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• W2605694530 abstract "Advanced modelling methods and products, such as an integrated advanced travel demand model and a fine-grained time-sensitive network that can operate at statewide, metropolitan and subarea/corridor levels, are required by a number of transportation planning agencies to meet their objectives and address various key challenges. This research develops an application-ready integrated transportation model that can predict, in a future-year scenario or in a hypothetical scenario, both the changes in travel behavioural adjustments and the dynamics in traffic conditions. The integrated framework embeds theoretically sound behavioural foundation by incorporating agent-based searching, information acquisition, learning, knowledge updating and decision-making. Multidimensional travel behaviour, including mode choice, route choice, departure time choice and en-route diversion, is considered. Behavioural user equilibrium is defined without assuming perfect rationality. A dynamic traffic simulation engine is employed to model and simulate real-time traffic conditions. Data exchanges between the travel demand model and the traffic simulation are explained in detail. The integration is demonstrated using a real-world case study. Future applications should cover a wide spectrum of scenarios in transportation planning/policy and traffic operations/control analyses." @default.
• W2605694530 created "2017-04-28" @default.
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• W2605694530 date "2018-07-01" @default.
• W2605694530 modified "2023-10-18" @default.
• W2605694530 title "AgBM-DTALite: An integrated modelling system of agent-based travel behaviour and transportation network dynamics" @default.
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• W2605694530 doi "https://doi.org/10.1016/j.tbs.2017.04.004" @default.
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