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Activity duration dependent utility in a dynamic scheduling model
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AI
DOI：10.1080/21680566.2024.2436933.png)
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摘要
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We present the use of duration-dependent activity utility within the dynamic scheduling modelScaper, which simulates individuals' full-day activity and travel schedules. InScaper, agents make sequential choices in time which maximize expected future utility and respect time-space constraints. Using Swedish travel survey data, we estimate a new version of the model including piecewise linear utility functions for marginal activity duration by activity purpose. Our model reveals a strong duration dependence for work, leisure, and visit activities with differing functional shapes for each purpose. In simulation, the duration-dependent model better reproduces observed distributions of activity duration and performs as well across other metrics as the model without duration dependence. We illustrate the potential policy applications of the model using a scenario of shortened work days. The duration-dependent model offers useful predictions for the effects of the scenario on commute timing, nonwork activities, time spent at home, and trip chaining.
Keyword:
Dynamic discrete choice
activity-based modelling
random-utility models
scheduling model
activity duration
time geography
期刊
IF:
3.4
论文数:
568
被引数:
1.2K
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