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- W2904139964 abstract "Aiming to alleviate traffic jams, many traffic management strategies/policies are adopted to nudge travelers to rearrange their departure time, or switch from driving to public transport or a nonmotorized mode. Thus, travel behavior has been widely studied to explore how travelers will change their behaviors under certain transportation policies. This chapter covers some of the typical modeling of travel behaviors and introduces several state-of-the-art analytical methods to study traveler's behaviors based on a data fusing method. Some traditional behavior models are based on the max-utility theory and perfect human rationality. The most widely used travel behavior model based on the maximization theory is the discrete choice model. This is operationalized in the modeling structure by making the choice process a function of both the alternative attributes and the characteristics of the traveler. Furthermore, analytical travel behavior models are used to predict traveler's departure time choice and mode switch under such strategies. An agent-based model for travelers’ choices of mode and departure time is utilized here." @default.
- W2904139964 created "2018-12-22" @default.
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- W2904139964 date "2019-01-01" @default.
- W2904139964 modified "2023-09-26" @default.
- W2904139964 title "Urban Travel Behavior Study Based on Data Fusion Model" @default.
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- W2904139964 doi "https://doi.org/10.1016/b978-0-12-817026-7.00005-9" @default.
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