Background

The concept of large-scale integrated models has long been recognized as a logical objective among urban and transportation planners. However, its complexity and high cost of research and development has also made a record of frustration that culminated, in 1973, with Douglas Lee’s “Requiem for large scale models"(8). Our context today is quite different than in 1973, not just in terms of computational power but also in terms of data quality and quantity, essential for calibration (9). It is thus without surprise that we now see a new wave of research in large-scale integrated models.
The common approach is through loose coupling of different models, each one specialized on a component. The interface between models consists of exchanging files or API (Application Programming Interface) calls. Majority of the recent efforts are concentrated towards integrating activity-based models with dynamic traffic assignment models in an agent-based framework. The demand component of these integrated models attempt to simulate the daily activity schedules of each individual (considering travel decision such as day pattern, mode, route and departure time choice for activities in a day). These activity schedule then passed on to the supply model, which execute their daily schedules in relation with the transport network. During the process network travel times are updated and feedback to the demand component. The iterative process is used to brings consistency between the two models. Among these efforts most recent is integration of CEMDAP (an ABM) with MATSIM (10). CEMDAP (Comprehensive Econometric Micro-simulator for Daily Activity-travel Patterns)(11), focused primarily on activity scheduling. MATSIM (6) on the other hand, in its own assumes individuals initial plans of the day which are derived on the basis of the household survey data. These initial plans are then executed in MATsim demand-supply simulator and, based on the score, agents adapt their plans in response to conditions that arose during the simulation. The scores within the MATSim are based on heuristic utility functions with a limited set of variables, mostly network performance related. The new plans are generated based on iterative feedback mechanism by modifying few scheduling dimensions of initial plans in order to get a stable solution, which they called a schedule user equilibrium (12). The integration of CEMDAP with MATSIM provide a framework which is more richer in terms of incorporating behavioural notions of individual travel decisions. The challenge is then to make these models speak with each other and guaranteeing full consistency. Moreover, it is difficult to implement just-in-time feedback processes such as activity rescheduling due to within-day dynamics. For example, in a major disruption scenario, many agents will need to reschedule/cancel their upcoming activities on a non-user equilibrium basis, i.e. with partial awareness of the options and of other agent’s decisions. Another example of such an integaration is based on the framework named as FEATHERS(13). In a study in the Flanders region of Belgium, it was connected with ALBATROSS(14), which provides it with daily activity schedules for the entire population using a rule based paradigm. Further, it have other components that model rescheduling decisions, in relation with supply side. Again, some effort is needed to combine the models together and make them spatially and temporally consistent(15).
While, in general, the approach has been to combine two or more sophisticated models on a loosely coupled fashion (e.g. activity-based demand simulator with a dynamic traffic assignment model), some models exist that are developed on the notion of integrated framework that can simulate full day activity/travel schedules. TRANSIMS (16) is an earlier example of such integrated model. There exist four distinctive modules in TRANSIMS such as Population Synthesizer, Activity Generator, Route Planner and Microsimulator. The Activity Generator module in TRANSIMS uses collected household survey data to work out almost all scheduling dimensions of activity patterns of synthetic individuals using some rules, random selection and matching of few socio-economic characteristics of individuals from the survey. Further within TRANSIMS, there is a feedback mechanism introduced between Router and Microsimulator, which attempts to bring the system into equilibrium. However, during that process, individuals can only change their routes with no flexibility of changing other dimensions of their activity patterns. Later, MATSIM was developed on similar notion as TRANSIMS, and both have been used with ABM to overcome the lack of behavioural richness at demand side.  
In addition to the efforts of integrating demand and supply models of day level travel decisions, some efforts are found in the literature where long- term decision models are loosely coupled with day level travel decision models. For example, Urbansim combines land-use, demographic and business establishment models, where agents make long-term decisions (e.g. home and job relocation) by considering, among others, transport accessibility (17). A common approach to obtain accessibility measures is by calling travel models, such as Transcad (18), which runs a 4-step model, TRANSIMS(19), or MATSim(20), the latter two following an activity-based paradigm. Very recently, an integrated modeling system, SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) is presented with a view to more tightly tie together long term and mid-term level decisions (1). SimTRAVEL claimed to integrate three separate model in a unified framework, these are Urbansim (landuse model), OpenAMOS (ABM) (21) and MALTA (DTA) (22). The design structure of SimTRAVEL gives much emphasis on integration of OpenAMOS and MALTA, and Urbansim model is loosely coupled by providing network travel times based accessibility measure to simulate location choices for the next year. However, later OpenAMOS is extended to have location choice and vehicle ownership models. Most of the case studies reported using SimTRAVEL are also based on application of OpenAMOS and MALTA. Berryman et al (23) argued that absence of microscopic traffic simulator in SimTRAVEL does not allow to test cases which require capturing of dynamics at a sufficiently low level of scale, such as impacts of different light rail transit alignments on traffic and landuse patterns.  
Another notable and very recent effort in the area of integrated framework is POLARIS (Planning and Operation Language for Agent-based Regional Integrated Simulation), which build on the notion to provide platform within which several separate models are plug-in together to provide integrated agent-based platform. So far, the use of POLARIS is limited to integrate only ABM and DTA models i.e. an integration of ADAPTS (24) and a mesoscopic traffic simulation model with a special focus on carrying out intelligent transport based case studies. Auld et al (2) reported priliminay results of one such study for Chicago region. According to Hope et al (25), the design of POLARIS is such that it incorporates innovative computaitional methodologies to make sure integration of different models is intact and at the same time provide high performances. However, the platform is still in development phases and no notable examples of integrated studies exist that consider long-term level decisions.  
The literature review clearly indicates that integrated modeling framework is still an emerging field, and so far successful integration modeling examples are limited to combine ABM and DTA models. The recent efforts are attempting to integrate long term models with ABM and DTA, however, the integration is mere on the basis of exchanging data files. This paper reports development of fully integrated SimMobility framework, that is developed primarily to integrate Long-term (land use models), mid-term (ABM+DTA) and short-term (microscopic traffic model) models in unified framework. Within long-term it utilized Urbansim, at mid-term it utilses day-activity schedule approach with DYNAMIT as its supply side and the short term is using MITSIM at its base. The main objective was to provide a platform which enables the simulation of a portfolio of technology, policy and investment options under alternative future scenarios, where impacts of the scenario can be visualized at its three levels in a consistent manner.