Activity-Based Travel Behaviour Modeling in a Microsimulation Framework

Miller, Eric J.; Salvini, Paul A.

doi:10.1016/b978-008044044-6/50027-9

Cited by 8 publications

(8 citation statements)

References 9 publications

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“…Agent-based microsimulation (ABM) is a computational framework for exercising disaggregate models of system behavior (23)(24)(25). As noted above, some form of ABM has become standard practice in current best-practice activity-and tour-based travel demand models.…”

Section: Agent-based Microsimulation: the Next Generation General Discussionmentioning

confidence: 99%

Modeling the Demand for New Transportation Services and Technologies

Miller

2017

Transportation Research Record

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This paper briefly discusses the current state of the art of urban travel demand modeling and research needs in the field. Special emphasis is given to both the challenges and the opportunities posed by modern information technology and the data, transportation services, and travel behaviors that this technology is generating. Travel demand modeling has made very significant strides over the past 20 years, especially in the development of operational activity- and tour-based regional travel demand forecasting systems. These model systems represent first-generation agent-based microsimulation models. Considerable need, opportunity, and scope exist for the development of significantly more powerful second-generation agent-based microsimulation models that build upon emerging big data sets (among other information sources) and high-performance computing. This task, however, will involve the development of new behavioral representations and computational algorithms implemented within much more flexible software environments that both fully exploit available computing power and enable flexible experimentation with and extension of representations of new transportation modes and services and evolving travel behavior.

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Section: Agent-based Microsimulation: the Next Generation General Discussionmentioning

confidence: 99%

Modeling the Demand for New Transportation Services and Technologies

Miller

2017

Transportation Research Record

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“…There has been much discussion in the research community on the microsimulation of travel and activities, see, for example, (8)(9)(10)(11)(12)(13)(14). Advantages of microsimulation include the ability to tabulate impacts for subgroups of the population (for example, low income or elderly), the capability of explicitly modeling realistic travel behavior patterns such as trip chaining and activity scheduling, and the ability to better reflect heterogeneity (and segmentation).…”

Section: Microsimulation Of Travel and Activity Behaviormentioning

confidence: 99%

“…The intricacies of the travel and activity behavior represented in these state of the art model systems vary substantially. For example, the original STEP was trip-based, the Dutch National (15) and Stockholm models (16) are tour-based, the Portland (17) and San Francisco (18) models are day schedule-based, the Columbus model includes the added wrinkle of explicit household interactions (14), and the Canadian ILUTE system (12) integrates land use and activity scheduling with travel demand, just to list a few. In this paper, we take a step back from this seemingly unstoppable growth in complexity to look at what can be done with microsimulation at a more modest scale, exploring advantages as well as comparing to a traditional aggregate approach.…”

Section: Microsimulation Of Travel and Activity Behaviormentioning

confidence: 99%

Making Household Microsimulation of Travel and Activities Accessible to Planners

Walker

2005

Transportation Research Record: Journal of the Transportation R

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There is a large gap between the aggregate, trip-based models used by transportation planning agencies and the activity-based, microsimulation methods being espoused by those at the forefront of research. The modeling environment presented here aims to bridge this gap by providing a palatable way for planning agencies to move towards advanced methods. Three components to bridging the gap are emphasized, including an incremental approach, demonstration of clear gains, and providing an environment that eases initial implementation and allows for expansion. The modeling environment (called STEP2) is a household microsimulator developed in TransCAD, which can be used to implement a 4-step model as well as models with longer term behavior and trip chaining. An implementation for Southern Nevada is described and comparisons are made with the region's aggregate 4-step model. The models perform similarly on numerous counts. A key advantage to the microsimulator is that it provides impacts by socioeconomic group (essential for equity analysis) and individual trip movements (for use in a vehicle microsimulator). A sensitivity analysis indicates that the microsimulation model has less inelastic cross elasticity of transit demand with respect to auto travel times than the aggregate model (aggregation error). The trade-off is that microsimulators have simulation error; results are presented regarding the severity of this error. This work shows that shifting to microsimulation does not necessarily require substantial investment to achieve many of the benefits. One of the greatest advantages is a flexible environment that can expand to include additional sensitivity to demographics and transportation policy variables.

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“…There has been much discussion in the research community on the microsimulation of travel and activities (8)(9)(10)(11)(12)(13)(14). Advantages of microsimulation include the ability to tabulate impact for subgroups of the population (for example, low-income or elderly), to explicitly model realistic travel behavior patterns such as trip chaining and activity scheduling, and to better reflect heterogeneity (and segmentation).…”

Section: Microsimulation Of Travel and Activity Behaviormentioning

confidence: 99%

Making Household Microsimulation of Travel and Activities Accessible to Planners

Walker

2005

Transportation Research Record

View full text Add to dashboard Cite

There is a large gap between the aggregate, trip-based models used by transportation planning agencies and the activity-based, microsimulation methods espoused by those at the forefront of research. The modeling environment presented here is intended to bridge this gap by providing a palatable way for planning agencies to move toward advanced methods. Three components to bridging the gap are emphasized: an incremental approach, a demonstration of clear gains, and a provision of an environment that eases initial implementation and allows for expansion. The modeling environment (called STEP2) is a household microsimulator, developed in TransCAD, that can be used to implement a four-step model as well as models with longer-term behavior and trip chaining. An implementation for southern Nevada is described, and comparisons are made with the region's aggregate four-step model. The models perform similarly in numerous ways. A key advantage to the microsimulator is that it provides impacts by socioeconomic group (essential for equity analysis) and individual trip movements (for use in a vehicle microsimulator). A sensitivity analysis indicates that the microsimulation model has less inelastic cross elasticity of transit demand with respect to auto travel times than the aggregate model (aggregation error). The trade-off is that microsimulators have simulation error; results are presented regarding the severity of this error. This work shows that a shift to microsimulation does not necessarily require substantial investment to achieve many of the benefits. One of the greatest advantages is a flexible environment that can expand to include additional sensitivity to demographics and transportation policy variables.

show abstract

Activity-Based Travel Behaviour Modeling in a Microsimulation Framework

Cited by 8 publications

References 9 publications

Modeling the Demand for New Transportation Services and Technologies

Modeling the Demand for New Transportation Services and Technologies

Making Household Microsimulation of Travel and Activities Accessible to Planners

Making Household Microsimulation of Travel and Activities Accessible to Planners

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