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Summary
Activity-based models are so called because they are based on the principle that travel demand is derived from people’s daily activity patterns. Activity-based models predict which activities are conducted when, where, for how long, for and with whom and the travel choices they will make to complete them. Having this type of detailed models at their disposal allows researchers, practitioners and policy makers to evaluate/ forecast the effect of alternative policies on individuals travel behavior at a high level of temporal and spatial resolution and select the best policy alternative considering a potential wide range of performance indicators.
Background
Activity based models represent an emerging practice in regional transportation planning. The genesis and continued support for their development is derived from the challenges of modern transportation planning practice itself, especially with regard to distinguishing between the social outcomes of transportation policy and the underlying choices made by travelers. While academic research and development has been underway since the 1970s, practical implementation in a handful of, mainly large, urban regions in the US began in the early 2000s. As of 2013, state of practice differs largely between countries. In Europe, a limited number of countries such as The Netherlands and Belgium and Switzerland apply activity-based models in practice while in Asia, only South Korea recently has demonstrated interest.
Current Practice
Activity based modeling is still in its formative stages and a not yet standard of practice. The specification of these models largely emerged from shift in policy challenges put before transportation planners; specifically the need to evaluate highway pricing and other demand management strategies as well as the impacts of land use planning that seek to mitigate travel demand, such as transit-oriented or neo-tradtional development densities. The modeling features most common to the activity based modeling architectures currently include: population synthesis, daily activity pattern formulation, tour formation and choice of time-of-day and mode. Also common among current activity based models is the attention paid to maintaining a high degree of specification along both the person and geographic dimensions. This has been made possible by rapid advances in both GIS and computational capacity that permit processing and storage of much finer geographic specification (e.g. parcels) and microsimulation and tracking of individual travel choices. These features permit the model results to retain the disaggregate character of the original travel survey data; making them appealing to a wide variety of policy analyses.
Modeling Approaches
Three modeling approaches are distinguished in the development of activity based models.
Constraint-based models
This is the first generation of activity based models. The main goal of these models is to examine whether an individual activity agenda is feasible within particular space-time constraints. Examples include PESASP (Lenntorp, 1976), CARLA (Jones et al. 1983), BSP (Huigen, 1986), MAGIC (Dijst, 1995; Dijst and Vidakovic, 1997), and GISICAS (Kwan, 1997).
Utility-maximizing models
This stream of models are based on the premise that individuals maximize their utility when they are organizing their daily schedule. Some representative examples are are the daily activity schedule model (Ben-Akiva, et al., 1996), and PCATS (Kitamura and Fujii, 1998)
Computational process models
Some scholars advocated the idea of mimicking decision heuristics to avoid the unrealistic assumption that individuals are maximizing the utility of their daily schedule. ALBATROSS (Arentze and Timmermans, 2000) and TASHA (Roorda and Miller, 2006) are examples of computational process models.
Early Experiences
Among the MPOs that pioneered activity-based modeling applications, studies have been conducted that evaluate their experience and performance. ARC’s Experience Using its CT-RAMP Activity-Based Model focuses on ARC’s original stated impetus for the development of an ABM, which was to enhance the theoretical integrity of their travel demand forecasting system. DRCOG’s Experience Using its FOCUS Activity-Based Model covers topics ranging from the development of the initial vision for the project, the design of the model’s theoretical and software structures, the calibration and validation of the model, to DRCOG’s uses of the model during the two years since completion of its initial version. SFCTA’s Experience Using its SF-CHAMP Activity-Based Model focuses on how SFCTA has modified and applied SF-CHAMP to answer the questions being asked by planners and decision-makers, as well as what resources, tools and tricks have aided their success. The ARC and SACOG Experience with Activity-Based Models – Synthesis and Lessons Learned was a study commissioned by the Association of Metropolitan Planning Organizations (AMPO) to better understand the experiences of metropolitan planning organizations (MPOs) that have operational activity-based models (ABMs) for use in their planning processes.
Latest Developments
All of the original implementations were developed in an open source environment. As acceptance of the fundamental features of activity-based model converges some efforts have been made to standardize data definitions and execution code with the goal of offering robust proprietary applications for widespread use. Additional challenges remain, however, particularly in the integration of improved transportation supply information produced by network microsimulation tools (e.g. dynamic traffic assignment) and the level-of-service information required by the activity based demand model.