simulation at the supply side. Figure 4 presents the modeling framework of the MT simulator implemented in SimMobility. Detail description of each component of the MT model can be found in (26). The demand comprises two groups of behavior models: pre-day and within-day. The pre-day models follows an enhanced version of econometric Day Activity Schedule approach (presented in (27)) to decide an initial overall daily activity schedule of the agent, particularly its activity sequence (including tours and sub-tours), with preferred modes, departure times by half-hour slots, and destinations. This is based on sequential application of hierarchical discrete choice models using a monte-carlo simulation approach.
Figure. Framework of the Mid-Term Simulator
As the day unfolds, the agents apply the within-day models to find the routes for their trips and transform the activity schedule into effective decisions and execution plans. Through the publish/subscribe mechanism of event management, as mentioned above, agents may get involved in a multitude of decisions, not constrained to the traditional set of destination, mode, path and departure time depending upon their state in the event simulation cycle. For example, the agent could reschedule the remainder of the day, cancel an activity (or transfer it to another household member), re-route in the middle of a trip (including alighting a bus to change route), or run an opportunistic activity, like shopping while waiting. The supply simulator follows the dynamic traffic assignment(DTA) paradigm as used previously in DynaMIT (5), including bus and pedestrian movements. Particularly for public transport, MT model allows for bus (and subway) line scheduling and headway based operations are currently being implemented. We also explicitly represent on-road bus stops and bus bays both at the mid-term and short-term, which allows for accurate estimation of impacts of the bus operations on the road traffic. Within the MT simulator, the interaction between the within-day and supply is responsible to bring the system to consistency. In addition to this, a day-to-day learning module, which feeds back network performance to the pre-day model, is introduced to update agent’s knowledge (either as a calibration procedure or for a multiple day simulation).
The MT simulator takes input in the form of population (an output of the LT level) that contains details characteristics of each agent in the simulation region, and process the day activity schedule of each agent. Furthermore, it passes the accessibility measure in the form of logsum from the top-level model of preday component to the LT [FP1] simulator representing maximum expected utility of activity-travel pattern at given supply conditions[A2] . The MT simulator also passes trip chains to ST simulator as a demand to simulate smaller region traffic with microscopic details.