Integration of Activity-Based Modeling and Dynamic Traffic Assignment

Lin, Dung Ying; Eluru, Naveen; Waller, S. Travis; Bhat, Chandra R.

doi:10.3141/2076-06

Cited by 82 publications

(38 citation statements)

References 30 publications

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“…The assignment package computes a (typically dynamic) route equilibrium and feeds the result back as time-dependent zone-to-zone travel impedances. When feedback is implemented, then the activity-based demand model recomputes some or all of its choices based on those travel impedances (Lin et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation

Flötteröd

Nagel

2011

Netw Spat Econ

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This article reports on the calibration and analysis of a fully disaggregate (agentbased) transport simulation for the metropolitan area of Zurich. The agent-based simulation goes beyond traditional transport models in that it equilibrates not only route choice but all-day travel behavior, including departure time choice and mode choice. Previous work has shown that the application of a novel calibration technique that adjusts all choice dimensions at once from traffic counts yields crossvalidation results that are competitive with any state-of-the-art four-step model. While the previous study aims at a methodological illustration of the calibration method, this work focuses on the real-world scenario, and it elaborates on the usefulness of the obtained results for further demand analysis purposes.

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Section: Introductionmentioning

confidence: 99%

Behavioral Calibration and Analysis of a Large-Scale Travel Microsimulation

Flötteröd

Nagel

2011

Netw Spat Econ

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“…Although some frameworks have emphasized linkages between land use and travel demand (4,5,12), other frameworks have focused on the travel demand and network supply interrelationships (13)(14)(15)(16)(17). However, in most of these integration approaches, linkages across model systems are established rather loosely through sequential feedback processes and data exchange mechanisms.…”

Section: Integrated Land Use-transport Model System With Dynamic Timementioning

confidence: 99%

Integrated Land Use–Transport Model System with Dynamic Time-Dependent Activity–Travel Microsimulation

Pendyala

Konduri

Chiu

et al. 2012

Transportation Research Record

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Advances in microsimulation approaches to modeling of urban environments have happened rather independently in three streams of research; namely, land use, travel demand, and network supply. For land use modeling, microsimulation approaches are applied to model the urban form in a region, including the land use choices of individuals, businesses, governments, and developers. Households within a region make choices about their residential location, whereas individuals within a household make choices about their fixed activity locations, including workplace location, school location, and college location (while accounting for intrahousehold interactions and constraints). Businesses make choices about locating their offices and other related facilities. Developers make decisions about development (on empty parcels of land) or redevelopment (on parcels of land with existing facilities). These land use choices, along with the sociodemographic and economic evolutionary processes, government regulations, and zoning policies, make up the urban form of a region (3-5).In the travel demand arena, the field has experienced an increasing use of activity-based microsimulation approaches to travel demand modeling and forecasting. Activity-based approaches explicitly recognize the fact that individuals travel to fulfill their need to engage in activities. The primary output from an activity-based travel demand model is the activity-travel patterns of individuals within a household along a continuous time axis (6). The model system comprises various submodels that closely interact with each other to generate household activity agendas, individual activity schedules, activity linkages, trip chaining, destination, and mode choices, subject to the different household interactions (including interactions among household members) and temporal, spatial, and monetary constraints (7). A rich body of literature describes various implementations of activity-based model systems (8). These model systems differ from each other by the underlying behavioral paradigms that they use to represent activity-travel decision-making behavior and by the various degrees to which they represent choice processes (9).Network assignment is typically the last step in any transport model. Conventional assignment methods do not recognize that transportation networks evolve continuously through the day, and the underlying assumption of static network conditions in many assignment models in practice leads to results that are unlikely to be representative of actual network conditions. With microsimulation models of travel demand now capable of generating demand at a fine temporal resolution (e.g., 1 min), interest in the deployment of dynamic traffic assignment models that explicitly account for network dynamics along a continuous time axis and that thus allow the accurate representation of people's path choices and resulting network conditions is increasing (10). Microsimulation approaches to land use and transport modeling allow realistic representations of the...

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“…Recent comprehensive reviews on activity-travel behavior in transportation networks have been given by Lam and Huang (2002), Arentze and Timmermans (2003), Lin et al (2008), Ramadurai and Ukkusuri (2010), and Dugundji et al (2011). However, the congestion of transportation networks and the inter-relationships between daily activities and travel demand have generated an urgent need for new theoretical models and methodological studies so as to provide better understanding of the activity-travel behavior on networks in response to various changes.…”

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confidence: 99%