New Features of Applied Activity-Based Travel Models
Peter Vovsha, Parsons Brinckerhoff
This paper describes new features of Activity-Based Models in practice in the US. They include new methods for integrating choices across multiple dimensions, achieving a better balance between activity demand and supply sides, tour formation and others.
The paper describes innovative features incorporated into the recently developed Activity-Based travel Models (ABMs) in the US metropolitan areas of Phoenix-Tucson, San-Diego, Chicago, and Jerusalem, Israel. These ABMs inherited the basic features of the previous generation such as a microsimulation implementation, accounting for interdependences between activities and trips at disaggregate individual level and with a continuous time resolution, using tour as the main unit of modeling instead of trip, accounting for intra-household interactions, etc. However, these models included several significant advances and methods that had not been applied before. The paper has the following main focuses:
Integrating choices across multiple dimensions: the paper discusses application of new techniques like Gibbs Sampling to handle various complicated choice contexts that cannot be handled by conventional sequences of choice models. In particular, it shows how the sequencing issue with respect to trip mode, destination, and time-of-day choice can be resolved. The paper discusses how different choice dimensions can be interlinked in model estimation and application, how the overall model convergence can be achieved, and how this improves the model system sensitivity and response to policy variables. The examples of improved models and associated new choice dimensions include choices of individual mobility attributes, usual work arrangements, tour structure, and others.
Addressing supply side of activities: tremendous progress has been recently made in the ABM paradigm on the demand side, i.e., in the way how person, household, and urban characteristics affect the needs for activities and corresponding travel. Supply side of activities that represents characteristics of different locations in terms of how they could meet the demand remains largely unexplored. In modeling tour and trip destinations, the differences between alternative locations are described by a limited number of population and employment variables. The paper describes new practical methods for addressing supply-side of activities in the framework of operational ABMs. The paper substantiates cases where the supply-driven approach offers practical advantages and a better balance between the demand and supply side can be achieved. They include incorporation of special events including sporting events, large-scale concerts, fare grounds, etc. These events are characterized by a predictable number of participants and constraints on the supply side. Participants in special events are generated at a fully disaggregate level based on the special event surveys. Then, these participants are allocated to households in the synthetic regional population. Participation in special event is considered as the highest priority activity that is embedded in the individual daily activity pattern of each participant. The paper presents an extended taxonomy of activity types and corresponding land-use variables was used that greatly improved the explanatory power of destination choice models. For example, several types of shops are considered with a special emphasis on shopping mall effects. Temporal profiles of activity supply and a spatio-temporal equilibrium between the demand (individual time-of-day choices) and supply (opening and closing hours) are explored.
Tour formation instead of tour generation: In the genuine ABM paradigm, activities should be modeled first and tours should be formed as a means to reach those activities. In this regard, an appealing way to distinguish between three types of activities: 1) Activities with a fixed location and schedule (start and end time). These activities are not bound to work and school but also include doctor/dentist appointments, shows, sport events, dropping-off and picking-up passengers, etc. It is assumed that individuals build their daily schedules and travel tours pivoting off these activities. Joint activities of this type are especially important for constraining schedules of the household members; 2) Activities with a fixed location but flexible schedule like visiting a certain store for a particular shopping type. It is assumed that individuals try to link these activities to the other activities in order to optimize their travel arrangements and capitalize on the schedule flexibility. It can be assumed that most of travel tour skeletons are defined by the first two types of activities; 3) Activities with a flexible location and schedule like grocery shopping or visiting a coffee shop. These activities are most frequently “inserted” in the travel tours depending on the time-space constraints but rarely play a role of the primary destination (except for short non-motorized tours). A combinatorial tour formation model is proposed that address the major activities of first two types while the travel-driven activities should be inserted as additional stops on the tours.
Association for European Transport