Charypar–Nagel: how an agent values time at an activity

In one sentence

A plan scores well when time is spent at activities close to their typical duration — travel is what takes that time away.

Why it matters

Utility grows with the logarithm of the time spent at an activity: steep at first, flattening around the typical duration, where the slope equals the performing rate (+6 utility per hour in this model). A day is scored as it happens — up during activities, down while travelling — so an hour on the road costs the activity time it displaces plus the mode’s own disutility.

Agent-based simulation is usually explained with equations or with a screenshot of a running model. Neither shows why a planner should care. These explainers show the mechanism itself — one person, one day, one score — so that the results on a dashboard stop being a black box.

Sources

• Charypar, D. & Nagel, K. (2005): Generating complete all-day activity plans with genetic algorithms. Transportation 32(4)
• Scoring parameters are typical MATSim values (illustrative); see Horni, Nagel & Axhausen (2016), ch. 3

What you see

1. 00.0Utility curve of an activity
2. 04.0Marginal utility after 7.8 h
3. 07.0Typical duration t* = 8 h
4. 09.0A day, scored
5. 14.0Travel costs activity time
6. 17.0Takeaway

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